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Technologies

  • Oct 21, 2022
  • Ionic vs React Native

    Ionic React and React Native are both excellent options for developing apps, but they have significant differences. We examine the differences in depth and suggest which one your team should use.
    Ionic React and React Native are both excellent options for developing apps, but they have significant differences. We examine the differences in depth and suggest which one your team should use.
    1. The framework & libraries: what pros and cons do I get from the framework or library of choice?
    2. The team: how convenient is the framework for my existing and future team?
    3. The backbone: how reliable, available, and supporting are the creators of the framework?

       1.Which one is more popular?

    Ionic vc React Native npm download

    1. In Ionic The application code can't easily access the native functionalities.
    2. Massive community around the ecosystem. Currently, there are impressive numbers on GitHub repo facebook/react-native. This means that developers are likely to find solutions to the difficulties or issues they are experiencing.
    3. Ability to be integrated into existing native apps.
    4. Application's look and feel as smooth as a native application Reason - React Native is translated to native code, with the benefit of achieving 60 frames per second.
    5. Ionic works with web technologies (HTML, CSS, and JavaScript) and fits well in a team that has no background in the native world.
    6. Every year iOS and Android give OS releases and all these features can be leveraged only in native world.
     
    React Native lonic
    Purpose Learn once, write anywhere Write once, run anywhere
    Language Stack React and JavaScript Web technologies-HTML, CSS, JavaScript, Angular JS, TypeScript
    Nature of apps Cross-platform Hybrid apps
    Developers Facebook Community Drifty.co
    Popular for Native-like and elegant user interfaces across the platforms Using a single code base you can develop an app for iOS, Android, Windows, Web, Desktop, and also PWA (Progressive Web Apps)
    Reusability Of Code The platform-specific code needs to be changed Optimum reusability of code
    Performance Closer native look and comparatively faster Slower than React Native due to WebView
    Code Testing Needs a real mobile device or emulator to test the code Using any browser, the code can be tested
    Learning curve A steep learning curve An easy learning curve due to web technologies, Angular, and TypeScript
    Community and Support Strong and Stable Strong and Stable
    GitHub Stars 66K 34k
    GitHub Contributors 1694 243
    Supported Platforms Android, iOS, UWP Android, iOS, UWP (Universal Windows Platform), and PWA
    Companies Using Facebook, Instagram, UberEATS, Airbnb JustWatch, Untappd, Cryptochange, Nationwide, Pacifica, and many more

    Companies using React Native

      Choose Ionic, if:
    1. You're also planning on building a web or desktop app.
    2. Your development team is most comfortable with web technologies.
    3. Performance optimization isn't critical to your project.

    Conclusion

    Both Ionic React and React Native are great ways for mobile application development. React Native may be a better option for teams targeting iOS and Android only, with more traditional native developers or advanced js developers and an existing repository of native controls. This describes why React Native is so popular among consumer app start-up companies with a background in native app development. Ionic React is a better option for teams with traditional web development skills and libraries who would like to focus on mobile and web (as a Progressive Web App). This explains why Ionic has been so effective with start-ups and enterprise teams with a background in web development. We believe that both developments will exist side by side because they address different requirements in the ecosystem. We are delighted to discuss which platform is best for your team.
     

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    Technologies

  • Oct 06, 2022
  • Jira Integration with GitHub

    The Jira and GitHub integration synchronizes development across tools and leverages automation to eliminate manual steps and reduce delivery time. By integrating GitHub code with Jira projects, developers can focus less on updates and more on creating amazing products.
    The Jira and GitHub integration synchronizes development across tools and leverages automation to eliminate manual steps and reduce delivery time. By integrating GitHub code with Jira projects, developers can focus less on updates and more on creating amazing products.

    OBJECTIVE:

    To configure github with jira through pytest to update results on jira tickets, When Merging a Pull Request the github workflow will be executed, After the workflow execution the status of the jira tickets will be updated as per the result of github workflow execution through pytest

    What is Jira?

    Jira is a web application used as tracking tools for tasks like epic, story, bugs and so on. Jira is available as an open source and paid version.

    Why do we use Jira ?

    It is used for various kinds of projects like business projects, software projects and service projects Applications like Github, slack, jenkins, zendesk etc can be integrated with jira. By using jira a ticket can be created for each type of task to monitor application development,  Here we integrate Github with jira through the pytest framework.

    What is Pytest ?

    Pytest is an automation testing framework in python which is used for testing software applications.

    Why do we use Pytest ?

    Pytest is a python framework, using pytest we can create TDD, BDD as well as Hybrid testing framework used for automation testing like UI, REST API and it is flexible for supporting different actions. Here we are going to execute the test cases that are triggered from the github actions workflow and update the particular jira tickets based on the workflow execution results.

    What is Rest API ?

    REST is abbreviated as (Representational State Transfer) it is an architectural style for interacting between the client and the server, the client sends the request and a response is received from the server in of JSON, XML, or HTML, but json is most commonly used response type because it is readable for both human and machine. Here we interact with the Jira through Rest API, the API Endpoints we are using to interact with Jira is given below rest api

    EXECUTION FLOW OF GITHUB FOR JIRA THROUGH PYTEST

    To update the jira tickets through pytest, we need to know about the Github workflow execution, Jira Rest API endpoints, pytest configurations

    Things we need to know for execution:

    • To create a github workflow file to execute pytest test cases when a PR is merged
    • To configure pytest test cases with jira API endpoints to send the workflow results

    JIRA REST API ENDPOINTS

    Prerequisites for Jira API Integration:

    Steps to create API Token:

    manage acc
    • STEP 3: Click on Security tab and click create and manage API token
    manage api
    • STEP 4: Click on create API Token button:
    create api
    • STEP 5: Provide a label for the token and click create, a new API Token will be generated Copy the token and save the token in a separate file because you cant able to get the same token again

    Encoding the API Token:

    Encoding the Api token can be done in the terminal, to create a base64 encoded token use the following command In LINUX/ mac-os: encoding api In Windows: You can use the link below to encode the api token online https://www.base64encode.org/

    GET Transition ID API:

    • GET:
    https://<JIRA_DOMAIN>.atlassian.net/rest/api/2/issue/<TICKET-ID>/transitions By using this API we can get all the transition details like transition ID transition name The transition ID is default for To-Do, In-progress and Done status, the curl command is given below get transition  
    Transition Status Transition ID
    To-Do 11
    In-Progress 21
    Done 31
    Issue 1 2
    Issue 2 3

    Update Transition Status API:

    Post :

    https://<JIRA_DOMAIN>.atlassian.net/rest/api/2/issue/<TICKET-ID>/transitions This API Endpoint is used to update the transition status of the jira ticket. Ticket ID is passed in the path param and the Transition ID is passed in the body of the request, The status of the ticket will be updated with respect to the transition id, Curl for the following API endpoint is mentioned below, The Transition ID can be obtained by using the Get transition ID API, which is mentioned above update transition

    Add Attachments API:

    Post:

    https://<JIRA_DOMAIN>.atlassian.net/rest/api/2/issue/<TICKET-ID>/attachments This API endpoint is used to add the attachment in a JIRA ticket according to the given Ticket ID and passed file. Use the below curl command add attachmennt

    Search API:

    GET:

    https://<jira_domain>.atlassian.net/rest/api/2/search This API Endpoint is used to get the ticket information using the Jira Query Language (JQL) syntax, the JQL should be passed as an parameter to this API, By using this API we can get the information of all/any of the ticket, An example for JQL to get the ticket information using PR Link which is mentioned in the Github info paragraph field of a jira ticket Example for JQL: example jql

    CONFIGURING GITHUB WITH JIRA:

    There are two ways in configuring github with jira, one is by providing the PR link in a separate field of jira ticket and the other way is by configuring github app in jira

       1. Configuring jira with PR link:

    • We can able to identify the ticket information by providing the PR link in a Jira ticket
    • PR Link should be provided in the custom field of Jira ticket
    • After placing the PR link in custom field, we need to use the Jira Search API endpoint through Jira Query Language(JQL) syntax

       2. Steps to configure PR link in Jira Ticket on custom field:

    • Go to Project Board > Project settings > Issue types
    • Select the Paragraph field type >  Enter the field name and description
    • Click Save changes

       3. Configure github app with jira:

    • To configure Github with jira,Login into Jira, go to Apps➡ Manage Your apps
    github jira
    • Select Github for jira ➡ click connect github organization
    • CLICK Install github for jira on new organization
    • On clicking Install github for jira on new organization select the github organization in which you want to install jira
    • Select repository which you want to configure and click install
    • Now you can see your git repository that have been configured in the github for jira tab

    UPDATING EXECUTION RESULTS TO JIRA TICKET USING PYTEST:

    • All the test cases and the reports report generation for all the test cases are done using pytest
    • After the Workflow execution, the build status and PR link will be added as comments and the reports will be added as attachments to the jira ticket, this is done by the pytest fixture. The pytest fixture is used to execute the conditions before and after the execution of test case, the yield keyword is used to execute the conditions after the execution of all test cases
    update result
    • The teardown module() method calls the Jira API Endpoints for Adding Comments and Attachments.
     

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    Technologies

  • Sep 15, 2022
  • Build APIs in Python Using FastAPI Framework

    FastAPI could be a modern, high-performance, web framework for building APIs with Python language. Good artificial language frameworks make it easy to provide quality products faster.

    FastAPI could be a modern, high-performance, web framework for building APIs with Python language. Good artificial language frameworks make it easy to provide quality products faster. Great frameworks even make the entire development experience enjoyable. FastAPI could be a new Python web framework that’s powerful and enjoyable to use.FastAPI is an ASGI web framework. What this implies is that different requests don’t necessarily sit up for the others before them to end up doing their tasks. Additional requests can do their task completed in no particular order. On the other hand, the WSGI frameworks process requests in a sequential manner.

    ASGI:

    ASGI is structured as one, asynchronous callable. It takes a scope, which could be a dict containing details about the precise connection, sends an asynchronous callable that lets the appliance send event messages to the client, and receives an asynchronous callable that lets the application receive event messages from the client.

    Does FastAPI need Uvicorn?

    The main thing needed to run a FastAPI application in an exceedingly remote server machine is an ASGI server program like Uvicorn.

    Using WSGIMiddleware:

    Need to import WSGIMiddleware.Then wrap the WSGI (e.g. Flask) app with the middleware. Then mount that beneath a path.

    FastAPI Different from other Frameworks:

    Let us walk through a journey of building a CRUD application with FAST API and understand how transactions, persistence/database layer, exception handling, and request/response mapping are done.

    Building a CRUD Application with FastAPI

    Setup:  

    Start by creating a brand new folder to carry your project called "sql_app". create a brand Create and activate a new virtual environment: Next, create the following files and folders for fastapi: Install the following dependencies: In the sql_app/main.py ,and define an entry point for running the fastapi application: In this case, we stated the file to run a
    Uvicorn server. Before starting the server via the entry point file, create a base route in api.py:  

    Difference between Database Models & Pydantic Models:

    FastAPI suggests calling Pydantic models schemas to assist make the excellence clear. Appropriately, let’s put all our database models into a python models.py file and every one of our Pydantic models into a schemas.py file. In doing this, we’ll also have to update database.py and main.py.

    Models.py:

    database.py:

    schema.py:

    FastAPI interactive documentation

    A feature that I like about API is its interactive documentation. FastAPI is based on OpenAPI, which is a set of rules that defines how to describe, create and visualize APIs. OpenAPI needs software, which is Swagger, which is the one that allows us to show the API documented. To access this interactive documentation you simply need to go to “/docs”.

    Structuring of FastAPI:

    By using __init__ everywhere, we are able to access the variables from everywhere in the app, similar to Django.

    Models:

    It is for your database models, by doing this you'll import the identical database session or object from v1 and v2.

    Schemas:

    It is for Pydantic's Settings Management which is extremely useful, you will be ready to use the identical variables without redeclaring it, to work out how it should somewhat be useful for taking a glance at our documentation for Settings and Environment Variables.

    Settings.py:

    It is for Pydantic's Settings Management which is extremely useful, you'll be able to use the identical variables without redeclaring it, to determine how it may well be useful for you take a look at our documentation for Settings and Environment Variables

    Views:

    This is optional if you're visiting render your frontend with Jinja, you'll have something near MVC pattern.

    Core views

    • v1_views.py
    • v2_views.py
    It would look something like this if you wish to feature views.

    Tests:

    It is good to own your tests inside your backend folder.

    APIs:

    Create them independently by APIRouter, rather than gathering all of your APIs inside one file.

    Logging

    It could be a means of tracking events that happen when some software runs. The software’s developer adds logging calls to their code to point out that certain events have occurred. an occasion is described by a descriptive message which might optionally contain variable data (ex. data that's potentially different for every occurrence of the event). Events even have an importance that the developer ascribes to the event; the importance also can be called the amount or severity. Github Link: https://github.com/keerthanakumar-08/FastAPI

    Conclusion

    Modern Python Frameworks and Async capabilities are evolving to support robust implementation of web applications and API endpoints. FAST API is definitely one strong contender. In this blog, we had a quick look at a simple implementation of the FAST API and code structure. Many tech giants like Microsoft, Uber, and Netflix are beginning to adopt. This will result in growing developer maturity and stability of the framework.

    Reference Link: 

    https://fastapi.tiangolo.com/ https://www.netguru.com/blog/python-flask-versus-fastapi

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    Technologies

  • Sep 15, 2022
  • How to use Apache spark with Python?

    Apache Spark is based on the Scala programming language. The Apache Spark community created PySpark to help Python work with Spark.

    Apache Spark is based on the Scala programming language. The Apache Spark community created PySpark to help Python work with Spark. You can use PySpark to work with RDDs in the Python programming language as well. This can be done using a library called Py4j.

    Apache spark:

    Apache spark is an open-source analytics and distributed data processing system for large amounts of data (large-scale datasets). It employs an in-memory caching and an accelerated query execution for quick analytic queries against any size of data. It is faster because it distributes large tasks across multiple nodes and uses RAM to cache and process data instead of using a file system. Data scientists and developers use it to quickly perform ETL jobs on large amounts of data from IoT devices, sensors, and other sources. Spark also has a Python DataFrame API that can read a JSON file into a DataFrame and infer the schema automatically. Spark provides development APIs for Python, Java, Scala, and R. It shares most of its features with PySpark, including Spark SQL, DataFrame, Streaming, MLlib, and Spark Core. We will be looking at PySpark.

    Spark Python:

    Python is well known for its simple syntax and is a high-level language that is simple to learn. Despite its simple syntax, it is also extremely productive. Programmers can do much more with it. Since it provides an easier interface, you don't have to worry about visualizations or Data Science libraries with Python API. The core components of R can be easily ported to Python as well. It is most certainly the preferred programming language for implementing Machine Learning algorithms.

    PySpark :

    Spark is implemented in Scala which runs on JVM. PySpark is a Python-based wrapper on top of the Scala API. PySpark is a Python interface to Apache Spark. It is a Spark Python API that helps you connect Resilient Distributed Datasets (RDDs) to Apache Spark and Python. It not only allows you to write Spark applications using python but also provides the PySpark shell for interactively analyzing your data in a distributed environment.

    PySpark features:

      • Spark SQL brings native SQL support to Spark and simplifies the process of querying data stored in RDDs (Spark's distributed datasets) as well as external sources. Spark SQL makes it easy to blend RDDs and relational tables. By combining these powerful abstractions, developers can easily mix SQL commands querying external data with complex analytics, all within a single application.
     
      • DataFrame A DataFrame is a distributed data collection organized into named columns. It is conceptually equivalent to relational tables with advanced optimization techniques. DataFrame can be built from a variety of sources, including Hive tables, Structured Data files, external databases, and existing RDDs. This API was created with inspiration from DataFrame in R Programming and Pandas in Python for modern Big Data and data science applications.
     
      • Streaming is a Spark API extension that allows data engineers and data scientists to process real-time data from a variety of sources like Kafka and Amazon Kinesis. This processed data can then be distributed to file systems, databases, and live dashboards. Streaming is a fault-tolerant, scalable streaming processing system. It supports both batch and streaming workloads natively.
     
      • Machine Learning Library (MLlib) is a scalable machine learning library made up of widely used learning tools and algorithms, such as dimensionality reduction, collaborative filtering, classification, regression, and clustering. With other Spark components like Spark SQL, Spark streaming, and DataFrames, Spark MLLib works without any issues.
     
      • Spark Core is a general execution engine of Spark and is the foundation upon which all other functionality is built. It offers an RDD (Resilient Distributed Dataset) and supports in-memory computing.

    Setting up PySpark on Linux(Ubuntu)

    Follow the steps below to setup and try pyspark: Please note that python version 3.7 or above is required. Create a new directory. Navigate to the directory. Build and enable a new virtual environment Install spark To check pyspark version

    PySpark shell

    Pyspark comes with an interactive shell. It helps us to test, learn and analyze data in the command line. Launch pyspark shell with command line ‘pyspark’. It launches the pyspark shell and gives you a prompt to interact with Spark in the Python language. To exit from spark shell use exit()

    Create pyspark Dataframe:

    Like in pandas, here also we can create dataframe manually by using these two methods toDF() and createDataFrame(), and also from JSON, CSV, TXT, XML formats by reading from S3, Azure Blob file systems e.t.c. First, create columns and datas

    RDD dataframe:

    An existing RDD is an easy way to manually create a PySpark DataFrame. First, let's create a Spark RDD from a List collection by calling the parallelize() function from the SparkContext. This rdd object is required for all of the following examples. A spark session is an entry point for the spark to access components. To create a Dataframe using toDF() method, we have to build a spark session and then pass the data as an argument to parallelize. Finally, we use “toDF(columns)” to specify column names as in the below code snippets. To createDataframe using createDataFrame() method: We have already created a rdd object with data and a spark session. We can use that object in creating a dataframe. We pass the rdd object as an argument for the createDataFrame() method and use toDF(columns) to specify the column names.

    Kafka and PySpark:

    We are going to use pyspark to produce a stream dataframe to Kafka and consume the stream dataframe. We need kafka and pyspark for the same. We have already setup pyspark in our system, Now we are going to setup kafka in the our system. If you have already setup kafka you can skip this, otherwise you can setup kafka by following these steps: Set up Kafka using Docker compose: Docker Compose is used to run multiple containers as a single service and it works on all environments. Docker Compose files are written YAML files. Now, create docker-compose YAML file named  docker-compose.yml for Kfka. Enter the following and save the file. It will run everything for you via Docker. From the terminal, navigate to a directory containing the docker-compose.yml (which was created in the previous step) and run the below command to start all services: Output Now run the below code to get into docker. It will create a new Bash session in the container kafka. Create Kafka topic named as test_topic by running the below code Exit from container bash session by using bash-5.1# exit command. Now we have set-up Kafka and have created Kafka topic to produce and consume dataframe.

    Produce CSV data to kafka topic, Consume using PySpark :

    Produce CSV data to kafka topic :

    For that we need a CSV. Download or create your own CSV file Install the kafka-python  package in a virtual environment. kafka-Python is a python client for the Apache Kafka distributed stream processing system. With pythonic interfaces, kafka-python is intended to operate similarly to the official java client. In the below code we have configured Kafka producer and created an object with it. In config we have to give info like bootstrap server and value_serializer. serializer instructs on how to turn the key and value objects the user provides with their ProducerRecord into bytes. Now read data from CSV file as dictionary : We have created a producer object and data from CSV, To produce data to kafka, iterate to csv data. Now create a py file named demo_kafkaproducer.py in pysaprk_demo directory. Copy the below code to py file. It will read data from CSV and produce data to Kafka topic. We have produced data to Kafka. Now we are going to consume data stream from Kafka How to read data stream from Kafka topic?   To read the data Stream from the Kafka topic, we have to follow the below steps:  First, set the packages to environment for pysaprk shell, spark stream, and spark sql We have setup the environment. Now we have to create a spark session. SparkSession is the entry point to PySpark. Session will be created using SparkSession.builder. Follow the block of code to create sparksession and read stream dataframe from kafka Now we have consumed stream data from Kafka and created dataframe named as stream_df Below is the block of code to create schema/StructType,

    What is schema/StructType in spark ?

    It defines the structure of the DataFrame. We can define it using StructType, which is a collection of StructFields that define the column name, DataType, column nullability, and metadata. Below code will write the data frame stream on console Output: Now create a py file named demo_kafkaconsumer.py in pysaprk_demo directory. Copy the below code to the py file. It will read stream dataframe from Kafka topic using pyspark, and write dataframe data in console.

    Conclusion :

    One of the popular tools for working with Big data is Spark. It has the PySpark API for Python users.This article covers the basics of data frames, how to install PySpark on Linux, what spark and PySpark features are, and how to manually generate data frames using the toDF() and createDataFrame() functions in the PySpark shell. Due to its functional similarities to pandas and SQL, PySpark is simple to learn and use. Additionally, we look at setting up Kafka, putting data into Kafka, and using PySpark to read data streams from Kafka. I hope you use this information and put it to use in your work.

    Reference Link:

    Apache Spark:
    https://spark.apache.org/docs/latest/api/python/getting_started/install.html Pyspark : https://sparkbyexamples.com/pyspark-tutorial/ Kafka: https://sparkbyexamples.com/spark/spark-streaming-with-kafka/

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    Technologies

  • Sep 14, 2022
  • Resemblance and Explanation of Golang vs Python

    Everyone has been looking for the best programming language to use when creating software and also there has recently been a battle between Golang and Python.

    Everyone has been looking for the best programming language to use when creating software and also there has recently been a battle between Golang and Python. I was contemplating which would be the better. Then I learned that Go was created and released in 2009, but it gained popularity quickly in comparison to Python. Both Golang and Python are general-purpose programming languages used to create web applications. These two appear to be very different. In this article, we will look at a comparison of these two languages.

    Golang

    Golang is a procedural, compiled, and statically typed programming language(syntax similar to C). It was developed in 2007 by Ken Thompson, Robert Griesemer, and Rob Pike at Google but launched in 2009 as an open-source programming language. This language is designed for networking and infrastructure-related applications. While it is similar to C, it adds a variety of next-gen features such as Garbage collection, Structural typing, and Memory management. Go is much faster than many other programming languages. Kubernetes, Docker, and Prometheus are written in it. (developed using this language or written in it)

    Features of Golang

    Simplicity

    The developers of the Go language focus on credibility, readability, and maintainability by incorporating only the essential attributes of the language. So we can avoid any kind of language complications resulting from the addition of complex traits.

    Robust standard Library

    It has a strong set of library packages, making it simple to compose our code.

    Web application building

    This language has garnered as a web application building language owing to its easy constructs and more agile execution speed.

    Concurrency

    • Go deals with Goroutines and channels. 
    • Concurrency effectively makes use of the multiprocessor architecture.
    • Concurrency also helps huge programs scale more consistently.
    • Some notable examples of projects written in Go are Docker, Hugo, Kubernetes, and Dropbox.

    Speed of Compilation

    • Go offers a much more powerful speed of completion and compilation than several other popular programming languages.
    • Go is readily parsable without a symbol table.

    Testing support

    • The "go test" command in Go allows users to test their code written in '*_test.go' files.

    Pros:

    • Ease to use - Go’s core resembles C/C++, so experienced programmers can pick up the basics fast, and Simple syntax is easy to understand and learn
    • Cross-platform development opportunities - Go can be used with various platforms like UNIX, Linux, Windows, and Other Operating systems, and Mobile devices also.
    • Faster compilation and execution - Go is a compiler-based language so it completely reads the code and executes due to this it executes faster than c,c++, and java.
    • Concurrent - Run various processes together and effectively

    Cons:

    • Still developing - Still in development
    • Absence of GUI Library - There is no native support
    • Poor Error handling - The built-in errors in Go don't have stack traces and don't support the usual try/catch handling techniques.
    • Lack of frameworks - Minimal amount of frameworks
    • No OOPS Support
    Here is the simple "Hello World" programme in the Go language.

    Output:

    Let's discuss the above program,
    • package main - Every Go program begins with code inside the package main
    • Import “fmt” - its an I/O function.
    • func main - This function always needs to be placed in the main package.{} Here we can write our code/logic.
    • fmt.Println - Print function, print the text on the screen.

    Why Go?

    • It's a statically strongly typed programming language with a great way to handle errors.
    • It allows using static linking to combine all dependency libraries and modules into one single binary file based on the type of the OS and architecture.
    • This language performs more efficiently because of its CPU scalability and concurrency model.
    • This language offers support for multiple libraries and tools, so it does not require any 3rd party libraries.
    Frameworks for Web Development: Gin, Beego, Iris, Echo, and Fiber

    Python

    Python is a universal, high quality and very popular programming language. Python was introduced and developed by Guido van Rossum in the year of 1991. Python is used in machine learning applications, data science, web development, and all modern software technologies. Python has an easy-to-learn syntax that improves readability and reduces program maintenance costs. Python code is interpreted when it is converted to machine language at run time. It is the most widely used programming language because of its tightly typed and dynamic characteristics. Python was originally used for trivial projects and is known as a "scripting language". Instagram, Google, and Spotify use Python and its frameworks.

    Features of Python

    • Free and open source
    It's free and open source, which means the source code is available to the public. So we easily download and use it
    • Easy to code
    Python is beginner-friendly because it prioritises readability, making it easier to understand and use. Its syntax is similar to the English language, making it simple for new programmers to enter the development world.
    • Object-oriented programming
    OOPS is one of the essential features of Python. Python supports the concepts of classes, objects, encapsulation, and object-oriented language.
    • GUI Programming support
    A graphical user interface can be developed by using modules such as PyQt5, PyQt4,wxPython, or Tk in python.
    • Extensible and portable
        • Python is an extensible language.
        • We can formulate some Python code into the C or C++ language.
        • Furthermore, we can compile that code in the C or C++ language.
        • Python is also a very portable language.
        • If we have Python code for Windows and want to run it on platforms such as Unix, Linux, and Mac, we do not need to change it. This code is platform-independent.
    • Interpreted and High-level language
        •  Python is a high-end language.
        • When we formulate programs in Python, there is no need to remember the system architecture, nor do we need to manage the memory.
        • Like in other programming languages, there is no requirement to compile Python code, making it easy to debug our code.
        • Python's source code is converted to an instantaneous form known as bytecode. Python is classified as an interpreted language because Python code is executed line by line.
     

    Pros:

    • Simple syntax: Easy to read and understand
    • Larger Community support: Python community is vast
    • Dynamically typed: The variable type is not required to be declared.
    • Auto memory management: Memory allocation and deallocation methods in Python are automatic because the Python developers created a garbage collector for Python so that the user does not have to manually collect garbage.
    • Embeddable:  Python can be used in embedded systems
    • Vast library support:  Lots of Libraries are available. For Example, TensorFlow, Opencv, Apache spark, Requests and Pytorch etc.,

    Cons:

    • Slow speed
    Python is an interpreted language, so the code will be executed line by line, which often results in slow execution
    • Not Memory Efficient
    Python's auto-memory management makes it unsuitable for memory-intensive tasks. Because of the flexibility of the data types, memory consumption is high.
    • Weak in mobile computing
    Python is typically used for server-side programming. It is not used in the development of client-side or mobile applications. because it is inefficient in terms of memory and processing speed.
    • Runtime errors
    Because Python uses dynamic typing, the data type of a variable can change at any time. In the future, a string could be stored in an integer number variable, causing runtime issues.
    • Poor database access 
    Database access is limited in Python. When compared to popular technologies such as JDBC and ODBC, Python's database access layer is found to be somewhat underdeveloped and primitive. It cannot, however, be used in enterprises that require the smooth interaction of complex legacy data.   Here is a simple "Hello World" programme written in Python.

    Why Python?

    Python is platform-independent; it runs on (Windows, Mac, Linux, Raspberry Pi, etc.). Python has a simple syntax that is related to that of the English language. Python's syntax allows programmers to write programmes with fewer lines than in other programming languages. Python is an interpreter-based language. As a result, prototyping can be completed quickly. Python can be processed as procedural, object-oriented, or functional. Frameworks for Web Development: Django, Flask, Fastapi, Bottle, etc.

    Comparison of Go vs Python:

     

    Case studies:

    Concurrency:

    Concurrency is the concept of multiple computations happening at the same time. Concurrency is well supported in Go via goroutines and channels. A goroutine is a function that can run alongside other functions. Channels allow two goroutines to communicate with each other and synchronise their execution.

    Output:

    Concurrency is the main advantage in Go compared to Python. Because Python is unsuitable for CPU-bound concurrent programming. In python, we use the Multiprocessing concept to achieve concurrency.

    Exception Handling :

    Output :

      Python supports exception handling, but Go doesn't.  

    Go vs Python: Which is Better?

    When it comes to productivity, Golang is the best language to learn to become a more productive programmer. The syntax is restricted, and the libraries are much lighter because there is less code to write; tasks can be completed in fewer lines of code. Python consists of a large number of packages and libraries. Python has the advantage in terms of versatility due solely to the number of libraries and syntax options. However, flexibility comes at a cost, and that cost is productivity. Which language is more productive in this Python vs Golang battle? The winner is Golang, which is designed to be more productive, easier to debug, and, most importantly, easier to read. Python is without a doubt the most popular choice for developers looking to create a machine learning model. The reason for this is that Python is the most popular language for machine learning and is the home of TensorFlow, a deep learning framework built on Python. Learning a programming language like Python, which almost resembles pseudo-code, is an added benefit that makes learning easier. On the other hand, Golang is super fast, and effortless to write and comes along with Go doc, which creates documentation automatically, making the life of the programmer easier.

    Conclusion

    Python and Golang are winners in their respective areas depending on the specific capabilities and underlying design principles of the language

    1.Maturity

    It's difficult to make conclusions about Go vs Python because comparing a mature language to a young one doesn't seem fair. Python may be the winner here

    2.In ML and Data science Usage

    Python is the leading language not only for machine learning and data analysis but also for web development. Golang has only been around for a decade, and it has yet to establish a robust ecosystem or community.

    3.Performance

    The main advantage of Go is speed. However, Python is slow when it comes to code execution.

    4.Microservices and Future Readiness

    When it comes to microservices, APIs, and other fast-loading features, Golang is better than Python. Go is equipped to be a future-ready web development framework with a lot of adoption around the world of containers.

    Referral Link:

    Python -
    https://docs.python.org/3/ Go - https://go.dev/doc/
     

    blog-img

    Technologies

  • Sep 08, 2022
  • Flask vs FastAPI – A Comparison Guide to Assist You Make a Better Decision

    Flask and FastAPI are python-based micro-frameworks for developing small-scale data science and machine learning web and apps.
    Flask and FastAPI are python-based micro-frameworks for developing small-scale data science and machine learning web and apps. Despite the fact that FastAPI is a relatively new framework, an increasing number of developers are using it in their new projects. Is it just a marketing ploy, or is FastAPI better than Flask? We've put together a comparison of the major pros and cons of Flask and FastAPI to assist you in deciding which will be the ideal choice for your next data science project.

    What is Flask?

    Flask is a micro web framework written in python. Armin Ronacher came up with the idea.  Flask is built on the WSGI (Web Server Gateway Interface) Werkzeug toolkit (For the implementation of  Request and Response) and the Jinja2 (template engine). WSGI is a standard for web application development.  It is used to build small-scale web applications and Rest API Flask's framework is more explicit than Django's framework, and it is also easier to learn because it requires less basic code to construct a simple web application.  

    In this real-world top Companies are using Flask

    flask-microframework

    What makes Flask special?

    • Lightweight Extensible  Framework.
    • Integrated unit test support.
    • Provided development server and debugger.
    • Uses Jinja templating.
    • Restful request handling.

    When should you use a Flask?

    • Flask is old and it has Good Community support
    • For Developing web applications and creating a quick Prototype.

    Flask Web Application Development

    1. Creation of a virtual environment
    1. The venv environment is being restarted.
    1. Database.
    1. Login and register for several users
    • Mode Debug
    • Creating a User Profile Page
    • Creating an avatar
    1. Handling errors
      1. Virtual environment creation environment-creation 2. Making Necessary Installation necessary-install

    Build a sample webpage using Flask, it will return the string

    webpage-flask After Running the application, we need to visit
    http://127.0.0.1:5000/ application

    Pros

    • Flask has a built-in development server, integrated support, and other features.
    • Flask Provides integrated support for unit tests.
    • Flask Uses Jinja2 templates.
    • Flask is just a collection of libraries and modules that helps developers to write their applications free without worrying about low-level details like   Protocols and Thread Management.
    • Because of its simplicity, Flask is particularly beginner-friendly, allowing developers to learn easier.  It also allows developers to construct apps quickly and easily.

    Cons

    • Flask makes use of Modules, which is third-party participation that might lead to security breaches. Modules are the intermediary between the framework and the developer.
    • Flask does not create automatic documentation;  They need several extensions like Flasgger and Flask RESTX  and also require additional setup.
    • Flask has a single source, which suggests that it will handle each request one by one, therefore regardless of how many multiple requests there are, it will still take them in turns, which takes extra time.
     

    What is FastAPI:

    FastAPI is built in ASGI (Asynchronous Server Gateway Interface) and pydantic, Starlette. This framework is used for building a web application and RestAPI. In FastAPI we need uvicorn to run the server. There is no built-in development server So the ASGI server Uvicorn is required to run the FastAPI application. The best thing that we Highlight in the FastAPI is documentation. It will generate documentation and create Swagger UI. which helps the developers to test endpoints effectively. In fast API, Also includes data validation and returns an Explanation of the error when the user enters the invalid data. It implements all of the OpenAI requirements and Swagger for these specifications. As a developer we will concentrate on developing logic; the rest is handled by the FastAPI. what-is-fastapi In this modern world, the top Websites are moving to FastAPI. The website was developed using FastAPI. developed-fastapi

    When should you use a FastAPI?

    • Has Good speed and performance when compared with Flask.
    • Decreasing bugs and Errors in code.
    • It Generates  Automatic documentation
    • Built-in data validation.

    What makes FastAPI special?

    • Fast Development
    • Fewer Bugs
    • High and Fast Performance
    • Automatic swagger UI
    • Data validation
      1. Virtual environment creation environment-creation 2. Making Necessary Installation necessary-install Build a webpage using FastAPI, It return string webpage-fastapi After running the application, we need to visit http://127.0.0.1:8000/docs or http://127.0.0.1:8000/redoc   Docs fastapi Redoc Redoc

    Pros

    • FastAPI is considered as one of the fastest Framework in python, It has an native async support and provides a simple and easy-to-use dependency injection framework. Another advantage to consider is built-in data validation and Have Interactive API documentation support .
    • Dependency Injection support
    • Fast API is based on standards such as JSON Schema (a tool for validating the structure of JSON data), OAuth 2.0 (an industry standard protocol for authorization), and OpenAPI (an open application programming interface).

    Cons

    • In FastAPI there is insufficient Security and also it will support OAuth.
    • Because FastAPI is relatively new, the community is small compared to other frameworks, and regardless of its detailed documentation, there are very few external educational materials.

    Difference between Flask and FastAPI:

    Both offer the same features but the implementation is different. The main difference between Flask and FastAPI is that Flask is built in WSGI (Web Server Gateway Interface) and FastAPI is built in ASGI(Asynchronous Gateway Interface). So, the FastAPI will support concurrency and asynchronous codes. In FastAPI there is automatic documentation for Swagger UI(docs and redocs), But in Flask we need to add some extensions like Flasgger or Flask RESTX and some dependencies setup. Unlike Flask, FastAPI provides data validation for defining a specific data type and it will raise an Error if the user enters an invalid data type. performance-table

    Performance:

    FastAPI uses an Async library which is helpful to write concurrent code. Async is greatly helpful for doing tasks that involve something like fetching data from API and querying from a database, reading the content of the file and FastAPI has ASGI whereas Flask is a WSGI Application

    Data Validation:

    There is no data validation in Flask. So Flask allows any kind of data type. In Flask the data validation will be handled by developers. But In FastAPI there is inbuilt data validation (pydantic). So it will raise an error when it gets an invalid data type from the user. This is useful for developers to interact with the API endpoints.

    Documentation:

    Flask doesn’t have any inbuilt documentation for swagger UI. We need to add some extensions like Flassger and Flask-RESTEX and some dependency setups. But In FastAPI it generates an automatic swagger UI when the API is created. For accessing the auto-generated swagger UI hit the endpoint with /docs or /redoc. It will show all the endpoints in your application.  

    HTTP METHODS:

    Flask FastAPI
    @app.route("/get", methods= ['GET']) @app.get('/get', tags=['sample'])
     

    Production Server

    At some point, you’ll want to deploy your application and show it to the world.
    • Flask
    Flask makes advantage of WSGI, which stands for Web Server Gateway Interface. The disadvantage is that it is synchronous. This means that if you have a large number of requests, they will have to wait in line for the queue to finish.
    • FastAPI
    FastAPI is an ASGI (Asynchronous Server Gateway Interface), web server, which is lightning fast because it is Asynchronous. So, if you have a lot of requests, they don't have to wait for the others to finish before being processed.

    Asynchronous Tasks

    • Flask
    In Flask Async can be performed by thread or multiprocessing or use some tools like celery, Create await/async for handling routes

    Installations

    flask-install

    Example:

    example tasks

    FastAPI:

    In FastAPI there is a default AsyncIO. So we can simply add the async keyword before the function. fastapi-async

    FastAPI was Built with Primary concerns

    • Speed and Developer Experience
    • Open Standards.
    1. FastAPI can connect Starlette, Pydantic, OpenAPI, and JSON Schema.
    2. FastAPI uses Pydantic for data validation and Starlette for tooling making it twice as fast as Flask and equivalent to high-speed web APIs written in Node or Go.
    3. Starlette + Uvicorn supports async requests, while Flask does not.
    4. Data validation, serialization and deserialization (for API development), and automatic documentation are all included (via JSON Schema and OpenAPI).
     

    Which Framework is Best for AI/ML

    Both Flask and FastAPI are the popular Framework for developing Machine learning and web applications. But most data scientists and Machine learning developers prefer Flask. Flask is the primary choice of Machine learning developers for writing the API’s . A few disadvantages of using Flask is time consuming for running the big applications. The major disadvantage in flask is to add more dependencies by adding plugins and the other one is lack of Async support whereas FastAPI supports Async by default . FastAPI is used for the creation of ML instances and applications. In the machine learning community Flask is one of the popular frameworks.Flask is perfect for ML engineers who want to create web models. FastAPI, on the other hand, is the best bet for a framework that provides both speed and scalability.  

    Migrating Flask TO FastAPI :

    migration

    Yes, It is possible to migrate a Flask application to FastAPI. In FastAPI there is native async support. Flask also supports Async but is not as extensive as FastAPI. There is some syntactical difference between Flask and FastAPI.  

    The Application object in Flask and FastAPI is

    object-flask-fastapi

    Simple Example for Migrate Flask to FastAPI:

    • Flask Application
    migrate-fastapi  

    1.To Migrate the Flask to FastAPI we need to install and import libraries.

     

    fastapi-install

     

    2. URL Parameters (/basic_api/employees/)

     

    url-parameter

    In FastAPI the request methods are defined in the methods FastAPI objects. For Example @app.get, @app.post, @app.put.  

    The Request Methods in Flask and FastAPI is

    method-flask-fastapi Here in the put request route, we are passing a body as an Employee object. And also we will create a new class called Employee and inherit it from the base model. And pass the type of the URL parameter employee_id within the route, instead of that pass the type of the parameter in employee_get()  

    Query Parameters:

      Like URL Parameters, Query parameters are also used for managing the state(For sorting or Filtering).  
    • Flask

    query-flask
    • FastAPI

    query-fastapi  

    Run the server in Flask And FastAPI

      Main (Flask) server-flask Main (FastAPI) server-fastapi  

    And Finally the FastAPI Application looks like :

     
    • FastAPI Application
    fastapi-application Use ASGI Application web server Uvicorn to run the FastAPI application (uvicorn.run(app)).  

    When Should you choose FastAPI instead of Flask and Django?

    • Native Async Support:The FastAPI web framework was created using the ASGI web server. Native asynchronous support eliminates inference latency.
    • Improved latency: As a high-performance framework, the framework's total latency is lower when compared to Flask and Django.
    • Production-ready:With the FastAPI web framework's auto validation and short defaults, developers may easily design web apps without rewriting the code.
    • High Performance: Developers have access to the key functionalities of Starlette and Pydantic because they are compatible. Needless to say, Pydantic is one of the quickest libraries, and as a result, overall speed improves, making FastAPI the preferred library for web development.
    • Learn Simple:This is a minimalist framework so it is easy to understand and learn.
     

    Flask Or FastAPI: Which is better

     
    S.No Flask FastAPI
    1. Flask is a micro web framework to develop small-scale web applications and Rest API. Flask is depends on WSGI toolkit (werkzeug, Jinja2) FastAPI is considered one of the Fastest frameworks compared to the flask. FastAPI is built in Pydantic and starlette.
    2. Flask is built in Web Server Gateway Interface(WSGI) FastAPI is built in Asynchronous Server Gateway Interface(ASGI)
    3. It does not have any inbuilt documentation such as swagger UI and needs to add some extensions like Flasgger or Flask RESTX. In FastAPI it has inbuilt documentation like (docs and redocs).
    4. There is no Inbuilt data validation in Flask, we need to define the data type in requests. In FastApI there is an Inbuilt data validation that will raise the error if the user provides an invalid data type.
    5. Flask is more flexible than Other frameworks. FastAPI is flexible in code standards and it does not restrict the code layouts.
     

    Conclusion:

    After learning about both Flask and FastAPI. Both are used to create a Web application and Rest API. But FastAPI is better when compared with Flask. Because FastAPI has a native ASGI support (Asynchronous Server Gateway Interface). So it is Faster and High in performance. Also, it has inbuilt documentation(Swagger UI) and data validation. FastAPI has High and Fast performance, Efficiency and it's easy to understand and learn. When compared to Flask, FastAPI has less community support but it reaches a lot in a short period of time.  

    Reference link:

    Flask: https://flask.palletsprojects.com/en/2.2.x/
    FastAPI: https://fastapi.tiangolo.com/

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    Case Studies

  • Apr 18, 2022
  • 11 essentials devops metrics to boost productivity

    As businesses continue to grow and demand more from their technology departments, DevOps has emerged as a key contributor to increased productivity.
    As businesses continue to grow and demand more from their technology departments, DevOps has emerged as a key contributor to increased productivity. When some say it's about new tools, some claim it’s a change in culture, while others associate it with the engineer role, DevOps is the idea of functionality and operability together. By integrating DevOps practices into an organization's overall IT strategy, businesses can achieve efficiencies in both the development and deployment stages of software projects, leading to a more streamlined and efficient process. The very interesting thing about DevOps is that while frequently, its mission is to create a change in the culture of an organization, this change requires far more than coordination: it also requires pure collaboration and co-laboring. You’ll see this same principle of empathy at work within your company or in your own team which boosts productivity. It is a way of working that allows teams to manage software development and IT operations together. This helps to increase the efficiency of the organization, while also reducing the risk of defects.

    The technology landscape is always evolving, whether it is through new infrastructure, or a new CO tool coming out to help you manage your fleet better

    —Mike Kail

    How does DevOps work?

    DevOps is one of the most important concepts in modern software development. It's a collaboration method that encourages communication and cooperation between developers, operations staff, and testers. DevOps helps to speed up the process of creating and deploying software by automating many of the manual tasks while enhancing the problem-solving aspect all on its own. Cloud computing being centralized offers standard strategies for deployment, testing, and dynamic integration of the produced collaboration. It’s a survival skill of adapting according to the ever-changing and demanding market requirements.

    TIP

    DevOps helps you manage things effectively so that teams can spend more time on research, development, and betterment of the product.

    Metrics for DevOps are crucial for optimizing and establishing a higher-quality software development process.

    Here are 11 essential DevOps metrics to increase productivity in organizations:

    Frequency of deployment

    It is vital to promote and sustain an ambitious edge by providing updates, new functions, and enhancements to the product's quality and technological efficiency. Increased delivery intensity enables greater adaptability and compliance with changing client obligations. The objective should be to enable smaller deployments as frequently as possible. Software testing and deployment are significantly more comfortable with smaller deployments.

    TIP

    Organizations can use platforms such as Jenkins to automate the deployment sequence from staging to production. Continuous deployment ensures that the code is automatically sent to the production environment after passing all of the test cases in the QA environment.

    Time required for deployment

    This indicator indicates how long it will take to accomplish a deployment. While deployment time may look trivial at first glance, it is one of the DevOps indicators that indicates possible difficulties. If deployment takes hours, for example, there must be an issue. As a result, concentrating on smaller but more regular deployments is beneficial.

    Size of the deployment

    This measure is used to monitor the number of feature requests, and bug patches sent to production. The number of individual task items varies significantly depending on their size. Additionally, you can keep track of the number of milestones and other parameters for deployment

    Enhance Customer satisfaction

    A positive customer experience is important to the longevity of a product. Increased sales volumes are the outcome of happy customers and excellent customer service. As a result, customer tickets represent customer satisfaction, which then reflects the DevOps process quality. The fewer the numbers, the higher the quality of service.

    Minimize defect escape rate

    Are you aware of the number of software defects detected in production versus QA? To ship code rapidly, you must have confidence in your ability to spot software defects before they reach production. Your defect escape rate is a good DevOps statistic for monitoring the frequency with which those defects make their way into production.

    Understanding cost breakups

    While the cloud is an excellent approach to reducing infrastructure expenses, certain unplanned failures and incidents can be rather costly. As a result, you should prioritize collecting and decreasing unnecessary costs. DevOps plays a major role here. Understanding your spending sources might assist you in determining which behaviors are the most expensive.

    Reduce frequent deployment failures

    We hope this never occurs, but how frequently do your releases result in outages or other severe issues for your users? While you never want to undo a failed deployment, you should always plan for the possibility. If you are experiencing troubles with failed deployments, monitor this indicator over time.

    Time required for detection

    While minimizing or even eliminating failed changes is the optimal strategy, recognizing errors as they occur is crucial. The time required to discover the fault will affect the appropriateness of existing response actions. Protracted detection times may impose limits on the entire operation. Establishing effective application monitoring enables a more complete picture of "detection time."

    Error Levels

    It is vital to monitor the application's error rate. They serve as a measure not only of quality difficulties but also of continuing efficiency and uptime issues. For excellent software to exist, the best methods for handling exceptions are necessary.

    TIP

    Track down and record new exceptions thrown in your code that occur as a result of a deployment.

     

    Application Utilization & Traffic

    You may wish to verify that the quantity of transactions or users logging into your system seems to be normal post-deployment. If there is a sudden lack of traffic or a big increase in traffic, something may be amiss. Numerous monitoring technologies are available to provide this data.

    Performance of the application

    Before launching, check for performance concerns, unknown defects, and other issues. Additionally, you should see changes in the overall output of the program both during and after deployment. To detect changes in the usage of particular queries, web server operations, and other requirements following a release utilize monitoring tools that accurately reflect the changes.

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    Case Studies

  • Apr 04, 2022
  • Prometheus vs Influxdb : Monitoring Tool Comparison

    When it comes to data storage, there are few alternatives that can compete with the venerable Prometheus, such as InfluxDB. But what if you need more than just collected data? What if you need real-time insights into your systems?

    When it comes to data storage, there are few alternatives that can compete with the venerable Prometheus, such as InfluxDB. But what if you need more than just collected data? What if you need real-time insights into your systems? Another powerful platform for real-time data analytics and storage is InfluxDB. Let's compare how they fare with one another.

    Prometheus is a memory-efficient, quick, and simple infrastructure monitoring system. InfluxDB, on the other hand, is a distributed time-series database used to gather information from various system nodes. In this article, we are going to compare Prometheus and InfluxDB. Both systems have their strengths and weaknesses, but they are both effective monitoring tools. If you are looking for a system that can monitor your database servers, then Prometheus is a good option. If you are looking for a system that can monitor your entire infrastructure, then InfluxDB is a better choice.

    What exactly is Prometheus?

    Prometheus is a time-series database and monitoring tool that is open source. Prometheus gives its users sophisticated query languages, storage, and visualization tools. It also includes several client libraries for easy interaction. Prometheus can also work with various systems (for example, Docker, StatsD, MySQL, Consul, etc.)

    TIPS

    Prometheus can be great for monitoring as long as the environment does not exceed 1000 nodes. Prometheus + Grafana = best ecosystem

    What is InfluxDB?

    By InfluxData, Inc., a database management system called InfluxDB was created. InfluxDB is open-source and cost-free to use. The InfluxDB Enterprise version is installed on a server inside a corporate network and comes with maintenance contracts and unique access controls for business customers. A web-based user interface for data ingestion and visualization is also included in the new InfluxDB 2.0 version, which operates as a cloud service that is fully customizable.

    TIPS

    When it comes to storing monitoring metrics, InfluxDB excels (e.g. performance data). If you need to store different sorts of data, InfluxDB is not the best option (like plain text, data relations, etc.)

    Let's see how these differ from one another

    Features Prometheus InfluxDB
    Data Gathering Prometheus is a system that operates on the principle of pull. The metrics are published by an application at a certain endpoint and Prometheus retrieves them on a regular basis. The system InfluxDB is based on is a push-based system. It requires an application to push data into InfluxDB on a regular basis.
    Storage Prometheus and InfluxDB both follow the key/value datastores. However, these are executed very differently on the two systems. Each metric in Prometheus is kept in its own file and is stored in indices that use LevelDB. Metrics recording and monitoring based on those are the major uses of Prometheus. Both the indices and the metric values are stored in monolithic databases by InfluxDB. Compared to Prometheus, InfluxDB often uses more disc space. The best database for event logging is InfluxDB. So we have a choice based on the requirements.
    Extensibility and Plug-ins Prometheus’ key benefit is its widespread community support, which stems from its CNCF-accredited project status. Many apps, particularly cloud-native applications, already support Prometheus. While InfluxDB has a lot of integrations, it doesn’t possess as many as Prometheus.
    Case Studies Prometheus was designed for monitoring, specifically distributed, cloud-native monitoring. It shines in this category, with several beneficial integrations with current products. While InfluxDB can support monitoring, it is not as well known as Prometheus for this purpose. As a result, you may have to develop your own integrations. If you want to do more than a mere monitoring tool, InfluxDB is a fantastic solution for storing time-series data, such as data from sensor networks or data used in real-time analytics.
    Query language Prometheus uses PromQL, a language that is much easier and has no connection to conventional SQL syntax. Let's say we want a number for CPU load that is greater than 0.5. In that case, we can simply enter CPU load>0.5 in the Prometheus command prompt. For its querying purposes, InfluxDB uses a standard SQL syntax known as InfluxQL. For instance, we could write select * from tbl where CPU load>0.5 in the Prometheus cell. This seems simple to an associate with a background in SQL, but Prometheus is also not a challenging experience.
    Community Prometheus is an open-source project with a huge community of users that can rapidly resolve your queries. Having a big network of support is an added benefit since there is a high probability that the challenges one is having might previously have been encountered by someone in the community. InfluxDB, despite its popularity, needs to improve on community support in comparison to Prometheus.
    Scaling When the load rises, the monitoring Prometheus servers require scaling as well.This is due to the fact that the Prometheus server is independent. Thus, the Prometheus server works great for the simpler load. Since the commercial section of Influx DB is distributed, there will be many interconnected nodes. As a result, as the server scales up, we don’t have to worry about scaling nodes. Thus, Influxdb nodes might be considered redundant while handling complicated loads.

    TIPS

    InfluxDB performs exceptionally well at storing monitoring metrics (e.g., performance data). Compared to Prometheus, InfluxDB utilizes more disc space and has a monolithic data storage strategy. It performs well for recording occurrences.

    Conclusion

    As a result, you can consider the factors discussed in this article while choosing between Prometheus and InfluxDB as monitoring systems for time series data, depending on your business case. When it regards monitoring services for time series data, both platforms are extremely well-liked by enterprises. Some claim that PromQL is new and InfluxQL is similar to SQL and will thus be better, but the reality is different. PromQL is considerably more user-friendly for querying, so go for it. Prometheus has a lot more functionality and integrations, so you can choose it. InfluxDB is a better option if you're looking for something specifically for IoT, sensors, and other analytics.

    Relevant Topics:

    https://prometheus.io/ https://github.com/influxdata/influxdb https://v2.docs.influxdata.com/v2.0/ https://www.influxdata.com/blog/multiple-data-center-replication-influxdb/ https://logz.io/blog/prometheus-monitoring/

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    Case Studies

  • Mar 24, 2022
  • 8 Proven Ways to Reduce Your AWS EC2 Costs

    AWS is everywhere and many organizations are leveraging it’s power. But with the power of AWS comes the EC2 cost which is undoubtedly a big component of your cloud payment.
    It is essential to understand how to reduce AWS EC2 costs. AWS is everywhere and many organizations are leveraging its power. But with the power of AWS comes the EC2 cost which is undoubtedly a big component of your cloud payment. It’s a fact that most new startups fail to launch their business because of poor financial management. Understanding the AWS billing cycle and how it works is critical to keeping your AWS EC2 costs lowering. In this blog, you will learn about EC2 and effective methods to reduce your AWS EC2 costs without compromising your operations.   pricing-model
     

    Here are 8 Proven Ways to minimize your EC2 costs:

     

    Decide on EC2, ECS, Fargate Or Serverless Archictecture

      Instances that can fulfill your applications' and workloads' needs. You can do this by evaluating your computing demands. Memory, network, SSD storage, CPU architecture, and CPU count are all factors to consider. Once you have this information, you should seek an instance that offers the greatest performance for the amount you are willing to pay. It is not hard to discover low-cost cloud instances based on your requirements. We can use serverless architecture if the REST service or deployment does not rely on the existence of running machines and can be an event driven architecture. We can also set up ECS or Fargate machines with the right size, memory, and storage to scale up or down depending on your needs.
     

    TIPS

    You can save licensing cost with predefined or bulk license management.

     

    Leverage reserved EC2 instances

      Reserved Instances are a way to buy EC2 machines for a long term and reduce overall pricing through an agreed discount. Since a reserved instance is a pre-paid model, Amazon offers a 75 percent drop on the hourly pricing per instance. As a result, the entry-level instance will cost less. The availability of the reserved instance model is likewise higher than that of the on-demand instance. Why? In a nutshell, it's because it's prepaid. As a result, it is pre-booked, allowing Amazon to schedule the time required. Finally, users can sign up for a one-year or three-year commitment to use the EC2 reserved instance.   

    Leverage GPU Instances

      CPUs and GPUs have a significant impact on both cost and performance. You would choose which type is most suitable for your requirements. For example, if you wish to do machine learning activities on a cloud, you should use modern GPU instances such as the G3 or P3 series. Even though GPUs have a higher cost per hour, GPU instances can dramatically accelerate training time and result in cost savings (as compared to CPUs).  

    Spot Instances for stateless and non-production workloads

      Spot instances can save a lot of money for stateless and non-production workloads. You can save up to 90% off the on-demand pricing and lower your AWS EC2 expenses. The fact that Spot Instances could be taken before the instance is used and that they are susceptible to change should be noted.  

    Leverage Tags & Setup Availability times

      Understanding the NFR Non-functional requirements of a business can help determine the hours our EC2 machines need to run. On this basis, we can schedule the machine's startup and shutdown times and prevent unnecessary running costs and downtime for the devices. You can save money on EC2 by prioritizing some EC2 instances over others. For Example, You could restrict your search to only production, non-production, and other Instances. The AWS dashboard and the AWS API are both used to find and optimize instances using tags. Security and compliance are other possible uses for Tags.  

    Auto-Scaling

      The Amazon Web Services (AWS) Auto Scaling mechanism ensures that the appropriate number of Amazon EC2 instances are running to meet the demand of a specific application. Auto Scaling changes compute performance dynamically based on a predetermined schedule or the current load measurements, increasing or decreasing the number of instances as necessary. To modify capacity to actual demands, you can use different types of scaling options that Amazon offers. By dynamically reducing the capacity, you can easily save money and prevent waste. Configure Auto Scaling with precision to maximize cost savings. You can over-provision capacity if you use Auto Scaling for applications that are too big or include too many instances.  

    EC2 Instances of appropriate size

      Right-sizing is adopting an EC2 instance type that is a suitable match for your application or workloads to prevent underutilized resources. To identify the kind of instance necessary, evaluate the number of CPU and memory resources utilized by a certain application. After that, you can choose the instance type and number of instances that are most suited to your needs. By choosing your size wisely, you can gain also the most of your reserved instance purchases. Once you've determined the best configuration for your instance, you can save even more money by signing up for a specific term and obtaining reserved instances. However, it may be difficult to determine the right size when dealing with unpredictable workloads, and reserved instances are often wasted.  

    Orphaned Snapshots should be detected and eliminated

      As per standard rules, any associated EBS volumes are automatically erased when an EC2 instance is terminated. Any snapshots that are still on S3 and are billing. These expenses might be more than you anticipate. Most backups are incremental, while the first snapshot captures the whole drive. Additionally, over time, incremental snapshots may need more data storage than the first one. Although S3 is less costly than EBS volumes, you'll need a strategy for deleting EBS volume snapshots when an EBS volume is destroyed. Over time, this might result in considerable storage cost savings.   

    TIPS

    Always plan to set up budgets and consume resources within the budget. Custom alerts can also help us realize if we used 50%, 75% or 90% of our limit

     
      Learn more about the AWS cost explorer

    Conclusion

      The Amazon EC2 service is a great way to get some computing power without having to manage a server. However, you can't leave an instance running all day and night without paying for it. For one thing, it's not free! Common problems with EC2 costs include tracking reserved instances with unused hours, underutilized and idle EC2 instances, and migration of EC2 instances from a previous generation. Oversizing and inefficiency of the system bring their own set of challenges. Finally, there are numerous ways to lower your EC2 costs. By following the tips in this article, you can resolve the above challenges, save money and improve your efficiency.The cost of an EC2 instance is based on the instance configuration associated with data processing needs. Successfully minimizing EC2 expenses is reliant on the balance between the cloud computing needs to process corporate data and the quantity of the data that is being processed. To reduce your EC2 costs, get in touch with us. Making the best choice for your tools will be easier for you with our expertise.    

    Related Blog

      https://segment.com/blog/spotting-a-million-dollars-in-your-aws-account/ https://cloudcheckr.com/cloud-cost-management/aws-cost-issues-quick-fix/ https://www.apptio.com/blog/decoding-your-hidden-aws-ec2-costs/
       

    Success Stories

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    Case Studies

  • Aug 12, 2021
  • Remote Monitoring by Doctors

    Communication between Doctor and patient is very important for recovery of a patient. With the help of remote monitoring devices, patients need not travel back and forth between their house and hospital

    Introduction

    Communication between Doctor and patient is very important for the recovery of a patient. Remote monitoring devices avoids the back and forth travel of patients between hospital and their house. Their health condition can be regularly monitored by using remote devices and hospitalization of the patient can be prevented. Remote patient monitoring is shortly abbreviated as RPM and is a method of capturing patient’s health data. It captures all vital information of a patient such as BP, Sugar level, heart rate, etc. Remote monitoring has proved to be advantageous by reducing patient readmission and allow treatment sooner

    Overview of market share

    The global remote patient monitoring market is projected to reach USD 117.1 billion by 2025 from USD 23.2 billion in 2020, at a CAGR of 38.2% between 2020 and 2025. The factors that boost the demand for remote patient monitoring are a reduction in the number of health care staff and an increase in awareness of telemedicine. There is a growth in the market due to the efforts taken for the discovery of Innovative devices Patient remote monitoring is becoming a sturdy market

    How remote monitoring Works

    Even while at home patients can carry out their normal activities and monitor their health. The remote monitoring devices helps them to monitor their health and collect data These monitoring devices are integrated with patient monitoring apps. The apps transmits the data electronically to their Doctor Doctors then examine this patient data from a distance. In case of a patient who needs immediate treatment or attention, alerts are sent to the patient’s mobile and they receive it in the form of notifications. This remote monitoring technology helps to detect any issue at an earlier stage

    What are the best features to have in remote patient monitoring apps

    Some of the best to have features of remote patient monitoring apps

    Notifications

    Timely notification is an important feature of remote patient monitoring. Timely notification may prevent them from a serious illness. Also, notifications should be in sync for both patient and doctor

    Integration with devices

    Integrating with monitoring devices is an important feature. When integrated, the app will be able to collect data from these devices from time to time which might help to monitor progress over a period of time

    HIPAA Compliance

    Patient data is highly sensitive and it needs to be protected. It should be ensured that it meets HIPAA compliance Remote monitoring apps should have physical, network, and process security measures to ensure HIPAA compliance

    Support for BLE

    Remote monitoring apps need to support Bluetooth connectivity which is very essential for the transfer of data between monitoring devices and apps

    Integration with doctor’s system

    Integration with a Doctor’s system through secure API built on FHIR industry standard to ensure proper exchange of data between multiple systems is an important feature that needs to be handled

    doctor-system

    Tech Stack

    Blockchain

    The patient and Doctor are connected through voice and video calls. Encryption of patient data prior to transmission is very important. Blockchain technology is used for encrypting the sensitive patient data

    Cloud Storage

    Cloud services are used for storage of data as it improves privacy and security control of the app. Also, data retrieval is very quick from the cloud servers. So storage and transfer become efficient

    Artificial Intelligence

    Artificial Intelligence-based Chatbots are used for patients to get their queries answered as doctors are not available round the clock

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="offshore teams blog"]

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    Success Stories

  • Aug 12, 2021
  • How to work with offshore teams and manage remote offshore teams successfully?

    Working with offshore teams is a common practice in the IT industry. Web and mobile app development are among the most common tasks that are outsourced to offshore development teams

    Introduction

    Working with offshore teams is a common practice in the IT industry. Web and mobile app development are among the most common tasks that are outsourced to offshore development teams. Outsourcing to an offshore team allows you to hire expert professionals for a fraction of the price that you would have to pay if you would hire full-time in-house employees. Along with salary of the employee, other expenses like health insurance, insurance contribution, and bonuses can also be saved. You are not required to spend money on office space, IT infrastructure, and utilities such as electricity. Moreover, a business can easily decrease or increase the size of the team according to its requirements. Thus, businesses enjoy both flexibility and scalability by outsourcing their projects to offshore teams

    Overview of Offshore Teams

    An offshore team usually implies a certain number of specialists who work for you remotely. They can be located at any place and the communication is done through phone calls, messengers like slack or video calls through zoom, meet. Hiring remote developers can be of great help financially. It helps to save cost. Such practice was usually associated with small companies that had a lack of financing. However, today the situation is different and even huge companies turn offshore as it has a number of undeniable benefits

    offshore-team

     

    Here are 5 reasons why businesses hire offshore teams:

    1. Controlled Costs
    2. Drastically Improved Efficiency
    3. Focus on Overlooked Areas
    4. Access to a Global Talent
    5. Flexibility

    Handling the Common Challenges in Offshore Team Management

    Here are the most common challenges that clients come across while handing their offshore teams

    Communication Challenges

    There are two things that can make or break the whole project: time-zone difference and language skills of an offshore vendor. The time zone difference creates difficulty in communicating with an outsourced team. So the calls are postponed which in turn lowers productivity and causes delay in project delivery How to overcome the challenge - There might be few hours overlap in time zone. This overlap can be used effectively for various activities like feedback, checking project progress and for communicating with the remote team When all the expectations are set up front, it becomes much easier to achieve them, as well as monitor the development process. The outsourced team has to clearly understand what is expected from them and what the requirements for the future product are

    Lack of Control

    For some managers, it is very crucial to be in charge of each step on the development timeline– So working with an independent vendor is not a comfortable experience. Not being able to ensure the project progresses according to plan is one of the challenges that come with outsourcing How to overcome the challenge - To know how to manage a remote development team, a business manager can send a trusted employee to work at the dedicated office and oversee project development. Asking for a personal account manager who keeps tabs on the product’s progress is another way to get more control over the development

    Ineffective Project Management

    what’s happening at each stage of development, are the red signs that something is wrong. If you came across these offshore team challenges, it can either mean that the vendor is incompetent or aren't following the methods that you use in your work How to overcome the challenges – The outsourced team should understand clearly and follow the development methodology a project needs. Make sure that the outsourcing company does have access to the technologies or tools needed for the completion of the project

    How to Get Maximum Productivity from an Offshore Team

    Daily Meetups

    Communication is the key to development success. That goes for any kind of group effort, and doubly so when the people are geographically disparate. When your team is far away from you, it should be ensured that you are updated about the progress of work. For updates about the progress of work, project management models like Scrum, Kanban or Agile can be used. To make the most out of it, use one of the project management models (Scrum, Kanban, Agile, etc.) while working with the outsourcing agency. By ensuring that your people all talk to each other daily, you’re keeping information flowing. Everyone knows what’s being worked on, and what their part is

    Sprint Planning

    Despite the daily stand-up, everyone is going to be largely working on their own tasks, and there’s a real danger of people’s work getting in each other’s way. The planning meeting is when those tasks are explained and handed out. If you’re following Agile (which you should), then you’ll have a scrum master and a product owner both participating to ensure that everyone comes out of the meeting knowing exactly what to do and why. As for the length of the sprint, that’s up to you

    Discuss Your Project Goals

    Just assigning a project to an offshore team without letting them know the goal behind it can land you in trouble. The developed product may not be as you expected it to be. Offshore developers require full product vision before starting working on the project. They should be given complete details like why the product is required, what functions will be carried out by the product, what all specifications is required in the product, and when it is expected to be

    Make Use of Agile Methodology

    As software development is a process that requires a high level of interaction and iteration, the adoption of agile methodology for offshore teams helps in the development and delivery of a high-quality software product on time In some cases a sprint may be just one­ weeks’ time or it may be one or two months. Based on priority, features can be allocated to different sprints. At the beginning of each sprint, you and your offshore team can have a discussion regarding the features to be developed and create a detailed plan. Whenever required face to face communication can be initiated with your remote team.

    Communicate Frequently and Use Simple Language

    When working with your remote team, you can communicate very easily and frequently by initiating face-to-face talk whenever you require. With offshore teams, you should communicate even more frequently so that all the things are clear and there is no confusion despite the large distance between your in-house and offshore teams

    Communicating with Offshore Teams

    Here are some highly recommendable communication tools that help you when you are working with remote teams

    JIRA

    This includes everything from planning till analytics. It allows to set clear and actionable goals. Their progress can be easily tracked. Jira is customizable and it is capable of working equally good for all of the Agile methodologies

    Confluence

    Another product from the makers of Jira,
    Confluence is one of the best collaborative document systems and it is more like Google Docs. On the surface, it’s similar to Google Docs. Multiple people can share a document, view and edit it simultaneously. Changes can be both suggested as well as accepted. The software supports templates for different documents. Above all, Confluence can interface perfectly with Jira. The software supports user-definable templates for different documents, labeling, and cross-document notes. On top of all that, Confluence interfaces perfectly with Jira. Taken together, the tools make a very powerful collaboration system

    Bitbucket

    Bitbucket Cloud is a Git-based code hosting and collaboration tool, built for teams. Bitbucket's best-in-class Jira and Trello integrations are designed to bring the entire software team together to execute a project. It helps you to track, preview, and confidently promote your deployments

    GitHub

    GitHub hosts your source code projects in a variety of different programming languages and keeps track of the various changes made to every iteration. It lets you and others work together on projects from anywhere

    TeamViewer

    TeamViewer, is an all-in-one solution for remote support, remote access, and online meetings which allows you to assist customers remotely, work with colleagues from a distance and also stay connected with your own devices or assist friends and family members. It even supports mobile devices, a must for mobile app development

    Slack or Skype

    Both slack and Skype have a chat room and supports the private messaging feature, with VoIP and video calls. They feature robust chat room and private messaging functionality, along with VoIP and even video calls. Use these tools correctly, and you’ll eliminate all of the communication problems endemic to offshoring

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Mobile Application Development blog"]

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    Success Stories

  • Jul 30, 2021
  • What Are The Best Practices For Microservice Orchestration and Multicluster management

    Container bundles up the OS and microservice runtime environment such as source code, dependencies, system libraries, etc.

    Introduction

    Container bundles up the OS and microservice runtime environment such as source code, dependencies, system libraries, etc. There are many tools available in the market for configuring the containers. Some of them are Kubernetes (including AKS, EKS and GKE) and ECS. Multicluster management is for managing many k8s clusters in an environment. For this, we have tools like rancher and kubesphere. In this article, Kubernetes deployment through Istio and Rancher multicluster management is covered. Istio is a service mesh which provides a language independent and transparent way for easy automation of application network functions. Istio’s features help to monitor, connect and secure services. Rancher is a complex stack for teams that adopt containers. It combines everything the organization needs to adopt and run in production. As it was built on Kubernetes it allows DevOps teams to test, deploy and manage the application in a lightweight framework

    Overview of Kubernetes Deployment through Istio

    Kubernetes also known as K8s is system which helps to automat e the process of deployment and containerized applications management Istio extends Kubernetes with Envoy service proxy for establishing a programmable and application aware network. With Kubernetes and olden workloads, Istio makes universal traffic management, security and telemetry to deployment

    How system Works

    Sample workflow for Istio

    best-istio  

    Architecture Diagram for Rancher

    introduction

    What are the best features of Istio and Rancher

    • Service Mesh
    • It has ways Ways to control data sharing between different parts of an application

    • Secure communication between service to service

    • Load Balancing is automatic for http

    • Control in traffic behaviour

    • TLS encryption, authorization and authentication tools are available to protect data and services

    • Observability - Monitoring, Logging, Tracing

    Features of Rancher

    • The users can deploy an entire multi-container clustered application from the application catalog with a single click of a button

    • Managing of deployed applications by automatically upgrading to newer versions

    • It contains the distribution of container orchestration like Docker swarm, Mesos and Kubernetes

    • Infrastructure services include networking, storage, load balancer, and security services

    • Users interact with ranchers using a command-line tool called rancher-compose. Users interact with ranchers using a command-line tool called rancher-compose. User can deploy multiple services and containers on Rancher infrastructure depending on Docker compose templates. The rancher-compose tool also supports the docker-compose.yml file format

    • Interactive UI for managing tasks and maintaining clusters

    devops

    Agile Delivery Process

    10decoders has a very strong focus on process. We help our clients to capture the requirements in clear process flows and screen design. Understand how our process driven culture helps customer to grow their business

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    Success Stories

  • Jul 28, 2021
  • How To Effectively Use Istio For Enterprise Governance and Monitoring

    The client offers deep and contextual application-layer visibility to remove the blind spots within distributed and cloud-native application environments, in a completely frictionless

    Introduction

    The client offers deep and contextual application-layer visibility to remove the blind spots within distributed and cloud-native application environments, in a completely frictionless manner while being agnostic to the platform, cloud, environment, and workload type. The solution allows many people like cloud application practitioners, security leaders, and application owners to have a visibility which would help them to address compliance, and security controls for microservices and other distributed applications

    Overview of Challenges faced by Client

    1. The client has run their pre-production application in cloud infrastructure and it costs high
    2. The client engineering team spent most of their time deploying their changes on cloud infrastructure for evaluation
    3. The client team faced more challenges in deploying their application in cloud environments and that cost 45% of their monthly budget allocation.
    4. Client teams spend more time on deployment and testing in cloud infrastructure will extend the delivery time of the application
    infrastructure

    How Current system Works

    Enterprises today deploy perimeter-centric solutions, such as network firewalls, web application firewalls, and/or API Gateways. Others like container firewalls, network-layer micro-segmentation, or manual application testing are also tried. Some other solutions concentrate on one type of workload (e.g. containers) or are focused on data-in-use or data-at-rest and do little to secure against run-time attacks embedded deep within the application-layer components

    How we proposed system architecture

    The client ideally needs an Infrastructure with different topologies of system types templated as a solution.Generic engine for generation and regeneration of infrastructures need to be utilized. Following are some of the key considerations
    1. The solution proposed is to create an environment like cloud infrastructure in local machines
    2. Writing tests framework to make the client engineering team use for their Unit Testing
    3. We are using MetalLB for implementing network Load Balancer in K8 local infrastructure
    4. Implementation of microservices to simplify the deployment and improve the performance of the application. By using testing frameworks to deliver the flawless application in a production environment
    5. Containerize the microservice components to achieve the CI/CD process with the K8 cluster to reduce the time spent for on deployment
    6. Provide scripts to automate the process of testing and deliver the application with zero bugs
    enterprise

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    Case Studies

  • Jul 01, 2021
  • What Are The Phases of Software Development Lifecycle

    Software Development Lifecycle, in short, termed as SDLC is a process that defines various stages involved in software development for the delivery of a product.
    Software Development Lifecycle, in short, termed as SDLC is a process that defines various stages involved in software development for the delivery of a product. SDLC is very important as it gives a framework for a set of activities and ensures the quality of the product delivered. There are seven phases involved in Software Development Lifecycle. They are Planning, Requirement Analysis, Design, Implementation, Testing, Deployment, and Maintenance. Here we shall see each of these phase-in detail

    Phases of SDLC

    1. Planning

    As the quote says “By failing to prepare, you are preparing to fail”, Planning is very important for any task. Similarly, Planning is the initial phase of the Software Development Life cycle. Planning starts with listing the problems of an Existing system. Problems in the existing system are listed to come up with the objectives of the new system to be developed. Along with the scope of the new system, financial planning and Resources planning are also done in this phase. Then last comes the planning for the project schedule which is very essential to complete the project on time. Only when the planning phase is completed, it can be moved on to the other phases

    2. Requirement Gathering and Analysis

    Defining Requirements and gathering all required information like the purpose of the new system, end-users for the new system, their needs are all carried out during this phase. Risks involved in the development of the new system are also identified. The analysis is done to ensure that the end-users needs can be met by the new system. All clarifications regarding the requirements are received from the concerned team before starting on the Design part. The output of this phase will be in the form of a document more often called a Software Requirement Specification or SRS document. This document along with new system requirements also contains Software, Hardware, and Network requirements needed for the development of the new system. This will be used as the input for the design phase

    3. Design

    Design is a kind of modeling everything visually. Developers will outline the details for the new system using the Software Requirement Specification document in the form of a Design Document. The Design document will include details like User Interface which will define how the user is going to interact with the new system, Database which is going to be used for storing data, platforms on which the new system will run, Security measures to be taken to protect the system, etc. So both front-end and back-end are defined here. If required, prototypes are also defined. Prototypes give a basic idea of the actual look and feel of the new system. When the design is completed it is time to move on to the next phase, which is the development phase

    4. Development

    This phase is the coding phase. This is the most important phase of SDLC as it is where the actual software is developed. It is the longest phase of SDLC. Here the design document is converted into the software. The developers need to make sure the software meets the Software requirement specifications. Developers will have to follow coding standards and use tools like compilers and debuggers to eliminate coding defects. Identifying coding bugs and fixing them is critical here. Programming languages are chosen based on the requirements and specifications of the project. A detailed design will help in hassle-free code development

    sdlc

    5. Testing

    Testing of an application is critical before it is actually made available to the Users. This is part of a Quality Assurance process. It is started as soon as coding is completed and all coding errors are fixed. It is done by Quality Assurance Engineers. Manual or Automated Testing are performed depending on the Project. In the case of Automated Testing, many tools are available in the market. Again depending on the nature of the project automated testing tools are selected. The developed software is tested thoroughly to make sure that the requirements are met. The defects are identified and logged in Defect Tracking tools. Then they are tracked to closure. Different types of defect tracking tools are used by different companies. The initial testing done is called Unit testing. Then the individual units are integrated and integration testing is performed. The software is repeatedly tested to ensure that there are no more defects

    6. Deployment

    When the defects are all closed and no more defects are identified, the software is ready for installation. The installation phase is often called the Deployment phase. In some cases, it could be the deployment of code on a web server, and in some cases, it could be integrating with other systems. The users can start using the software after deployment. In some cases, since the software is deployed to the production environment, again another round of testing is carried out here to ensure that there are no issues in the new environment. The users could also be trained just before this phase to make sure that they are aware of the usage and features of the new system

    7. Maintenance

    Maintenance is an important phase as there might be issues identified when the end-users start using the product. In some cases, the end-users keep changing and there might be different types of issues identified. These issues need to be fixed from time to time. The maintenance time might vary depending on the size of the project. Sometimes even new features are added as per user feedback and released agile

    SDLC Models

    There are various SDLC models and the most common ones are Waterfall and Agile. We shall see about these in detail

    Waterfall Model

    This was the most commonly used and most accepted model. The output of one phase of the Software Development Lifecycle is used as the input for the next phase. So the successive phases can be started only after the completion of the previous phase. At the end of each phase review and sign-off is done before moving on to the next phase. The waterfall model is very useful when the requirements are fixed and do not keep changing. The main advantage of the waterfall model is it is easy to follow and the milestones are clearly defined

    Agile Model

    Agile is a simple and highly effective process. In the Agile model, the task is divided into small iterations of smaller durations. For each iteration, all phases of SDLC like planning, analysis, design, coding, implementation, testing, and deployment are carried out. Here there will be continuous delivery. Even when there are frequent changes in the requirement that can be handled here easily. During each sprint the new requirements come from Backlog and roll through all phases of SDLC. Since changes are inevitable the agile model helps the project to adapt to it instead of ignoring it SDLC is a systematic process and it ensures the quality of the product delivered. All phases of SDLC are very important. So adhering to phases of SDLC is very important for the success of the project

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    Success Stories

  • Jun 28, 2021
  • How to build a Ridesharing App?

    The main idea of taxi booking apps is to book a taxi in under 30 seconds easily. And the most convenient way is to connect drivers and riders via a mobile app like Uber, Ola, etc.

    You can call your trip in the following criteria

    • The passenger has pre-planned a trip and his travel
    • The passenger has made no prior arrangement and this is unplanned
    • The passenger is out on the road and looking for a taxi service
    Sometimes passengers may look for companions to share costs but have a rest during long trips The main idea of taxi booking apps is to easily book a taxi in under 30 seconds. Like Uber and Ola it would be easy and convenient for a rider to connect with a driver through a mobile app.

    taxi

    Here’s how Taxi Booking Apps work

    1. Request - Passengers specify where they’re going, where they'd like to pick up and drop off passengers, and when
    2. Booking - Passengers look through the type of trips, cars, and book a ride
    3. Payment - Passengers pay in the app or cash when they get in the car
    4. Rating - Riders rate the trip and leave their reviews
    If riders choose to pay via the app, the money goes to the drivers bank account from the time of payment within two days

    get-a-taxi

    Must-Have Features

    Registration & Profile

    For registration the user need to enter his phone number, email and then generate a password. Some apps also offer signing up through social media like facebook, Google or twitter and helps to save the time of user.

    Book a Ride

    Initially passengers enter their destination along with pickup point and then select a driver to take up the ride. Before starting a ride the rider will look for the cost. Drivers can view the booking requests and accept or reject them. Otherwise they can accept all requests that come to them automatically. When there is no ride available for a rider, he will get an alert saying that he will be notified as soon as a ride is available.

    My Rides (Passenger/Driver)

    Passengers see the number of rides they’ve completed and their details—date, destination, car, payment details—in the ‘archived’ tab

    GPS Location

    In ride-sharing app development, GPS is used to detect someone's location. That's how drivers can set exact pickup and drop off points, while riders can see their whole route

    Fare Calculation

    The app calculates the cost for each passenger based on their number and travel distance. This helps passengers to select the preferred mode of payment.
    • Online - The app transfers money to PayPal or a bank account
    • In cash - Riders pay in the car before or after the ride

    Admin Panel

    Admin panel helps the administrators to manage users. They can search for an user, block them or check up an ID card, do payments, perform reviews, generate reports or view statistics

    taxi1

    How to Monetize a Taxi Booking App?

    Before you start creating a ridesharing app the first step would be to choose a monetization model. The most common are
    • Paid advertising (users see third-party ads in the app)
    • Reservation/cancellation fees for riders (passengers pay a small booking fee to confirm their intentions)
    • Transaction fees for drivers
    • Collecting a small service fee for every ride from passengers
     

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    Success Stories

  • Jun 10, 2021
  • How to create a Fitness App?

    Health and fitness is becoming everyone’s top priorities. In this digital era there are many apps to keep track of our fitness. Most of them are freely available to the Users

    Introduction

    Health and fitness are becoming everyone’s top priorities. In this modern World, many apps are readily available to track fitness and are free of cost. People are looking for different approaches in fitness app. This makes it essential to keep creating multiple fitness app. And so, many companies have started developing fitness app. Fitness app is used for multiple purpose. It may be to notify about health or to improve diet. Here we will see the various types of Fitness App and how to build them

    Overview of Market Share

    In January 2019 one of the Market Research published a study and presented a forecast. The forecast mentioned that the fitness app market will grow to $14.7 billion by 2026. It is expected to grow up to 23% CAGR during the above mentioned period. The statistics mentions that revenue in Fitness segment has reached $17,963 million in 2020. It also continues to grow rapidly. So the revenue might grow to a rate of 5% CAGR during the period 2019-2023. So fitness application market will continue to grow and is expected to expand with different developments in health and fitness features market-share

    How do various Fitness Apps work?

    The fitness apps help to keep track of our health. It gives health advice also. There are many type of Fitness apps. The three widely used apps are given below

    Diet and Nutrition Apps

    Diet and nutrition apps can do the following
    • The target calories for intake can be set depending upon a person’s age, weight, and sex.
    • Weight loss goals can be set
    • Users can log the food they eat and the app helps to track the calories included in the food they have logged in.
    • Users can adjust their intake accordingly with the help of the calories calculated.
    • It can also track the amount of water intake

    Work-out Apps

    • This is a personal trainer who trains you from your mobile
    • Users can set a time limit and perform workouts/yoga using a timer
    • Users get the option to choose the type of workout they would like to perform. For example, whole-body workout, upper body workout, etc
    • The app offers a set of exercises that the user can access and perform by playing the exercise simultaneously in the app
    • The user has the option to skip certain exercises in the list of exercises

    Activity Tracking apps

    • The app tracks the distance traveled, number of steps climbed, and calories burnt during exercise
    • The information collected can be depicted in a progress chart to motivate the users
    • Even the app can monitor the heartbeat

    What are the best features to have?

    Each fitness app has a different function and offers unique features for its users. Some of the important features required for a fitness app to be user-friendly are given below Sign Up and Log In –  Signup sign in features helps for users privacy as he can login through his own credentials or through his social media account User Activity Tracking – This feature is much beneficial as the user can keep track of his activity for a specified period. This tracking can then be depicted in chart for motivating the user to perform better Geolocation – The user can use the map to know the distance he walked or jogged. This will be easy to track and gives a sort of motivation to the user Notifications and Reminders – Notification and Reminder is an important feature for a fitness app. For example, when his calorie intake is close to the limit for the day, then he will get appropriate notification on his mobile. The user can adjust his intake accordingly which will be of great help to achieve his fitness goal Scanning Barcode – The scanning barcode of an edible item helps the user to scan and get its nutritional information in the case of the diet and nutrition app

    How to Develop a Fitness App?

    When the type of fitness app and the type of features needed is decided, the custom software development process starts The Monetization model is the first step in developing a fitness app. They decide whether the app will be free or paid or app with in-app purchases Technology Stack – The technology that is to be used for developing the app need to be identified. Team Hiring – Depending on the technologies identified, hire a development team to match the technology The Inception Phase – Here we will define the scope of work to be performed, finalize the budget, and plan for the required resources Technical Documentation and Design. Based on the requirements the design document is prepared with technical details. The design document also has the UI/UX details of the app Prototype – Prototype is the model of the fitness app to be developed. The developer can use this prototype and easily develop the application Application Development. Fitness apps compatible with multiple OS are developed by the developers in this phase Quality Assurance – Testing of the product is done and bugs are identified. Testing is done many times to make sure that the developed application meets the requirements and does not have any bug

    Conclusion

    While developing a fitness app, extra care must be taken in making it user-friendly, flexible, and in selecting the features to be developed in the app. User-friendliness, flexibility, and features of the app will attract more users to use the app and make it profitable. If you are planning for fitness app development and would like to outsource it, please feel free to contact us

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Create a Fitness App blog"]

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    Case Studies

  • Jun 04, 2021
  • Cloud Migration : Lift & Shift Strategy

    Lift-and-shift is the process of migrating a workload from on premise to Cloud with little or no modification

    Introduction

    Lift-and-shift is the process of migrating a workload from on-premise to Cloud with little or no modification. A lift-and-shift is a common route for enterprises to move to the cloud and can be a transitionary state to a more cloud-native approach

    There are also some workloads that simply can’t be refactored because they’re third-party software or it’s not a business priority to do a total rewrite. Simply shifting to the cloud is the end of the line for these workloads

    Applications are expertly “lifted” from the present environment and “shifted” just as it is to new hosting premises, which means in the cloud. There are often no severe alterations to make in the data flow, application architecture, or authentication mechanisms

    It allows your business to modernize its IT infrastructure for improved performance and resiliency at a fraction of the cost of other methods

    cloud

    Overview of Market Share

    In recent days there is great growth in Cloud computing market. Companies are trying out various cloud models with right balance of flexibility and functionality The cloud migrations hosts the application and data in an effective environment based on various factors. This is the key role of cloud migration Many companies migrate their on-site data and application from their data center to cloud infrastructure with the benefits of redundancy, elasticity, self-service provisioning and flexible pay per use model. These factors are further expected to drive tremendous growth in the global cloud migration services market during the forecast period 2020-2027 According to the report, the global cloud migration services market generated $88.46 billion in 2019 and is estimated to reach $515.83 billion by 2027, witnessing a CAGR of 24.8% from 2020 to 2027 The growth of the market is attributed to an increase in cloud computation among small and medium enterprises around the globe

    What are the best features to have?

    • Workloads that demand specialized hardware, say, for example, graphical cards or HPC, can be directly moved to specialized VMs in the cloud, which will provide similar capabilities
    • A lift and shift allows you to migrate your on-premises identity services components such as Active Directory to the cloud along with the application
    • Security and compliance management in a lift and shift cloud migration is relatively simple as you can translate the requirements to controls that should be implemented against compute, storage, and network resources
    • The lift and shift approach uses the same architecture constructs even after the migration to the cloud takes place. That means there are no significant changes required in terms of the business processes associated with the application as well as monitoring and management interfaces
    • It is the fastest way to shift work systems and applications on the public cloud because there isn’t a need for code tweaks or optimization right away
    • Considered the most cost-effective model, the lift and shift help save migration costs as there isn’t any need for configuration or code tweaks. In the long run, these savings could give way to extra spending if workload costs are not optimized
    • With minimal planning required, the lift and shift model needs the least amount of resources and strategy
    • Posing the least risk, the lift and shift model is a safe option as compared to refactoring applications especially in the scenario where you don’t have code updating resources
    When is the Lift-and-Shift Cloud-Migration Model the best fit? The lift and shift approach allows on-site applications to be moved to the cloud without any significant redesigns or overhauls. You should consider using the lift and shift approach if the following apply to your business You’re on a deadline If you’re in a time crunch, the lift and shift approach may help expedite the transition to the cloud quicker than other methods You want lower costs A lift and shift migration can provide cost savings compared to more expensive methods such as re-platforming and refactoring. This approach is of minimal risk and is beneficial for workplace operations You want to reduce risk Lift and shift approach is less risky and simpler process when compared to other methods like refactoring or re-platforming When you are choosing options to migrate, you need to look at the larger picture Although the lift and shift technique can work well in many instances, you should consider all options and choose the migration type that will keep you functioning at peak performance By choosing the right IT support firm to assist with the transition, you can mitigate cloud migration challenges to ensure optimal performance and a seamless transition With the lift-and-shift method, on-premise applications can move to the cloud without remodeling. Since they cannot take full advantage of native-cloud features every time, this may not be the most cost-effective migration path Bounce back can be avoided by developing a strategy for cost-allocation and defining roles to monitor how much is spent for cloud
      cards

    Cloud Migration Steps: Ensuring a Smooth Transition

    • First, choose which platform that you wish to migrate to
    • Examine all the connections in and out of the application and its data
    • If you are lifting and shifting more than one application, then you may need to consider automating multiple migrations
    • You should consider containerization to replicate the existing software configurations. This will also allow you to test configurations in the cloud before moving to production
    • Back up the databases from the existing system as well as supporting files. When the new database is ready, restore the backups
    • Once migrated, test the application
    • Check that all the current data compliance and regulatory requirements are running in the new cloud deployment. Run your normal validation tests against the newly migrated application
    • Don’t be tempted to introduce new features during the migration. This can lead to many hours of additional testing to make sure you have not created new bugs
    • Retire your old systems once testing is complete

    Technical Stack

    Google Cloud and Azure are new but still they take advantage of the experience and framework of tech giants namely Microsoft and Google
    AWS is a public cloud, flexible and ready to meet the needs of both big and small applications. Azure’s strong values are perfect integrations with Microsoft 365 ecosystem and focus on enterprise market To help you make an informed choice, we’ve prepared a table that compares the most significant features of AWS, Azure, and GCP  

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Cloud Migration blog"]

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  • Jun 04, 2021
  • How to build a video streaming app like netflix?

    Live streaming, also known as live broadcasting of the video over the internet is the important cause for the change in way of communication.

    Introduction

    The way people communicate all over the world has changed now!!! Live streaming is the live broadcasting of video content over internet. This has caused a major change in the way we communicate. Live streaming is becoming inevitable in the digital world where all sorts of organizations like education, business, entertainment, even family & friends meeting are flourishing because of this

    Overview of Market Share

    There is a great demand for live streaming. This has caused the live streaming market to grow. Covid - 19 is also one of the important growth factor. According to Global market insights the video chat market will grow by over 15% CAGR marketshare

    How live streaming works?

    A streaming server has to be already created and running. A broadcaster can initiate a stream by registering with a stream name. The users who want to be an audience can access the stream with the same stream name. When a stream is initiated, the below process happens to make the video available at the receiving end

    Live streaming undergoes the below steps

    • Compression
    • Encoding
    • Segmentation
    • Content Delivery Network (CDN) distribution
    • CDN caching
    • Decoding
    • Video playback
    live-streaming

    Features to have

    User Sign up & Sign in

    It can be a simple registration with an email or phone number and password. It’s a good way to offer sign-ups or ins via Facebook, Twitter, or Google as it saves the users’ time. A password reset feature via email or text message is needed

    User Profile

    It is better to decide on what kind of personal information will be in the user profiles like profile picture, full name, subscriptions, etc., This can be viewed by friends & subscribers

    Live Streaming

    Allows the user to record and broadcast a live stream to members who have subscribed to his/her channel or the public

    Chat

    Chat is an essential part of any communication application. Chat combined with live streaming will be very useful for the audience to give their feedback. Third-party tools like Firebase or Twilio helps to integrate chat into video chatting. Can include Emojis to make the chat interesting

    Record

    Feature to record the videos and can have a user gallery to store and organize the recorded videos on user profile

    How to develop a live streaming app using WebRTC?

    Backend development

    Create a live streaming application by means of WebRTC technology For a live stream to happen, the live video has to be sent to a server so that it can distribute the live stream to the audience or subscribers. So, a media server should be running somewhere that you can access There are many open source WebRTC media servers available. One such is Ant Media Server that can live stream & supports ultra-low latency (0.5 seconds) adaptive streaming and records live videos in several formats like HLS, MP Set up a media server You can download ant media server & use its trial version license Broadcast live stream Provide a stream name for the video stream and start recording. This will be passed to the ant media server View live stream The subscriber can use the same steam name to join the stream and view the live video

    UI/UX design

    Next comes the good & attractive user interface & user experience. It is better to have simple navigation as it will be convenient to understand. The user has to grasp the need for features & their performance

    Tech stack

    Content Delivery Network Streaming protocols Programming languages
    API server Database Backend           Hosting
    Push notifications Media processing platform Messaging queues

    Video Section

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    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Video Streaming App blog"]

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    Case Studies

  • Apr 18, 2022
  • 11 essentials devops metrics to boost productivity

    As businesses continue to grow and demand more from their technology departments, DevOps has emerged as a key contributor to increased productivity.
    As businesses continue to grow and demand more from their technology departments, DevOps has emerged as a key contributor to increased productivity. When some say it's about new tools, some claim it’s a change in culture, while others associate it with the engineer role, DevOps is the idea of functionality and operability together. By integrating DevOps practices into an organization's overall IT strategy, businesses can achieve efficiencies in both the development and deployment stages of software projects, leading to a more streamlined and efficient process. The very interesting thing about DevOps is that while frequently, its mission is to create a change in the culture of an organization, this change requires far more than coordination: it also requires pure collaboration and co-laboring. You’ll see this same principle of empathy at work within your company or in your own team which boosts productivity. It is a way of working that allows teams to manage software development and IT operations together. This helps to increase the efficiency of the organization, while also reducing the risk of defects.

    The technology landscape is always evolving, whether it is through new infrastructure, or a new CO tool coming out to help you manage your fleet better

    —Mike Kail

    How does DevOps work?

    DevOps is one of the most important concepts in modern software development. It's a collaboration method that encourages communication and cooperation between developers, operations staff, and testers. DevOps helps to speed up the process of creating and deploying software by automating many of the manual tasks while enhancing the problem-solving aspect all on its own. Cloud computing being centralized offers standard strategies for deployment, testing, and dynamic integration of the produced collaboration. It’s a survival skill of adapting according to the ever-changing and demanding market requirements.

    TIP

    DevOps helps you manage things effectively so that teams can spend more time on research, development, and betterment of the product.

    Metrics for DevOps are crucial for optimizing and establishing a higher-quality software development process.

    Here are 11 essential DevOps metrics to increase productivity in organizations:

    Frequency of deployment

    It is vital to promote and sustain an ambitious edge by providing updates, new functions, and enhancements to the product's quality and technological efficiency. Increased delivery intensity enables greater adaptability and compliance with changing client obligations. The objective should be to enable smaller deployments as frequently as possible. Software testing and deployment are significantly more comfortable with smaller deployments.

    TIP

    Organizations can use platforms such as Jenkins to automate the deployment sequence from staging to production. Continuous deployment ensures that the code is automatically sent to the production environment after passing all of the test cases in the QA environment.

    Time required for deployment

    This indicator indicates how long it will take to accomplish a deployment. While deployment time may look trivial at first glance, it is one of the DevOps indicators that indicates possible difficulties. If deployment takes hours, for example, there must be an issue. As a result, concentrating on smaller but more regular deployments is beneficial.

    Size of the deployment

    This measure is used to monitor the number of feature requests, and bug patches sent to production. The number of individual task items varies significantly depending on their size. Additionally, you can keep track of the number of milestones and other parameters for deployment

    Enhance Customer satisfaction

    A positive customer experience is important to the longevity of a product. Increased sales volumes are the outcome of happy customers and excellent customer service. As a result, customer tickets represent customer satisfaction, which then reflects the DevOps process quality. The fewer the numbers, the higher the quality of service.

    Minimize defect escape rate

    Are you aware of the number of software defects detected in production versus QA? To ship code rapidly, you must have confidence in your ability to spot software defects before they reach production. Your defect escape rate is a good DevOps statistic for monitoring the frequency with which those defects make their way into production.

    Understanding cost breakups

    While the cloud is an excellent approach to reducing infrastructure expenses, certain unplanned failures and incidents can be rather costly. As a result, you should prioritize collecting and decreasing unnecessary costs. DevOps plays a major role here. Understanding your spending sources might assist you in determining which behaviors are the most expensive.

    Reduce frequent deployment failures

    We hope this never occurs, but how frequently do your releases result in outages or other severe issues for your users? While you never want to undo a failed deployment, you should always plan for the possibility. If you are experiencing troubles with failed deployments, monitor this indicator over time.

    Time required for detection

    While minimizing or even eliminating failed changes is the optimal strategy, recognizing errors as they occur is crucial. The time required to discover the fault will affect the appropriateness of existing response actions. Protracted detection times may impose limits on the entire operation. Establishing effective application monitoring enables a more complete picture of "detection time."

    Error Levels

    It is vital to monitor the application's error rate. They serve as a measure not only of quality difficulties but also of continuing efficiency and uptime issues. For excellent software to exist, the best methods for handling exceptions are necessary.

    TIP

    Track down and record new exceptions thrown in your code that occur as a result of a deployment.

     

    Application Utilization & Traffic

    You may wish to verify that the quantity of transactions or users logging into your system seems to be normal post-deployment. If there is a sudden lack of traffic or a big increase in traffic, something may be amiss. Numerous monitoring technologies are available to provide this data.

    Performance of the application

    Before launching, check for performance concerns, unknown defects, and other issues. Additionally, you should see changes in the overall output of the program both during and after deployment. To detect changes in the usage of particular queries, web server operations, and other requirements following a release utilize monitoring tools that accurately reflect the changes.

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    Case Studies

  • Apr 04, 2022
  • Prometheus vs Influxdb : Monitoring Tool Comparison

    When it comes to data storage, there are few alternatives that can compete with the venerable Prometheus, such as InfluxDB. But what if you need more than just collected data? What if you need real-time insights into your systems?

    When it comes to data storage, there are few alternatives that can compete with the venerable Prometheus, such as InfluxDB. But what if you need more than just collected data? What if you need real-time insights into your systems? Another powerful platform for real-time data analytics and storage is InfluxDB. Let's compare how they fare with one another.

    Prometheus is a memory-efficient, quick, and simple infrastructure monitoring system. InfluxDB, on the other hand, is a distributed time-series database used to gather information from various system nodes. In this article, we are going to compare Prometheus and InfluxDB. Both systems have their strengths and weaknesses, but they are both effective monitoring tools. If you are looking for a system that can monitor your database servers, then Prometheus is a good option. If you are looking for a system that can monitor your entire infrastructure, then InfluxDB is a better choice.

    What exactly is Prometheus?

    Prometheus is a time-series database and monitoring tool that is open source. Prometheus gives its users sophisticated query languages, storage, and visualization tools. It also includes several client libraries for easy interaction. Prometheus can also work with various systems (for example, Docker, StatsD, MySQL, Consul, etc.)

    TIPS

    Prometheus can be great for monitoring as long as the environment does not exceed 1000 nodes. Prometheus + Grafana = best ecosystem

    What is InfluxDB?

    By InfluxData, Inc., a database management system called InfluxDB was created. InfluxDB is open-source and cost-free to use. The InfluxDB Enterprise version is installed on a server inside a corporate network and comes with maintenance contracts and unique access controls for business customers. A web-based user interface for data ingestion and visualization is also included in the new InfluxDB 2.0 version, which operates as a cloud service that is fully customizable.

    TIPS

    When it comes to storing monitoring metrics, InfluxDB excels (e.g. performance data). If you need to store different sorts of data, InfluxDB is not the best option (like plain text, data relations, etc.)

    Let's see how these differ from one another

    Features Prometheus InfluxDB
    Data Gathering Prometheus is a system that operates on the principle of pull. The metrics are published by an application at a certain endpoint and Prometheus retrieves them on a regular basis. The system InfluxDB is based on is a push-based system. It requires an application to push data into InfluxDB on a regular basis.
    Storage Prometheus and InfluxDB both follow the key/value datastores. However, these are executed very differently on the two systems. Each metric in Prometheus is kept in its own file and is stored in indices that use LevelDB. Metrics recording and monitoring based on those are the major uses of Prometheus. Both the indices and the metric values are stored in monolithic databases by InfluxDB. Compared to Prometheus, InfluxDB often uses more disc space. The best database for event logging is InfluxDB. So we have a choice based on the requirements.
    Extensibility and Plug-ins Prometheus’ key benefit is its widespread community support, which stems from its CNCF-accredited project status. Many apps, particularly cloud-native applications, already support Prometheus. While InfluxDB has a lot of integrations, it doesn’t possess as many as Prometheus.
    Case Studies Prometheus was designed for monitoring, specifically distributed, cloud-native monitoring. It shines in this category, with several beneficial integrations with current products. While InfluxDB can support monitoring, it is not as well known as Prometheus for this purpose. As a result, you may have to develop your own integrations. If you want to do more than a mere monitoring tool, InfluxDB is a fantastic solution for storing time-series data, such as data from sensor networks or data used in real-time analytics.
    Query language Prometheus uses PromQL, a language that is much easier and has no connection to conventional SQL syntax. Let's say we want a number for CPU load that is greater than 0.5. In that case, we can simply enter CPU load>0.5 in the Prometheus command prompt. For its querying purposes, InfluxDB uses a standard SQL syntax known as InfluxQL. For instance, we could write select * from tbl where CPU load>0.5 in the Prometheus cell. This seems simple to an associate with a background in SQL, but Prometheus is also not a challenging experience.
    Community Prometheus is an open-source project with a huge community of users that can rapidly resolve your queries. Having a big network of support is an added benefit since there is a high probability that the challenges one is having might previously have been encountered by someone in the community. InfluxDB, despite its popularity, needs to improve on community support in comparison to Prometheus.
    Scaling When the load rises, the monitoring Prometheus servers require scaling as well.This is due to the fact that the Prometheus server is independent. Thus, the Prometheus server works great for the simpler load. Since the commercial section of Influx DB is distributed, there will be many interconnected nodes. As a result, as the server scales up, we don’t have to worry about scaling nodes. Thus, Influxdb nodes might be considered redundant while handling complicated loads.

    TIPS

    InfluxDB performs exceptionally well at storing monitoring metrics (e.g., performance data). Compared to Prometheus, InfluxDB utilizes more disc space and has a monolithic data storage strategy. It performs well for recording occurrences.

    Conclusion

    As a result, you can consider the factors discussed in this article while choosing between Prometheus and InfluxDB as monitoring systems for time series data, depending on your business case. When it regards monitoring services for time series data, both platforms are extremely well-liked by enterprises. Some claim that PromQL is new and InfluxQL is similar to SQL and will thus be better, but the reality is different. PromQL is considerably more user-friendly for querying, so go for it. Prometheus has a lot more functionality and integrations, so you can choose it. InfluxDB is a better option if you're looking for something specifically for IoT, sensors, and other analytics.

    Relevant Topics:

    https://prometheus.io/ https://github.com/influxdata/influxdb https://v2.docs.influxdata.com/v2.0/ https://www.influxdata.com/blog/multiple-data-center-replication-influxdb/ https://logz.io/blog/prometheus-monitoring/

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  • Mar 24, 2022
  • 8 Proven Ways to Reduce Your AWS EC2 Costs

    AWS is everywhere and many organizations are leveraging it’s power. But with the power of AWS comes the EC2 cost which is undoubtedly a big component of your cloud payment.
    It is essential to understand how to reduce AWS EC2 costs. AWS is everywhere and many organizations are leveraging its power. But with the power of AWS comes the EC2 cost which is undoubtedly a big component of your cloud payment. It’s a fact that most new startups fail to launch their business because of poor financial management. Understanding the AWS billing cycle and how it works is critical to keeping your AWS EC2 costs lowering. In this blog, you will learn about EC2 and effective methods to reduce your AWS EC2 costs without compromising your operations.   pricing-model
     

    Here are 8 Proven Ways to minimize your EC2 costs:

     

    Decide on EC2, ECS, Fargate Or Serverless Archictecture

      Instances that can fulfill your applications' and workloads' needs. You can do this by evaluating your computing demands. Memory, network, SSD storage, CPU architecture, and CPU count are all factors to consider. Once you have this information, you should seek an instance that offers the greatest performance for the amount you are willing to pay. It is not hard to discover low-cost cloud instances based on your requirements. We can use serverless architecture if the REST service or deployment does not rely on the existence of running machines and can be an event driven architecture. We can also set up ECS or Fargate machines with the right size, memory, and storage to scale up or down depending on your needs.
     

    TIPS

    You can save licensing cost with predefined or bulk license management.

     

    Leverage reserved EC2 instances

      Reserved Instances are a way to buy EC2 machines for a long term and reduce overall pricing through an agreed discount. Since a reserved instance is a pre-paid model, Amazon offers a 75 percent drop on the hourly pricing per instance. As a result, the entry-level instance will cost less. The availability of the reserved instance model is likewise higher than that of the on-demand instance. Why? In a nutshell, it's because it's prepaid. As a result, it is pre-booked, allowing Amazon to schedule the time required. Finally, users can sign up for a one-year or three-year commitment to use the EC2 reserved instance.   

    Leverage GPU Instances

      CPUs and GPUs have a significant impact on both cost and performance. You would choose which type is most suitable for your requirements. For example, if you wish to do machine learning activities on a cloud, you should use modern GPU instances such as the G3 or P3 series. Even though GPUs have a higher cost per hour, GPU instances can dramatically accelerate training time and result in cost savings (as compared to CPUs).  

    Spot Instances for stateless and non-production workloads

      Spot instances can save a lot of money for stateless and non-production workloads. You can save up to 90% off the on-demand pricing and lower your AWS EC2 expenses. The fact that Spot Instances could be taken before the instance is used and that they are susceptible to change should be noted.  

    Leverage Tags & Setup Availability times

      Understanding the NFR Non-functional requirements of a business can help determine the hours our EC2 machines need to run. On this basis, we can schedule the machine's startup and shutdown times and prevent unnecessary running costs and downtime for the devices. You can save money on EC2 by prioritizing some EC2 instances over others. For Example, You could restrict your search to only production, non-production, and other Instances. The AWS dashboard and the AWS API are both used to find and optimize instances using tags. Security and compliance are other possible uses for Tags.  

    Auto-Scaling

      The Amazon Web Services (AWS) Auto Scaling mechanism ensures that the appropriate number of Amazon EC2 instances are running to meet the demand of a specific application. Auto Scaling changes compute performance dynamically based on a predetermined schedule or the current load measurements, increasing or decreasing the number of instances as necessary. To modify capacity to actual demands, you can use different types of scaling options that Amazon offers. By dynamically reducing the capacity, you can easily save money and prevent waste. Configure Auto Scaling with precision to maximize cost savings. You can over-provision capacity if you use Auto Scaling for applications that are too big or include too many instances.  

    EC2 Instances of appropriate size

      Right-sizing is adopting an EC2 instance type that is a suitable match for your application or workloads to prevent underutilized resources. To identify the kind of instance necessary, evaluate the number of CPU and memory resources utilized by a certain application. After that, you can choose the instance type and number of instances that are most suited to your needs. By choosing your size wisely, you can gain also the most of your reserved instance purchases. Once you've determined the best configuration for your instance, you can save even more money by signing up for a specific term and obtaining reserved instances. However, it may be difficult to determine the right size when dealing with unpredictable workloads, and reserved instances are often wasted.  

    Orphaned Snapshots should be detected and eliminated

      As per standard rules, any associated EBS volumes are automatically erased when an EC2 instance is terminated. Any snapshots that are still on S3 and are billing. These expenses might be more than you anticipate. Most backups are incremental, while the first snapshot captures the whole drive. Additionally, over time, incremental snapshots may need more data storage than the first one. Although S3 is less costly than EBS volumes, you'll need a strategy for deleting EBS volume snapshots when an EBS volume is destroyed. Over time, this might result in considerable storage cost savings.   

    TIPS

    Always plan to set up budgets and consume resources within the budget. Custom alerts can also help us realize if we used 50%, 75% or 90% of our limit

     
      Learn more about the AWS cost explorer

    Conclusion

      The Amazon EC2 service is a great way to get some computing power without having to manage a server. However, you can't leave an instance running all day and night without paying for it. For one thing, it's not free! Common problems with EC2 costs include tracking reserved instances with unused hours, underutilized and idle EC2 instances, and migration of EC2 instances from a previous generation. Oversizing and inefficiency of the system bring their own set of challenges. Finally, there are numerous ways to lower your EC2 costs. By following the tips in this article, you can resolve the above challenges, save money and improve your efficiency.The cost of an EC2 instance is based on the instance configuration associated with data processing needs. Successfully minimizing EC2 expenses is reliant on the balance between the cloud computing needs to process corporate data and the quantity of the data that is being processed. To reduce your EC2 costs, get in touch with us. Making the best choice for your tools will be easier for you with our expertise.    

    Related Blog

      https://segment.com/blog/spotting-a-million-dollars-in-your-aws-account/ https://cloudcheckr.com/cloud-cost-management/aws-cost-issues-quick-fix/ https://www.apptio.com/blog/decoding-your-hidden-aws-ec2-costs/
       

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  • Dec 23, 2021
  • Top 4 Python development Companies in Chennai

    Python is a popular high level Object oriented programming language which helps to work quickly and integrate systems more efficiently
    Python is a popular high level Object oriented programming language which helps to work quickly and integrate systems more efficiently. There is a great demand for developing applications in Python as well as for migrating existing applications to Python because of its dynamic nature. Full blown enterprise applications on Django or minimalist microservices with Flask or modern API development with Python Fast API - Python has a huge share in developer preference for building high performance applications. We want to briefly list the key capabilities and details about the Top 4 Python development companies in Chennai

    1. Techno Kryon

    Techno Kryon is a web development company in Chennai. They have Offshore Python developers with more than 5 years of experience in building web applications using Python technology. Their services are result and quality oriented. technokryon Company Website:  https://www.technokryon.com

    Employee Reviews

    • Like Work Culture, Team Coordination
    •  A place where we can learn and work as a family.A small company with a high working culture.

    Technologies they work on

    Back End: Java, Python, Node.js, Php Front End: React.js, Angular Framework: Django, Flask, FastAPI, Spring / Spring Boot, Express Database: MySQL Infrastructure: Google Cloud

    Industries from where their Clients belong

    Media and Entertainment Health and Healthcare Retail

    2. 10Decoders Consultancy Services Private Limited

    10Decoders is the best Python development company in Chennai, India building highly scalable applications for clients across the globe. 10Decoders has immense experience in developing scalable and robust web applications for various business domains like Healthcare, FinTech, Argitech etc . 10decoders Company Website:  https://10decoders.com/ Number of Employees: 100+

    Employees Review

    • “Great place to explore, challenge and strengthen your skills. An actively growing company, you’d love to be a part of!”
    • “There are so many great things about working at 10Decoders. It provides great opportunities to develop my technical skills. An overall, work is good in its way, the client and co-workers are well supported. Excellent place to start your career with. Has multiple domains to gain knowledge on”
    • “Friendly Staff and Friendly co-workers, best work to improve ourselves and learn new technologies”

    Technologies we Work On

    Back End: Java, Python, Node.js Front End: React.js, Angular Framework: Django, Flask, FastAPI, Spring / Spring Boot, Express Database: MongoDB, DynamoDB, MySQL, MS SQL Infrastructure: Azure, AWS, Google Cloud, Digital Ocean

    Industries from Where Our Clients Belong

    • FinTech
    • Healthcare & MedTech
    • Agriculture

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    3. iStudio Technologies

    iStudio Technologies is a web designing company in Chennai. Being one of the top Python development companies in Chennai, iStudio Technologies have experts for Python Django development who can provide end to end solution for web application development. istudiotech Company Website https://www.istudiotech.in

    Employee Reviews

    • Good atmosphere filled with talented people. U get motivated and trained. Great place to take you ahead in your career.
    • Working for more than a year. Have learned and enhanced my skills. Good management to keep you motivated.

    Technologies they work on

    Back End: Java, Node.js, Php,Python Front End: React.js, Angular, Flutter Framework: Django, Express JS Database: MongoDB

    Industries from where their Clients belong

    Healthcare E-Commerce Retail

    4. Dextra Technologies

    Dextra Technologies is a web Application, Website Development and Digital Marketing Company in Chennai. They have a team of professional experts for website and web portal development. dextratechologies Company Website https://dextratechnologies.com

    Employee Reviews

    Great Place to Work Leadership team handle very difficult circumstances all the time in the most graceful way possible

    Technologies they work on

    Back End: Python, Php Front End: HTML, CSS, jquery, Bootstrap Framework: ASP.NET MVC Framework Database: MS SQL Server, MySql, Oracle

    Industries from where their Clients belong

    Healthcare E-Commerce Education

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    Case Studies

  • Aug 24, 2021
  • Top 5 Java Development companies in Chennai

    There is a constant requirement for new technologies in this digital era. Even though many new languages are in high demand, the demand for Java
    There is a constant requirement for new technologies in this digital era. Java language always have a high demand in spite of many new languages coming up. We have shortlisted the top 5 Java development companies in Chennai. A brief overview of each of these top 5 Java companies is given below

    1. Hakuna Matata Tech Solutions

    Hakuna Matata Tech solution develops applications by using latest digital technologies to come-up with Client specific solutions which can transform enterprises from their traditional processes impacting their efficiency and productivity to have a rapid growth hakunamatatatech Company Website  
    https://www.hakunamatatatech.com/ Number Of Employees 200+

    Employees Review

    • “Good place to start working”
    • “Excellent work culture and platform for learning”
    • “Good place to learn and grow”
    Technologies They Work On Android, Java, iOS, Xamarin, ElectronJS, Node.JS, CSS, HTML, AngularJS, C#, Microsoft SQL Server, Swift, .NET Core, Laravel, MongoDB, Php, JQuery, MySQL, JavaScript Industries From Where Their Clients Belong
    • Media
    • Healthcare
    • Manufacturing
    • Retail
    • Construction

    2. 10Decoders Consultancy Services Private Limited

    10decoders is a cloud engineering company with solid experience architecting and building highly scalable and highly available systems on the cloud. 10decoders helps startups and businesses to scale their remote teams with the right people 10decoders has a vast client base and experience working on silicon valley startups, healthcare giants & Fin-tech companies in the USA & Canada. 10decoders specialize in AgriTech and RegulatoryTech product implementations also Started as a small company with 5 members in 2015, 10decoders has grown into a team of 80 members with capabilities across web, mobile, and cloud engineering 10decoders Company Website  https://10decoders.com/ Number of Employees  130+ Industry Experience  7 Certified Engineers  40% Clients  110+

    Employees Review

    • “Great place to explore, challenge and strengthen your skills. An actively growing company, you'd love to be a part of!”
    • “There are so many great things about working at 10Decoders. It provides great opportunities to develop my technical skills. An overall, work is good in its way, the client and co-workers are well supported. Excellent place to start your career with. Has multiple domains to gain knowledge on”
    • “Friendly Staff and Friendly co-workers, best work to improve ourselves and learn new technologies”

    Technologies we Work On

    Front End: React.js, Angular Back End: Java, Python, Node.js Framework: Django, Flask, FastAPI, Spring / Spring Boot, Express Database: MongoDB, DynamoDB, MySQL, MS SQL Infrastructure: Azure, AWS, Google Cloud, Digital Ocean

    Industries From Where Our Clients Belong

    • FinTech
    • Healthcare & MedTech
    • Agriculture

    3. Siam Computing

    Siam computing is one of the top software development companies in Chennai. They have professional services for developing and improving software solutions. The developers make sure that they effectively use the latest technology and the latest digital strategies and technology are integrated siamcomputing Company Website  https://siamcomputing.com/ Number Of Employees 60+

    Employees Review

    • “One of the best companies I have worked for”
    • “Best Place to develop your skills”
    • “Web development – The best place to develop your skills”
    Technologies They Work On PHP, Python, Node.JS, ReactJS, Angular, Laravel, Django, MySQL, Microsoft SQL, MongoDB, HTML5, CSS3

    Industries From Where Their Clients Belong

    • Real Estate
    • Marketing and Advertising
    • Education
    • Information Technology
    • Financial & Payments
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    4. Zencode Technologies

    Zencode offers a wide range of business solutions to its customers. From mobile application development to artificial intelligence and data analytics, they cover everything. Their main aim is to provide top-notch services to the customers to fulfill their varying business needs. Over the years, they have offered out customized business solutions to a huge number of industries which include Finance, Engineering, E-commerce, Logistics, and Healthcare zencode Company Website  https://zencode.guru/ Number Of Employees 51-200

    Employees Review

    • “Working in Zencode will build your confidence as you are encouraged at every step in your work”
    • “Good work culture and environment. The company is striving towards innovation and latest technology, providing opportunities for employees to learn and grow professionally”
    Technologies They Work On  PHP, AngularJS, ReactJS, JavaScript, MySQL, AJAX, jQuery, CSS, and HTML

    Industries From Where Their Clients Belong

    • Hospitality & Leisure
    • Business Services
    • Financial Services

    5. Agriya

    Agriya is a software development company with more than 150 employees spread across two development centers in India. Their head office is located in Chennai. Agirya is listed in top 10 software companies in Chennai due its top-quality work. The company was established in 2000 agriya Company Website  https://www.agriya.com/ Number Of Employees  50 – 249

    Employees Review

    • “Peaceful environment to work”
    • “Perfect company to kick-start your career”
    • “Great concern to learn and work with new technologies”
    Technologies They Work On  HTML, CSS, JavaScript, Ajax, Bootstrap, Angular.JS, Backbone.JS, Vue.JS, React Native, PHP, Java, .Net, Python, Ruby Rails, Node.JS, Android, iOS, C++, C#, C, Swift

    Industries From Where Their Clients Belong

    • Information Technology
    • Art, Entertainment & Music
    • Business Services
    • Advertising & Marketing
    • Retail

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    Case Studies

  • Aug 12, 2021
  • Remote Monitoring by Doctors

    Communication between Doctor and patient is very important for recovery of a patient. With the help of remote monitoring devices, patients need not travel back and forth between their house and hospital

    Introduction

    Communication between Doctor and patient is very important for the recovery of a patient. Remote monitoring devices avoids the back and forth travel of patients between hospital and their house. Their health condition can be regularly monitored by using remote devices and hospitalization of the patient can be prevented. Remote patient monitoring is shortly abbreviated as RPM and is a method of capturing patient’s health data. It captures all vital information of a patient such as BP, Sugar level, heart rate, etc. Remote monitoring has proved to be advantageous by reducing patient readmission and allow treatment sooner

    Overview of market share

    The global remote patient monitoring market is projected to reach USD 117.1 billion by 2025 from USD 23.2 billion in 2020, at a CAGR of 38.2% between 2020 and 2025. The factors that boost the demand for remote patient monitoring are a reduction in the number of health care staff and an increase in awareness of telemedicine. There is a growth in the market due to the efforts taken for the discovery of Innovative devices Patient remote monitoring is becoming a sturdy market

    How remote monitoring Works

    Even while at home patients can carry out their normal activities and monitor their health. The remote monitoring devices helps them to monitor their health and collect data These monitoring devices are integrated with patient monitoring apps. The apps transmits the data electronically to their Doctor Doctors then examine this patient data from a distance. In case of a patient who needs immediate treatment or attention, alerts are sent to the patient’s mobile and they receive it in the form of notifications. This remote monitoring technology helps to detect any issue at an earlier stage

    What are the best features to have in remote patient monitoring apps

    Some of the best to have features of remote patient monitoring apps

    Notifications

    Timely notification is an important feature of remote patient monitoring. Timely notification may prevent them from a serious illness. Also, notifications should be in sync for both patient and doctor

    Integration with devices

    Integrating with monitoring devices is an important feature. When integrated, the app will be able to collect data from these devices from time to time which might help to monitor progress over a period of time

    HIPAA Compliance

    Patient data is highly sensitive and it needs to be protected. It should be ensured that it meets HIPAA compliance Remote monitoring apps should have physical, network, and process security measures to ensure HIPAA compliance

    Support for BLE

    Remote monitoring apps need to support Bluetooth connectivity which is very essential for the transfer of data between monitoring devices and apps

    Integration with doctor’s system

    Integration with a Doctor’s system through secure API built on FHIR industry standard to ensure proper exchange of data between multiple systems is an important feature that needs to be handled

    doctor-system

    Tech Stack

    Blockchain

    The patient and Doctor are connected through voice and video calls. Encryption of patient data prior to transmission is very important. Blockchain technology is used for encrypting the sensitive patient data

    Cloud Storage

    Cloud services are used for storage of data as it improves privacy and security control of the app. Also, data retrieval is very quick from the cloud servers. So storage and transfer become efficient

    Artificial Intelligence

    Artificial Intelligence-based Chatbots are used for patients to get their queries answered as doctors are not available round the clock

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="offshore teams blog"]

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    Case Studies

  • Aug 12, 2021
  • How to effectively use JIRA to drive the agile transformation of your organization?

    Agile transformation is the sustained organization-wide process of helping individuals and organizations undergo the necessary mindset shift to reap the full benefits of agility

    Introduction

    Agile transformation is the sustained organization-wide process of helping individuals and organizations undergo the necessary mindset shift to reap the full benefits of agility. What makes Agile transformation necessary for the traditional business is the constant state of change as well as the democratization of value definition and delivery. By transforming the entire organization to be more Agile, big companies can retain a competitive advantage. Agile transformation is necessary for organizations to thrive in today’s markets and into the future As a leading collaboration platform for agile teams, JIRA Software boasts powerful features for marketers. JIRA is a proprietary issue tracking product, developed by Atlassian. It provides bug tracking, issue tracking, and project management functions. Also, JIRA has integrated solutions for cross-functional projects. You can easily bring all teams together to collaborate on a shared goal

    Overview of Market Share

    Looking at Atlassian JIRA customers by industry, Computer Software (26%) and Information Technology and Services (14%) are the largest segments. Atlassian TEAM delivered better-than-expected fourth-quarter fiscal 2021 results. The company’s non-IFRS (International Financing Reporting Standards) earnings per share of 24 cents beat the Zacks Consensus Estimate of 18 cents Atlassian forecast adjusted earnings between 38 cents and 39 cents per share on revenue between $575 million and $590 million for the first quarter. The company witnessed solid demand for its cloud-based products, primarily led by smaller customers, while the cloud migration momentum continued for larger clients Atlassian reported an operating loss of $7.5 million for the quarter, up from a loss of $3.3 million a year ago. Despite the year-over-year dollar increase, the operating margin loss remained 1%. Its shares jumped 24% to $331.96 per share Friday at the last check

    How JIRA helps in the Agile Transformation of the Organization?

    Creating a Scrum Project

    Once you create and log in to an account in Jira Software, you can select a template from the library. Select Scrum and then, you’ll be prompted to choose a project type. If your team works independently and wants to control your own working processes and practices in a self-contained space, consider giving the team-managed Scrum template a try

    Creating User Stories or Tasks in the Backlog

    In Jira Software, you can create work items like user stories, tasks, and bugs "issues". Create a few user stories with the quick create option on the backlog. If you don't have user stories in mind, just create sample stories to get started and see how the process works. Once you've created a few user stories, you can start prioritizing them in the backlog. In Jira Software, you rank or prioritize your stories by dragging and dropping them in the order that they should be worked on

    Creating a Sprint

    Create your first sprint in the backlog so you can start planning the sprint Sprint: In Scrum, teams forecast to complete a set of user stories or other work items during a fixed time duration, known as a sprint. Generally speaking, sprints are one, two, or four weeks long. It's up to the team to determine the length of a sprint. Once a sprint cadence is determined, the team perpetually operates on that cadence. Fixed length sprints reinforce estimation skills and predict the future velocity for the team as they work through the backlog

    sprint

    Hold the Sprint Planning Meeting

    At the beginning of a sprint, you should hold the sprint planning meeting with your team. The sprint planning meeting is a ceremony that sets up the entire team for success throughout the sprint. In this meeting, the entire team discusses the sprint goal and the stories in the prioritized product backlog. The development team creates detailed tasks and estimates for the high-priority stories. The development team then commits to completing a certain number of stories in the sprint. These stories and the plan for completing them become what is known as the sprint backlog

    Start the Sprint in JIRA

    Name the sprint. Some teams name the sprint based on their sprint goal. If there is a commonality between the issues in the sprint, name the sprint around that theme. Add a duration of the sprint and start and end dates. The start and end dates should align with your team's schedule Following are the steps to be followed after starting a newsprint
    1.  Hold the daily standup meetings
    2.  View the Burndown Chart
    3. View the sprint report
    4. Hold the sprint review meeting
    5. Hold the sprint retrospective meeting
    6. Complete the spring it JIRA
    If the sprint has incomplete issues, you can move the issue/issues to the backlog, move the issue/issues to a future sprint, or move the issue/issues to newsprint, which Jira will create for you

    What are the Best Features of Using JIRA to Drive the Agile Transformation?

    Agile Project Management

    The platform primarily focuses on agile project management, offering the Scrum approach. It also has the capability to capture regulatory evidence at different stages of the development process. Moreover, Jira Software supports all sorts of estimation techniques, be it by hours, story points, or more. This way, you can make sure that you are working with accurate data at all times

    Customizable Workflows

    With Jira, you can even create custom workflows and issue schemes in more specific cases. This will take much of your developers’ burden off their shoulders, and empower your project management units to maximize the potential of their idea. If you’re using Jira’s cloud-based solution, the configuration will take even less time And custom dashboards are a one-stop-shop for all of the information you need to organize projects, and achievements in a single view

    Product Roadmaps

    It is a plan of action for how a product or solution will evolve over time. When used in agile development, a roadmap provides crucial context for the team's everyday work and should be responsive to shifts in the competitive landscape. To build a roadmap, product owners take into account market trajectories, value propositions, and engineering constraints. Once these factors are reasonably well-understood, they are expressed in a roadmap as initiatives and timelines. Once a roadmap is built, it needs to be shared with the entire product team so everyone understands the vision and direction

    Bugs and Defect Management

    JIRA helps you to quickly capture, assign and prioritize bugs and track all aspects of the software development cycle. JIRA's powerful workflow engine provides a clear view of a bug's status, and automation keeps you in the know with notifications as issues transition from backlog to done. JIRA gives you full visibility and control of your products' end-to-end development Once you have identified a bug, create an issue and add all relevant details, including descriptions, severity level, screenshots, version, and more. Issues can represent anything from a software bug, a project task to a leave request form, and each unique issue type can have its own custom workflow

    Powerful Search and Filtering

    JIRA Software comes with advanced search capabilities powered by Jira Query Language(JQL) that offers teams detailed views into their work. Query results can be saved and used as filters and views across Jira (including boards). The three flavors of search in Jira - Quick, Basic, and Advanced - can help you find important information about your projects

    Advanced Reporting

    JIRA offers reporting in a number of different formats. Project reports that are available from the home screen of the selected project, Gadgets that can be added and arranged in Dashboards and for each filter, the issue navigator offers various output formats that can be used in third-party reporting software

    Technological Stack

    Business Tools

    JIRA

    Jira Software is built for every member of your software team to plan, track, and release great software

    Acunote

    Designed as a simple yet powerful Agile PM and Scrum tool for companies large and small, Acunote allows project teams to plan sprints, identify backlog items and monitor burndown in real-time

    Application and Data

    Java

    A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms=" jira blog"]

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    Case Studies

  • Aug 12, 2021
  • How To Build An E-Commerce for wholesale dealers

    Electronic commerce is buying and selling of products through online services. In E-commerce for wholesale the products are sold in bulk from the e-commerce site instead of selling individually to each person

    Introduction

    Electronic commerce is buying and selling of products through online services. In E-commerce for wholesale the products are sold in bulk from the e-commerce site instead of selling individually to each person. Wholesale reduces the cost of doing business and is intermediate between manufacturer and retailer. Since items are sold in bulk there might be larger orders. So the products can be sold quickly without much need for marketing. Ecommerce for wholesale is completely new but it is growing fast these days. There is a trigger in growth because of the increase in internet connection and smartphone use

    Overview of market share

    The global e­commerce market size was valued at USD 6.64 trillion in 2020 and is expected to grow by a compound annual growth rate (CAGR) of 18.7% from the period 2021 to 2028. The COVID-19 pandemic brought about a shift in wholesale dealer's preference for online shopping, creating avenues for growth. The factors that affected e­commerce business outlook are the changes in consumer behaviour, increase in order quantity, physical stores closure and disruption in supply chain While retail sales dipped in 2020,  e-commerce sales witnessed a surge. Several businesses are now focused on moving their customer online Established organizations and large enterprises are moving towards online business due to lesser expenditure in communication and infrastructure. E-commerce offers the organization an easier reach for the dealers/customers, and hence necessary exposure to business is also achieved. Nowadays, the marketing options are in abundance due to the popularity of social media applications, which helps in driving the market for e-commerce towards a growth path

    How e-commerce for wholesale dealers Works

    In wholesale e-commerce, the products are sold in bulk and the wholesaler is the middle man in the supply chain which starts from Producers. The wholesale dealers buy the product in bulk from a manufacturer or dealer through their online site. Here the dealer places his order for products on the website. The concerned organization will process the order and supply the goods to the wholesale dealer. It is then sold to another wholesale dealer or directly to the consumers

    wholesale-dealers

    What are the best features to have in e-commerce for wholesale

    Some of the best to have features of wholesale eCommerce are

    Payment Flexibility

    The payment gateway and the payment options offered will all make a difference in the success of a business. Users of e-commerce websites should have payment flexibility. They should be able to pay in any way that will work for them. A payment gateway with advanced functionalities should be integrated to support the business and its growth

    Easy to Use checkout feature

    Adding items to the cart and then checking them out to proceed with payment must be an easy process. In case the checkout feature is too complicated the buyer may feel irritated and abort the process of buying products. So this should be easy to use a feature

    Ease of Navigation

    The key to the success of any e-commerce website is east to Navigation. The navigation should be easy, clear, and user-friendly. Extreme care should be taken while designing and developing the User Interface (UI). Clear navigation will improve the User Experience (UX) which will attract more users

    User Reviews

    Most people who shop on the website read the reviews before purchasing the product. People think that negative reviews will diminish sales. But it is actually not true. It is often positive to have negative reviews. When there are only positive reviews people think that they are fake. When there are true reviews, it will attract more people to the website

    Security

    The e-commerce platform should be secure for the users. Using features like an SSL certificate for a secure connection between user and e-commerce site, firewall to provide a gateway between networks and allow only authorized traffic, two-factor authentication for a user to log in would be ideal for any e-commerce site

    Tech Stack

    Front end for E-commerce

    The front end for an e-commerce website can be developed using JavaScript libraries like Angular or React, CSS, HTML

    Back end for E-commerce

    The programming languages used for server-side coding are C#, PHP, and Python. Depending on the requirement of the project and the goals of the business-appropriate language is selected

    Third-party Services

    The e-commerce website needs to be integrated with third-party services like payment gateways, shipping modules, CRM, and analytics tools for the effective functioning of the e-commerce site

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="E-Commerce blog"]

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    Case Studies

  • Aug 10, 2021
  • How To Build A Productivity Tracking App

    Productivity Tracking App is a free time tracking software that notes and analyzes productivity at work. It is a tool that has been chosen by startups and large enterprises that employ hundreds of people.

    Introduction

    Time tracking software helps both employees and managers to track the project time along with expenses and other operations of the enterprise effectively. There will be good growth in the time tracking software industry because of prevailing remote work, use of cloud­ based time tracking software, and mobile phones being used for official work

    Overview of Market Share

    Time tracking software enables managers and employees to manage and track project time and expense, payroll, and other enterprise operations effectively. Furthermore, due to the emergence of cloud-based time tracking software, the prevalence of remote work, and the use of mobile phones for official purposes, it is expected that the time tracking software industry will grow during the forecast period. The Global time tracking software market is expected to register at a CAGR of 20.69% By the end of 2027, the Time tracking software market size is estimated to be USD 2043.83 billion. The major factors that are driving the market are the improvement in inventory management, asset tracking, and the usage of consumer goods, especially in the North-America

    productivity

    How does Productivity Tracking App work?

    Time Tracking

    It tracks the time worked by each and everyone on your team and gives you a breakdown by client, project, and task. It helps you to track the time spent working and time wasted and also to identify the inefficiencies

    Screenshots

    Productivity Tracking app captures Screenshots of employee monitors every 5 minutes (or turned off). It helps you to monitor exactly what your team is doing and how. By this, you can identify time-wasting, distractions, and inefficiencies. Screenshots are only taken when team members indicate that they’re working to eliminate privacy concerns

    Time Use Alerts

    Employees get a pop-up or notification alerts if they sit idle for too long, or if they are back from sleep mode Sitting idle for too long will be notified as “You are in idle mode for long. Please start the timer to continue”

    functions

    Best Features to have

    Here are the basic key features required for a productivity tracking app to make it more user-friendly and accommodating

    Signup and Login

    It allows users to have the option of creating their account or if you are running a LARGE ENTERPRISE, it lets you create multiple organizations with multiple users

    Users and Projects

    Users and projects can be created for each Organization. For each user project can be assigned. This will help to track the user’s activities for that particular project. Track in which project they are working on and how much time they spent on each project

    Clients Feature

    Give your clients access to the Productivity Tracking app at no extra cost. The client can see the screenshots and can also get reports regarding the tasks that were worked. Your clients will be restricted to seeing only data about work that you’ve done for them, rather than all work done in your company

    All Devices

    It can be used on desktops, tablets, and mobile phones – wherever the work is, we track it

    Activity Monitoring

    It helps you to track your employees’ activities during their work time at 0 Cost. So you can easily monitor where they are in the project and how they are working

    View Screenshots

    You can also find how your employees are spending every five minutes of your workday by capturing the screenshots

    Technological Stack

    React JS

    ReactJs is a toolkit for creating user interfaces introduced by Facebook in the year 2011. To merely put across, React is a solution that helps developers to resolve issues faced when building user interfaces. It enables developers to create intricate user interfaces that have components that will change regularly over time without writing tricky JavaScript codes every time

    Angular

    Angular is a TypeScript-based free and open-source web application framework led by the Angular Team at Google and our team create a web application using angular with responsiveness and deliver good products

    Electron

    We create desktop applications using Electron for cross platforms support with UI frameworks like angular and deliver effective user-friendly application

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Productivity Tracking blog"]

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    Case Studies

  • Jul 28, 2021
  • Video on Demand platform

    Video on Demand platform delivers direct fast and high-quality transactional video to its customers to watch on TV or PC.

    Introduction

    Video on Demand platform delivers direct fast and high-quality transactional video to its customers to watch on TV or PC. It helps users to access online content from video libraries. Users can watch the videos according to their own convenience from any device. VOD is a dynamic feature and is offered by Internet Protocol. It is transmitted through Real-Time Streaming Protocol. It is the future of online content delivery

    Overview of market share

    The global video-on-demand market size is projected to reach 159.62 billion USD by the end of 2027. The worth of the VOD market was USD 53.96 billion in 2019 and will exhibit a CAGR of 14.8% during the forecast period, 2020-2027. This information was published by Fortune Business Insights. Smartphone penetration is increasing across the world which will create several opportunities for market growth. The availability of low-cost cloud platforms will also be a favor for market growth. VOD is gaining popularity over the last few years

    market-share

    How VOD Works

    In VOD the video content is stored on a server in digital form. When a User makes a demand request, it is compressed and transmitted through the internet. Then at the user’s end, the video is again decompressed, decoded, and stored on a video server in the user’s device. Here, the user has full control of the video. Video can be watched instantly, fast-forwarded, rewinded, or paused. These capabilities are available only in VOD and not in other traditional methods. These videos can also be downloaded and watched later A library contains all videos in uncompressed format. Transcoders are used to compress videos before transmitting them through the internet

    What are the best features to have in VOD

    Access for Multiple Users

    Multiple users should be granted access to view the video contents. Enough security measures need to be handled to make sure that the video content is available only to the intended Audience and not to external people

    Multiple viewing options

    Users should have multiple viewing options to view them on a wide range of devices. When users have many options they will show more interest in viewing the videos

    Recording Live Events

    The Live events can be captured, edited, and recorded. This can be stored in the video content library for the ease of access to the User

    Video Analytics

    This will help to analyze which videos are most watched, which videos are popular, and what type of devices are used for watching. This will help to make business decisions

    User interactive

    The videos should be made user-interactive. For example, for education-related videos quizzes can be inserted. Surveys can be included to get feedback about a product from users

    interactive

    What are the Benefits of VOD

    There are multiple benefits of VOD. Few of them are listed here
    • The videos will be available in the library for a long period of time. Users can access the video at any time even after years. The content can thus reach a large audience
    • The user has the option to preview, edit, add or remove the content in the video. Even effects or animation can be added to the video
    • These videos can also be viewed offline. This will help people to watch it at their own convenient time.
    • Cost-wise VOD will be cheaper compared to other traditional ones. In the case of VOD, there might be offer packages or discounts which will attract more users
    • Also, VOD gives us total control of our content. The user has the flexibility to create his own content without compromising his creativity

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    Case Studies

  • Jul 01, 2021
  • What Are The Phases of Software Development Lifecycle

    Software Development Lifecycle, in short, termed as SDLC is a process that defines various stages involved in software development for the delivery of a product.
    Software Development Lifecycle, in short, termed as SDLC is a process that defines various stages involved in software development for the delivery of a product. SDLC is very important as it gives a framework for a set of activities and ensures the quality of the product delivered. There are seven phases involved in Software Development Lifecycle. They are Planning, Requirement Analysis, Design, Implementation, Testing, Deployment, and Maintenance. Here we shall see each of these phase-in detail

    Phases of SDLC

    1. Planning

    As the quote says “By failing to prepare, you are preparing to fail”, Planning is very important for any task. Similarly, Planning is the initial phase of the Software Development Life cycle. Planning starts with listing the problems of an Existing system. Problems in the existing system are listed to come up with the objectives of the new system to be developed. Along with the scope of the new system, financial planning and Resources planning are also done in this phase. Then last comes the planning for the project schedule which is very essential to complete the project on time. Only when the planning phase is completed, it can be moved on to the other phases

    2. Requirement Gathering and Analysis

    Defining Requirements and gathering all required information like the purpose of the new system, end-users for the new system, their needs are all carried out during this phase. Risks involved in the development of the new system are also identified. The analysis is done to ensure that the end-users needs can be met by the new system. All clarifications regarding the requirements are received from the concerned team before starting on the Design part. The output of this phase will be in the form of a document more often called a Software Requirement Specification or SRS document. This document along with new system requirements also contains Software, Hardware, and Network requirements needed for the development of the new system. This will be used as the input for the design phase

    3. Design

    Design is a kind of modeling everything visually. Developers will outline the details for the new system using the Software Requirement Specification document in the form of a Design Document. The Design document will include details like User Interface which will define how the user is going to interact with the new system, Database which is going to be used for storing data, platforms on which the new system will run, Security measures to be taken to protect the system, etc. So both front-end and back-end are defined here. If required, prototypes are also defined. Prototypes give a basic idea of the actual look and feel of the new system. When the design is completed it is time to move on to the next phase, which is the development phase

    4. Development

    This phase is the coding phase. This is the most important phase of SDLC as it is where the actual software is developed. It is the longest phase of SDLC. Here the design document is converted into the software. The developers need to make sure the software meets the Software requirement specifications. Developers will have to follow coding standards and use tools like compilers and debuggers to eliminate coding defects. Identifying coding bugs and fixing them is critical here. Programming languages are chosen based on the requirements and specifications of the project. A detailed design will help in hassle-free code development

    sdlc

    5. Testing

    Testing of an application is critical before it is actually made available to the Users. This is part of a Quality Assurance process. It is started as soon as coding is completed and all coding errors are fixed. It is done by Quality Assurance Engineers. Manual or Automated Testing are performed depending on the Project. In the case of Automated Testing, many tools are available in the market. Again depending on the nature of the project automated testing tools are selected. The developed software is tested thoroughly to make sure that the requirements are met. The defects are identified and logged in Defect Tracking tools. Then they are tracked to closure. Different types of defect tracking tools are used by different companies. The initial testing done is called Unit testing. Then the individual units are integrated and integration testing is performed. The software is repeatedly tested to ensure that there are no more defects

    6. Deployment

    When the defects are all closed and no more defects are identified, the software is ready for installation. The installation phase is often called the Deployment phase. In some cases, it could be the deployment of code on a web server, and in some cases, it could be integrating with other systems. The users can start using the software after deployment. In some cases, since the software is deployed to the production environment, again another round of testing is carried out here to ensure that there are no issues in the new environment. The users could also be trained just before this phase to make sure that they are aware of the usage and features of the new system

    7. Maintenance

    Maintenance is an important phase as there might be issues identified when the end-users start using the product. In some cases, the end-users keep changing and there might be different types of issues identified. These issues need to be fixed from time to time. The maintenance time might vary depending on the size of the project. Sometimes even new features are added as per user feedback and released agile

    SDLC Models

    There are various SDLC models and the most common ones are Waterfall and Agile. We shall see about these in detail

    Waterfall Model

    This was the most commonly used and most accepted model. The output of one phase of the Software Development Lifecycle is used as the input for the next phase. So the successive phases can be started only after the completion of the previous phase. At the end of each phase review and sign-off is done before moving on to the next phase. The waterfall model is very useful when the requirements are fixed and do not keep changing. The main advantage of the waterfall model is it is easy to follow and the milestones are clearly defined

    Agile Model

    Agile is a simple and highly effective process. In the Agile model, the task is divided into small iterations of smaller durations. For each iteration, all phases of SDLC like planning, analysis, design, coding, implementation, testing, and deployment are carried out. Here there will be continuous delivery. Even when there are frequent changes in the requirement that can be handled here easily. During each sprint the new requirements come from Backlog and roll through all phases of SDLC. Since changes are inevitable the agile model helps the project to adapt to it instead of ignoring it SDLC is a systematic process and it ensures the quality of the product delivered. All phases of SDLC are very important. So adhering to phases of SDLC is very important for the success of the project

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    Case Studies

  • Jun 04, 2021
  • Cloud Migration : Lift & Shift Strategy

    Lift-and-shift is the process of migrating a workload from on premise to Cloud with little or no modification

    Introduction

    Lift-and-shift is the process of migrating a workload from on-premise to Cloud with little or no modification. A lift-and-shift is a common route for enterprises to move to the cloud and can be a transitionary state to a more cloud-native approach

    There are also some workloads that simply can’t be refactored because they’re third-party software or it’s not a business priority to do a total rewrite. Simply shifting to the cloud is the end of the line for these workloads

    Applications are expertly “lifted” from the present environment and “shifted” just as it is to new hosting premises, which means in the cloud. There are often no severe alterations to make in the data flow, application architecture, or authentication mechanisms

    It allows your business to modernize its IT infrastructure for improved performance and resiliency at a fraction of the cost of other methods

    cloud

    Overview of Market Share

    In recent days there is great growth in Cloud computing market. Companies are trying out various cloud models with right balance of flexibility and functionality The cloud migrations hosts the application and data in an effective environment based on various factors. This is the key role of cloud migration Many companies migrate their on-site data and application from their data center to cloud infrastructure with the benefits of redundancy, elasticity, self-service provisioning and flexible pay per use model. These factors are further expected to drive tremendous growth in the global cloud migration services market during the forecast period 2020-2027 According to the report, the global cloud migration services market generated $88.46 billion in 2019 and is estimated to reach $515.83 billion by 2027, witnessing a CAGR of 24.8% from 2020 to 2027 The growth of the market is attributed to an increase in cloud computation among small and medium enterprises around the globe

    What are the best features to have?

    • Workloads that demand specialized hardware, say, for example, graphical cards or HPC, can be directly moved to specialized VMs in the cloud, which will provide similar capabilities
    • A lift and shift allows you to migrate your on-premises identity services components such as Active Directory to the cloud along with the application
    • Security and compliance management in a lift and shift cloud migration is relatively simple as you can translate the requirements to controls that should be implemented against compute, storage, and network resources
    • The lift and shift approach uses the same architecture constructs even after the migration to the cloud takes place. That means there are no significant changes required in terms of the business processes associated with the application as well as monitoring and management interfaces
    • It is the fastest way to shift work systems and applications on the public cloud because there isn’t a need for code tweaks or optimization right away
    • Considered the most cost-effective model, the lift and shift help save migration costs as there isn’t any need for configuration or code tweaks. In the long run, these savings could give way to extra spending if workload costs are not optimized
    • With minimal planning required, the lift and shift model needs the least amount of resources and strategy
    • Posing the least risk, the lift and shift model is a safe option as compared to refactoring applications especially in the scenario where you don’t have code updating resources
    When is the Lift-and-Shift Cloud-Migration Model the best fit? The lift and shift approach allows on-site applications to be moved to the cloud without any significant redesigns or overhauls. You should consider using the lift and shift approach if the following apply to your business You’re on a deadline If you’re in a time crunch, the lift and shift approach may help expedite the transition to the cloud quicker than other methods You want lower costs A lift and shift migration can provide cost savings compared to more expensive methods such as re-platforming and refactoring. This approach is of minimal risk and is beneficial for workplace operations You want to reduce risk Lift and shift approach is less risky and simpler process when compared to other methods like refactoring or re-platforming When you are choosing options to migrate, you need to look at the larger picture Although the lift and shift technique can work well in many instances, you should consider all options and choose the migration type that will keep you functioning at peak performance By choosing the right IT support firm to assist with the transition, you can mitigate cloud migration challenges to ensure optimal performance and a seamless transition With the lift-and-shift method, on-premise applications can move to the cloud without remodeling. Since they cannot take full advantage of native-cloud features every time, this may not be the most cost-effective migration path Bounce back can be avoided by developing a strategy for cost-allocation and defining roles to monitor how much is spent for cloud
      cards

    Cloud Migration Steps: Ensuring a Smooth Transition

    • First, choose which platform that you wish to migrate to
    • Examine all the connections in and out of the application and its data
    • If you are lifting and shifting more than one application, then you may need to consider automating multiple migrations
    • You should consider containerization to replicate the existing software configurations. This will also allow you to test configurations in the cloud before moving to production
    • Back up the databases from the existing system as well as supporting files. When the new database is ready, restore the backups
    • Once migrated, test the application
    • Check that all the current data compliance and regulatory requirements are running in the new cloud deployment. Run your normal validation tests against the newly migrated application
    • Don’t be tempted to introduce new features during the migration. This can lead to many hours of additional testing to make sure you have not created new bugs
    • Retire your old systems once testing is complete

    Technical Stack

    Google Cloud and Azure are new but still they take advantage of the experience and framework of tech giants namely Microsoft and Google
    AWS is a public cloud, flexible and ready to meet the needs of both big and small applications. Azure’s strong values are perfect integrations with Microsoft 365 ecosystem and focus on enterprise market To help you make an informed choice, we’ve prepared a table that compares the most significant features of AWS, Azure, and GCP  

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Cloud Migration blog"]

    Technologies

    blog-img

    Technologies

  • Oct 21, 2022
  • Ionic vs React Native

    Ionic React and React Native are both excellent options for developing apps, but they have significant differences. We examine the differences in depth and suggest which one your team should use.
    Ionic React and React Native are both excellent options for developing apps, but they have significant differences. We examine the differences in depth and suggest which one your team should use.
    1. The framework & libraries: what pros and cons do I get from the framework or library of choice?
    2. The team: how convenient is the framework for my existing and future team?
    3. The backbone: how reliable, available, and supporting are the creators of the framework?

       1.Which one is more popular?

    Ionic vc React Native npm download

    1. In Ionic The application code can't easily access the native functionalities.
    2. Massive community around the ecosystem. Currently, there are impressive numbers on GitHub repo facebook/react-native. This means that developers are likely to find solutions to the difficulties or issues they are experiencing.
    3. Ability to be integrated into existing native apps.
    4. Application's look and feel as smooth as a native application Reason - React Native is translated to native code, with the benefit of achieving 60 frames per second.
    5. Ionic works with web technologies (HTML, CSS, and JavaScript) and fits well in a team that has no background in the native world.
    6. Every year iOS and Android give OS releases and all these features can be leveraged only in native world.
     
    React Native lonic
    Purpose Learn once, write anywhere Write once, run anywhere
    Language Stack React and JavaScript Web technologies-HTML, CSS, JavaScript, Angular JS, TypeScript
    Nature of apps Cross-platform Hybrid apps
    Developers Facebook Community Drifty.co
    Popular for Native-like and elegant user interfaces across the platforms Using a single code base you can develop an app for iOS, Android, Windows, Web, Desktop, and also PWA (Progressive Web Apps)
    Reusability Of Code The platform-specific code needs to be changed Optimum reusability of code
    Performance Closer native look and comparatively faster Slower than React Native due to WebView
    Code Testing Needs a real mobile device or emulator to test the code Using any browser, the code can be tested
    Learning curve A steep learning curve An easy learning curve due to web technologies, Angular, and TypeScript
    Community and Support Strong and Stable Strong and Stable
    GitHub Stars 66K 34k
    GitHub Contributors 1694 243
    Supported Platforms Android, iOS, UWP Android, iOS, UWP (Universal Windows Platform), and PWA
    Companies Using Facebook, Instagram, UberEATS, Airbnb JustWatch, Untappd, Cryptochange, Nationwide, Pacifica, and many more

    Companies using React Native

      Choose Ionic, if:
    1. You're also planning on building a web or desktop app.
    2. Your development team is most comfortable with web technologies.
    3. Performance optimization isn't critical to your project.

    Conclusion

    Both Ionic React and React Native are great ways for mobile application development. React Native may be a better option for teams targeting iOS and Android only, with more traditional native developers or advanced js developers and an existing repository of native controls. This describes why React Native is so popular among consumer app start-up companies with a background in native app development. Ionic React is a better option for teams with traditional web development skills and libraries who would like to focus on mobile and web (as a Progressive Web App). This explains why Ionic has been so effective with start-ups and enterprise teams with a background in web development. We believe that both developments will exist side by side because they address different requirements in the ecosystem. We are delighted to discuss which platform is best for your team.
     

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    Technologies

  • Oct 06, 2022
  • Jira Integration with GitHub

    The Jira and GitHub integration synchronizes development across tools and leverages automation to eliminate manual steps and reduce delivery time. By integrating GitHub code with Jira projects, developers can focus less on updates and more on creating amazing products.
    The Jira and GitHub integration synchronizes development across tools and leverages automation to eliminate manual steps and reduce delivery time. By integrating GitHub code with Jira projects, developers can focus less on updates and more on creating amazing products.

    OBJECTIVE:

    To configure github with jira through pytest to update results on jira tickets, When Merging a Pull Request the github workflow will be executed, After the workflow execution the status of the jira tickets will be updated as per the result of github workflow execution through pytest

    What is Jira?

    Jira is a web application used as tracking tools for tasks like epic, story, bugs and so on. Jira is available as an open source and paid version.

    Why do we use Jira ?

    It is used for various kinds of projects like business projects, software projects and service projects Applications like Github, slack, jenkins, zendesk etc can be integrated with jira. By using jira a ticket can be created for each type of task to monitor application development,  Here we integrate Github with jira through the pytest framework.

    What is Pytest ?

    Pytest is an automation testing framework in python which is used for testing software applications.

    Why do we use Pytest ?

    Pytest is a python framework, using pytest we can create TDD, BDD as well as Hybrid testing framework used for automation testing like UI, REST API and it is flexible for supporting different actions. Here we are going to execute the test cases that are triggered from the github actions workflow and update the particular jira tickets based on the workflow execution results.

    What is Rest API ?

    REST is abbreviated as (Representational State Transfer) it is an architectural style for interacting between the client and the server, the client sends the request and a response is received from the server in of JSON, XML, or HTML, but json is most commonly used response type because it is readable for both human and machine. Here we interact with the Jira through Rest API, the API Endpoints we are using to interact with Jira is given below rest api

    EXECUTION FLOW OF GITHUB FOR JIRA THROUGH PYTEST

    To update the jira tickets through pytest, we need to know about the Github workflow execution, Jira Rest API endpoints, pytest configurations

    Things we need to know for execution:

    • To create a github workflow file to execute pytest test cases when a PR is merged
    • To configure pytest test cases with jira API endpoints to send the workflow results

    JIRA REST API ENDPOINTS

    Prerequisites for Jira API Integration:

    Steps to create API Token:

    manage acc
    • STEP 3: Click on Security tab and click create and manage API token
    manage api
    • STEP 4: Click on create API Token button:
    create api
    • STEP 5: Provide a label for the token and click create, a new API Token will be generated Copy the token and save the token in a separate file because you cant able to get the same token again

    Encoding the API Token:

    Encoding the Api token can be done in the terminal, to create a base64 encoded token use the following command In LINUX/ mac-os: encoding api In Windows: You can use the link below to encode the api token online https://www.base64encode.org/

    GET Transition ID API:

    • GET:
    https://<JIRA_DOMAIN>.atlassian.net/rest/api/2/issue/<TICKET-ID>/transitions By using this API we can get all the transition details like transition ID transition name The transition ID is default for To-Do, In-progress and Done status, the curl command is given below get transition  
    Transition Status Transition ID
    To-Do 11
    In-Progress 21
    Done 31
    Issue 1 2
    Issue 2 3

    Update Transition Status API:

    Post :

    https://<JIRA_DOMAIN>.atlassian.net/rest/api/2/issue/<TICKET-ID>/transitions This API Endpoint is used to update the transition status of the jira ticket. Ticket ID is passed in the path param and the Transition ID is passed in the body of the request, The status of the ticket will be updated with respect to the transition id, Curl for the following API endpoint is mentioned below, The Transition ID can be obtained by using the Get transition ID API, which is mentioned above update transition

    Add Attachments API:

    Post:

    https://<JIRA_DOMAIN>.atlassian.net/rest/api/2/issue/<TICKET-ID>/attachments This API endpoint is used to add the attachment in a JIRA ticket according to the given Ticket ID and passed file. Use the below curl command add attachmennt

    Search API:

    GET:

    https://<jira_domain>.atlassian.net/rest/api/2/search This API Endpoint is used to get the ticket information using the Jira Query Language (JQL) syntax, the JQL should be passed as an parameter to this API, By using this API we can get the information of all/any of the ticket, An example for JQL to get the ticket information using PR Link which is mentioned in the Github info paragraph field of a jira ticket Example for JQL: example jql

    CONFIGURING GITHUB WITH JIRA:

    There are two ways in configuring github with jira, one is by providing the PR link in a separate field of jira ticket and the other way is by configuring github app in jira

       1. Configuring jira with PR link:

    • We can able to identify the ticket information by providing the PR link in a Jira ticket
    • PR Link should be provided in the custom field of Jira ticket
    • After placing the PR link in custom field, we need to use the Jira Search API endpoint through Jira Query Language(JQL) syntax

       2. Steps to configure PR link in Jira Ticket on custom field:

    • Go to Project Board > Project settings > Issue types
    • Select the Paragraph field type >  Enter the field name and description
    • Click Save changes

       3. Configure github app with jira:

    • To configure Github with jira,Login into Jira, go to Apps➡ Manage Your apps
    github jira
    • Select Github for jira ➡ click connect github organization
    • CLICK Install github for jira on new organization
    • On clicking Install github for jira on new organization select the github organization in which you want to install jira
    • Select repository which you want to configure and click install
    • Now you can see your git repository that have been configured in the github for jira tab

    UPDATING EXECUTION RESULTS TO JIRA TICKET USING PYTEST:

    • All the test cases and the reports report generation for all the test cases are done using pytest
    • After the Workflow execution, the build status and PR link will be added as comments and the reports will be added as attachments to the jira ticket, this is done by the pytest fixture. The pytest fixture is used to execute the conditions before and after the execution of test case, the yield keyword is used to execute the conditions after the execution of all test cases
    update result
    • The teardown module() method calls the Jira API Endpoints for Adding Comments and Attachments.
     

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    Technologies

  • Sep 15, 2022
  • Build APIs in Python Using FastAPI Framework

    FastAPI could be a modern, high-performance, web framework for building APIs with Python language. Good artificial language frameworks make it easy to provide quality products faster.

    FastAPI could be a modern, high-performance, web framework for building APIs with Python language. Good artificial language frameworks make it easy to provide quality products faster. Great frameworks even make the entire development experience enjoyable. FastAPI could be a new Python web framework that’s powerful and enjoyable to use.FastAPI is an ASGI web framework. What this implies is that different requests don’t necessarily sit up for the others before them to end up doing their tasks. Additional requests can do their task completed in no particular order. On the other hand, the WSGI frameworks process requests in a sequential manner.

    ASGI:

    ASGI is structured as one, asynchronous callable. It takes a scope, which could be a dict containing details about the precise connection, sends an asynchronous callable that lets the appliance send event messages to the client, and receives an asynchronous callable that lets the application receive event messages from the client.

    Does FastAPI need Uvicorn?

    The main thing needed to run a FastAPI application in an exceedingly remote server machine is an ASGI server program like Uvicorn.

    Using WSGIMiddleware:

    Need to import WSGIMiddleware.Then wrap the WSGI (e.g. Flask) app with the middleware. Then mount that beneath a path.

    FastAPI Different from other Frameworks:

    Let us walk through a journey of building a CRUD application with FAST API and understand how transactions, persistence/database layer, exception handling, and request/response mapping are done.

    Building a CRUD Application with FastAPI

    Setup:  

    Start by creating a brand new folder to carry your project called "sql_app". create a brand Create and activate a new virtual environment: Next, create the following files and folders for fastapi: Install the following dependencies: In the sql_app/main.py ,and define an entry point for running the fastapi application: In this case, we stated the file to run a
    Uvicorn server. Before starting the server via the entry point file, create a base route in api.py:  

    Difference between Database Models & Pydantic Models:

    FastAPI suggests calling Pydantic models schemas to assist make the excellence clear. Appropriately, let’s put all our database models into a python models.py file and every one of our Pydantic models into a schemas.py file. In doing this, we’ll also have to update database.py and main.py.

    Models.py:

    database.py:

    schema.py:

    FastAPI interactive documentation

    A feature that I like about API is its interactive documentation. FastAPI is based on OpenAPI, which is a set of rules that defines how to describe, create and visualize APIs. OpenAPI needs software, which is Swagger, which is the one that allows us to show the API documented. To access this interactive documentation you simply need to go to “/docs”.

    Structuring of FastAPI:

    By using __init__ everywhere, we are able to access the variables from everywhere in the app, similar to Django.

    Models:

    It is for your database models, by doing this you'll import the identical database session or object from v1 and v2.

    Schemas:

    It is for Pydantic's Settings Management which is extremely useful, you will be ready to use the identical variables without redeclaring it, to work out how it should somewhat be useful for taking a glance at our documentation for Settings and Environment Variables.

    Settings.py:

    It is for Pydantic's Settings Management which is extremely useful, you'll be able to use the identical variables without redeclaring it, to determine how it may well be useful for you take a look at our documentation for Settings and Environment Variables

    Views:

    This is optional if you're visiting render your frontend with Jinja, you'll have something near MVC pattern.

    Core views

    • v1_views.py
    • v2_views.py
    It would look something like this if you wish to feature views.

    Tests:

    It is good to own your tests inside your backend folder.

    APIs:

    Create them independently by APIRouter, rather than gathering all of your APIs inside one file.

    Logging

    It could be a means of tracking events that happen when some software runs. The software’s developer adds logging calls to their code to point out that certain events have occurred. an occasion is described by a descriptive message which might optionally contain variable data (ex. data that's potentially different for every occurrence of the event). Events even have an importance that the developer ascribes to the event; the importance also can be called the amount or severity. Github Link: https://github.com/keerthanakumar-08/FastAPI

    Conclusion

    Modern Python Frameworks and Async capabilities are evolving to support robust implementation of web applications and API endpoints. FAST API is definitely one strong contender. In this blog, we had a quick look at a simple implementation of the FAST API and code structure. Many tech giants like Microsoft, Uber, and Netflix are beginning to adopt. This will result in growing developer maturity and stability of the framework.

    Reference Link: 

    https://fastapi.tiangolo.com/ https://www.netguru.com/blog/python-flask-versus-fastapi

    Agile Delivery Process

    10decoders has a very strong focus on process. We help our clients to capture the requirements in clear process flows and screen design. Understand how our process driven culture helps customer to grow their business

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    Technologies

  • Sep 15, 2022
  • How to use Apache spark with Python?

    Apache Spark is based on the Scala programming language. The Apache Spark community created PySpark to help Python work with Spark.

    Apache Spark is based on the Scala programming language. The Apache Spark community created PySpark to help Python work with Spark. You can use PySpark to work with RDDs in the Python programming language as well. This can be done using a library called Py4j.

    Apache spark:

    Apache spark is an open-source analytics and distributed data processing system for large amounts of data (large-scale datasets). It employs an in-memory caching and an accelerated query execution for quick analytic queries against any size of data. It is faster because it distributes large tasks across multiple nodes and uses RAM to cache and process data instead of using a file system. Data scientists and developers use it to quickly perform ETL jobs on large amounts of data from IoT devices, sensors, and other sources. Spark also has a Python DataFrame API that can read a JSON file into a DataFrame and infer the schema automatically. Spark provides development APIs for Python, Java, Scala, and R. It shares most of its features with PySpark, including Spark SQL, DataFrame, Streaming, MLlib, and Spark Core. We will be looking at PySpark.

    Spark Python:

    Python is well known for its simple syntax and is a high-level language that is simple to learn. Despite its simple syntax, it is also extremely productive. Programmers can do much more with it. Since it provides an easier interface, you don't have to worry about visualizations or Data Science libraries with Python API. The core components of R can be easily ported to Python as well. It is most certainly the preferred programming language for implementing Machine Learning algorithms.

    PySpark :

    Spark is implemented in Scala which runs on JVM. PySpark is a Python-based wrapper on top of the Scala API. PySpark is a Python interface to Apache Spark. It is a Spark Python API that helps you connect Resilient Distributed Datasets (RDDs) to Apache Spark and Python. It not only allows you to write Spark applications using python but also provides the PySpark shell for interactively analyzing your data in a distributed environment.

    PySpark features:

      • Spark SQL brings native SQL support to Spark and simplifies the process of querying data stored in RDDs (Spark's distributed datasets) as well as external sources. Spark SQL makes it easy to blend RDDs and relational tables. By combining these powerful abstractions, developers can easily mix SQL commands querying external data with complex analytics, all within a single application.
     
      • DataFrame A DataFrame is a distributed data collection organized into named columns. It is conceptually equivalent to relational tables with advanced optimization techniques. DataFrame can be built from a variety of sources, including Hive tables, Structured Data files, external databases, and existing RDDs. This API was created with inspiration from DataFrame in R Programming and Pandas in Python for modern Big Data and data science applications.
     
      • Streaming is a Spark API extension that allows data engineers and data scientists to process real-time data from a variety of sources like Kafka and Amazon Kinesis. This processed data can then be distributed to file systems, databases, and live dashboards. Streaming is a fault-tolerant, scalable streaming processing system. It supports both batch and streaming workloads natively.
     
      • Machine Learning Library (MLlib) is a scalable machine learning library made up of widely used learning tools and algorithms, such as dimensionality reduction, collaborative filtering, classification, regression, and clustering. With other Spark components like Spark SQL, Spark streaming, and DataFrames, Spark MLLib works without any issues.
     
      • Spark Core is a general execution engine of Spark and is the foundation upon which all other functionality is built. It offers an RDD (Resilient Distributed Dataset) and supports in-memory computing.

    Setting up PySpark on Linux(Ubuntu)

    Follow the steps below to setup and try pyspark: Please note that python version 3.7 or above is required. Create a new directory. Navigate to the directory. Build and enable a new virtual environment Install spark To check pyspark version

    PySpark shell

    Pyspark comes with an interactive shell. It helps us to test, learn and analyze data in the command line. Launch pyspark shell with command line ‘pyspark’. It launches the pyspark shell and gives you a prompt to interact with Spark in the Python language. To exit from spark shell use exit()

    Create pyspark Dataframe:

    Like in pandas, here also we can create dataframe manually by using these two methods toDF() and createDataFrame(), and also from JSON, CSV, TXT, XML formats by reading from S3, Azure Blob file systems e.t.c. First, create columns and datas

    RDD dataframe:

    An existing RDD is an easy way to manually create a PySpark DataFrame. First, let's create a Spark RDD from a List collection by calling the parallelize() function from the SparkContext. This rdd object is required for all of the following examples. A spark session is an entry point for the spark to access components. To create a Dataframe using toDF() method, we have to build a spark session and then pass the data as an argument to parallelize. Finally, we use “toDF(columns)” to specify column names as in the below code snippets. To createDataframe using createDataFrame() method: We have already created a rdd object with data and a spark session. We can use that object in creating a dataframe. We pass the rdd object as an argument for the createDataFrame() method and use toDF(columns) to specify the column names.

    Kafka and PySpark:

    We are going to use pyspark to produce a stream dataframe to Kafka and consume the stream dataframe. We need kafka and pyspark for the same. We have already setup pyspark in our system, Now we are going to setup kafka in the our system. If you have already setup kafka you can skip this, otherwise you can setup kafka by following these steps: Set up Kafka using Docker compose: Docker Compose is used to run multiple containers as a single service and it works on all environments. Docker Compose files are written YAML files. Now, create docker-compose YAML file named  docker-compose.yml for Kfka. Enter the following and save the file. It will run everything for you via Docker. From the terminal, navigate to a directory containing the docker-compose.yml (which was created in the previous step) and run the below command to start all services: Output Now run the below code to get into docker. It will create a new Bash session in the container kafka. Create Kafka topic named as test_topic by running the below code Exit from container bash session by using bash-5.1# exit command. Now we have set-up Kafka and have created Kafka topic to produce and consume dataframe.

    Produce CSV data to kafka topic, Consume using PySpark :

    Produce CSV data to kafka topic :

    For that we need a CSV. Download or create your own CSV file Install the kafka-python  package in a virtual environment. kafka-Python is a python client for the Apache Kafka distributed stream processing system. With pythonic interfaces, kafka-python is intended to operate similarly to the official java client. In the below code we have configured Kafka producer and created an object with it. In config we have to give info like bootstrap server and value_serializer. serializer instructs on how to turn the key and value objects the user provides with their ProducerRecord into bytes. Now read data from CSV file as dictionary : We have created a producer object and data from CSV, To produce data to kafka, iterate to csv data. Now create a py file named demo_kafkaproducer.py in pysaprk_demo directory. Copy the below code to py file. It will read data from CSV and produce data to Kafka topic. We have produced data to Kafka. Now we are going to consume data stream from Kafka How to read data stream from Kafka topic?   To read the data Stream from the Kafka topic, we have to follow the below steps:  First, set the packages to environment for pysaprk shell, spark stream, and spark sql We have setup the environment. Now we have to create a spark session. SparkSession is the entry point to PySpark. Session will be created using SparkSession.builder. Follow the block of code to create sparksession and read stream dataframe from kafka Now we have consumed stream data from Kafka and created dataframe named as stream_df Below is the block of code to create schema/StructType,

    What is schema/StructType in spark ?

    It defines the structure of the DataFrame. We can define it using StructType, which is a collection of StructFields that define the column name, DataType, column nullability, and metadata. Below code will write the data frame stream on console Output: Now create a py file named demo_kafkaconsumer.py in pysaprk_demo directory. Copy the below code to the py file. It will read stream dataframe from Kafka topic using pyspark, and write dataframe data in console.

    Conclusion :

    One of the popular tools for working with Big data is Spark. It has the PySpark API for Python users.This article covers the basics of data frames, how to install PySpark on Linux, what spark and PySpark features are, and how to manually generate data frames using the toDF() and createDataFrame() functions in the PySpark shell. Due to its functional similarities to pandas and SQL, PySpark is simple to learn and use. Additionally, we look at setting up Kafka, putting data into Kafka, and using PySpark to read data streams from Kafka. I hope you use this information and put it to use in your work.

    Reference Link:

    Apache Spark:
    https://spark.apache.org/docs/latest/api/python/getting_started/install.html Pyspark : https://sparkbyexamples.com/pyspark-tutorial/ Kafka: https://sparkbyexamples.com/spark/spark-streaming-with-kafka/

    blog-img

    Technologies

  • Sep 14, 2022
  • Resemblance and Explanation of Golang vs Python

    Everyone has been looking for the best programming language to use when creating software and also there has recently been a battle between Golang and Python.

    Everyone has been looking for the best programming language to use when creating software and also there has recently been a battle between Golang and Python. I was contemplating which would be the better. Then I learned that Go was created and released in 2009, but it gained popularity quickly in comparison to Python. Both Golang and Python are general-purpose programming languages used to create web applications. These two appear to be very different. In this article, we will look at a comparison of these two languages.

    Golang

    Golang is a procedural, compiled, and statically typed programming language(syntax similar to C). It was developed in 2007 by Ken Thompson, Robert Griesemer, and Rob Pike at Google but launched in 2009 as an open-source programming language. This language is designed for networking and infrastructure-related applications. While it is similar to C, it adds a variety of next-gen features such as Garbage collection, Structural typing, and Memory management. Go is much faster than many other programming languages. Kubernetes, Docker, and Prometheus are written in it. (developed using this language or written in it)

    Features of Golang

    Simplicity

    The developers of the Go language focus on credibility, readability, and maintainability by incorporating only the essential attributes of the language. So we can avoid any kind of language complications resulting from the addition of complex traits.

    Robust standard Library

    It has a strong set of library packages, making it simple to compose our code.

    Web application building

    This language has garnered as a web application building language owing to its easy constructs and more agile execution speed.

    Concurrency

    • Go deals with Goroutines and channels. 
    • Concurrency effectively makes use of the multiprocessor architecture.
    • Concurrency also helps huge programs scale more consistently.
    • Some notable examples of projects written in Go are Docker, Hugo, Kubernetes, and Dropbox.

    Speed of Compilation

    • Go offers a much more powerful speed of completion and compilation than several other popular programming languages.
    • Go is readily parsable without a symbol table.

    Testing support

    • The "go test" command in Go allows users to test their code written in '*_test.go' files.

    Pros:

    • Ease to use - Go’s core resembles C/C++, so experienced programmers can pick up the basics fast, and Simple syntax is easy to understand and learn
    • Cross-platform development opportunities - Go can be used with various platforms like UNIX, Linux, Windows, and Other Operating systems, and Mobile devices also.
    • Faster compilation and execution - Go is a compiler-based language so it completely reads the code and executes due to this it executes faster than c,c++, and java.
    • Concurrent - Run various processes together and effectively

    Cons:

    • Still developing - Still in development
    • Absence of GUI Library - There is no native support
    • Poor Error handling - The built-in errors in Go don't have stack traces and don't support the usual try/catch handling techniques.
    • Lack of frameworks - Minimal amount of frameworks
    • No OOPS Support
    Here is the simple "Hello World" programme in the Go language.

    Output:

    Let's discuss the above program,
    • package main - Every Go program begins with code inside the package main
    • Import “fmt” - its an I/O function.
    • func main - This function always needs to be placed in the main package.{} Here we can write our code/logic.
    • fmt.Println - Print function, print the text on the screen.

    Why Go?

    • It's a statically strongly typed programming language with a great way to handle errors.
    • It allows using static linking to combine all dependency libraries and modules into one single binary file based on the type of the OS and architecture.
    • This language performs more efficiently because of its CPU scalability and concurrency model.
    • This language offers support for multiple libraries and tools, so it does not require any 3rd party libraries.
    Frameworks for Web Development: Gin, Beego, Iris, Echo, and Fiber

    Python

    Python is a universal, high quality and very popular programming language. Python was introduced and developed by Guido van Rossum in the year of 1991. Python is used in machine learning applications, data science, web development, and all modern software technologies. Python has an easy-to-learn syntax that improves readability and reduces program maintenance costs. Python code is interpreted when it is converted to machine language at run time. It is the most widely used programming language because of its tightly typed and dynamic characteristics. Python was originally used for trivial projects and is known as a "scripting language". Instagram, Google, and Spotify use Python and its frameworks.

    Features of Python

    • Free and open source
    It's free and open source, which means the source code is available to the public. So we easily download and use it
    • Easy to code
    Python is beginner-friendly because it prioritises readability, making it easier to understand and use. Its syntax is similar to the English language, making it simple for new programmers to enter the development world.
    • Object-oriented programming
    OOPS is one of the essential features of Python. Python supports the concepts of classes, objects, encapsulation, and object-oriented language.
    • GUI Programming support
    A graphical user interface can be developed by using modules such as PyQt5, PyQt4,wxPython, or Tk in python.
    • Extensible and portable
        • Python is an extensible language.
        • We can formulate some Python code into the C or C++ language.
        • Furthermore, we can compile that code in the C or C++ language.
        • Python is also a very portable language.
        • If we have Python code for Windows and want to run it on platforms such as Unix, Linux, and Mac, we do not need to change it. This code is platform-independent.
    • Interpreted and High-level language
        •  Python is a high-end language.
        • When we formulate programs in Python, there is no need to remember the system architecture, nor do we need to manage the memory.
        • Like in other programming languages, there is no requirement to compile Python code, making it easy to debug our code.
        • Python's source code is converted to an instantaneous form known as bytecode. Python is classified as an interpreted language because Python code is executed line by line.
     

    Pros:

    • Simple syntax: Easy to read and understand
    • Larger Community support: Python community is vast
    • Dynamically typed: The variable type is not required to be declared.
    • Auto memory management: Memory allocation and deallocation methods in Python are automatic because the Python developers created a garbage collector for Python so that the user does not have to manually collect garbage.
    • Embeddable:  Python can be used in embedded systems
    • Vast library support:  Lots of Libraries are available. For Example, TensorFlow, Opencv, Apache spark, Requests and Pytorch etc.,

    Cons:

    • Slow speed
    Python is an interpreted language, so the code will be executed line by line, which often results in slow execution
    • Not Memory Efficient
    Python's auto-memory management makes it unsuitable for memory-intensive tasks. Because of the flexibility of the data types, memory consumption is high.
    • Weak in mobile computing
    Python is typically used for server-side programming. It is not used in the development of client-side or mobile applications. because it is inefficient in terms of memory and processing speed.
    • Runtime errors
    Because Python uses dynamic typing, the data type of a variable can change at any time. In the future, a string could be stored in an integer number variable, causing runtime issues.
    • Poor database access 
    Database access is limited in Python. When compared to popular technologies such as JDBC and ODBC, Python's database access layer is found to be somewhat underdeveloped and primitive. It cannot, however, be used in enterprises that require the smooth interaction of complex legacy data.   Here is a simple "Hello World" programme written in Python.

    Why Python?

    Python is platform-independent; it runs on (Windows, Mac, Linux, Raspberry Pi, etc.). Python has a simple syntax that is related to that of the English language. Python's syntax allows programmers to write programmes with fewer lines than in other programming languages. Python is an interpreter-based language. As a result, prototyping can be completed quickly. Python can be processed as procedural, object-oriented, or functional. Frameworks for Web Development: Django, Flask, Fastapi, Bottle, etc.

    Comparison of Go vs Python:

     

    Case studies:

    Concurrency:

    Concurrency is the concept of multiple computations happening at the same time. Concurrency is well supported in Go via goroutines and channels. A goroutine is a function that can run alongside other functions. Channels allow two goroutines to communicate with each other and synchronise their execution.

    Output:

    Concurrency is the main advantage in Go compared to Python. Because Python is unsuitable for CPU-bound concurrent programming. In python, we use the Multiprocessing concept to achieve concurrency.

    Exception Handling :

    Output :

      Python supports exception handling, but Go doesn't.  

    Go vs Python: Which is Better?

    When it comes to productivity, Golang is the best language to learn to become a more productive programmer. The syntax is restricted, and the libraries are much lighter because there is less code to write; tasks can be completed in fewer lines of code. Python consists of a large number of packages and libraries. Python has the advantage in terms of versatility due solely to the number of libraries and syntax options. However, flexibility comes at a cost, and that cost is productivity. Which language is more productive in this Python vs Golang battle? The winner is Golang, which is designed to be more productive, easier to debug, and, most importantly, easier to read. Python is without a doubt the most popular choice for developers looking to create a machine learning model. The reason for this is that Python is the most popular language for machine learning and is the home of TensorFlow, a deep learning framework built on Python. Learning a programming language like Python, which almost resembles pseudo-code, is an added benefit that makes learning easier. On the other hand, Golang is super fast, and effortless to write and comes along with Go doc, which creates documentation automatically, making the life of the programmer easier.

    Conclusion

    Python and Golang are winners in their respective areas depending on the specific capabilities and underlying design principles of the language

    1.Maturity

    It's difficult to make conclusions about Go vs Python because comparing a mature language to a young one doesn't seem fair. Python may be the winner here

    2.In ML and Data science Usage

    Python is the leading language not only for machine learning and data analysis but also for web development. Golang has only been around for a decade, and it has yet to establish a robust ecosystem or community.

    3.Performance

    The main advantage of Go is speed. However, Python is slow when it comes to code execution.

    4.Microservices and Future Readiness

    When it comes to microservices, APIs, and other fast-loading features, Golang is better than Python. Go is equipped to be a future-ready web development framework with a lot of adoption around the world of containers.

    Referral Link:

    Python -
    https://docs.python.org/3/ Go - https://go.dev/doc/
     

    blog-img

    Technologies

  • Sep 08, 2022
  • Flask vs FastAPI – A Comparison Guide to Assist You Make a Better Decision

    Flask and FastAPI are python-based micro-frameworks for developing small-scale data science and machine learning web and apps.
    Flask and FastAPI are python-based micro-frameworks for developing small-scale data science and machine learning web and apps. Despite the fact that FastAPI is a relatively new framework, an increasing number of developers are using it in their new projects. Is it just a marketing ploy, or is FastAPI better than Flask? We've put together a comparison of the major pros and cons of Flask and FastAPI to assist you in deciding which will be the ideal choice for your next data science project.

    What is Flask?

    Flask is a micro web framework written in python. Armin Ronacher came up with the idea.  Flask is built on the WSGI (Web Server Gateway Interface) Werkzeug toolkit (For the implementation of  Request and Response) and the Jinja2 (template engine). WSGI is a standard for web application development.  It is used to build small-scale web applications and Rest API Flask's framework is more explicit than Django's framework, and it is also easier to learn because it requires less basic code to construct a simple web application.  

    In this real-world top Companies are using Flask

    flask-microframework

    What makes Flask special?

    • Lightweight Extensible  Framework.
    • Integrated unit test support.
    • Provided development server and debugger.
    • Uses Jinja templating.
    • Restful request handling.

    When should you use a Flask?

    • Flask is old and it has Good Community support
    • For Developing web applications and creating a quick Prototype.

    Flask Web Application Development

    1. Creation of a virtual environment
    1. The venv environment is being restarted.
    1. Database.
    1. Login and register for several users
    • Mode Debug
    • Creating a User Profile Page
    • Creating an avatar
    1. Handling errors
      1. Virtual environment creation environment-creation 2. Making Necessary Installation necessary-install

    Build a sample webpage using Flask, it will return the string

    webpage-flask After Running the application, we need to visit
    http://127.0.0.1:5000/ application

    Pros

    • Flask has a built-in development server, integrated support, and other features.
    • Flask Provides integrated support for unit tests.
    • Flask Uses Jinja2 templates.
    • Flask is just a collection of libraries and modules that helps developers to write their applications free without worrying about low-level details like   Protocols and Thread Management.
    • Because of its simplicity, Flask is particularly beginner-friendly, allowing developers to learn easier.  It also allows developers to construct apps quickly and easily.

    Cons

    • Flask makes use of Modules, which is third-party participation that might lead to security breaches. Modules are the intermediary between the framework and the developer.
    • Flask does not create automatic documentation;  They need several extensions like Flasgger and Flask RESTX  and also require additional setup.
    • Flask has a single source, which suggests that it will handle each request one by one, therefore regardless of how many multiple requests there are, it will still take them in turns, which takes extra time.
     

    What is FastAPI:

    FastAPI is built in ASGI (Asynchronous Server Gateway Interface) and pydantic, Starlette. This framework is used for building a web application and RestAPI. In FastAPI we need uvicorn to run the server. There is no built-in development server So the ASGI server Uvicorn is required to run the FastAPI application. The best thing that we Highlight in the FastAPI is documentation. It will generate documentation and create Swagger UI. which helps the developers to test endpoints effectively. In fast API, Also includes data validation and returns an Explanation of the error when the user enters the invalid data. It implements all of the OpenAI requirements and Swagger for these specifications. As a developer we will concentrate on developing logic; the rest is handled by the FastAPI. what-is-fastapi In this modern world, the top Websites are moving to FastAPI. The website was developed using FastAPI. developed-fastapi

    When should you use a FastAPI?

    • Has Good speed and performance when compared with Flask.
    • Decreasing bugs and Errors in code.
    • It Generates  Automatic documentation
    • Built-in data validation.

    What makes FastAPI special?

    • Fast Development
    • Fewer Bugs
    • High and Fast Performance
    • Automatic swagger UI
    • Data validation
      1. Virtual environment creation environment-creation 2. Making Necessary Installation necessary-install Build a webpage using FastAPI, It return string webpage-fastapi After running the application, we need to visit http://127.0.0.1:8000/docs or http://127.0.0.1:8000/redoc   Docs fastapi Redoc Redoc

    Pros

    • FastAPI is considered as one of the fastest Framework in python, It has an native async support and provides a simple and easy-to-use dependency injection framework. Another advantage to consider is built-in data validation and Have Interactive API documentation support .
    • Dependency Injection support
    • Fast API is based on standards such as JSON Schema (a tool for validating the structure of JSON data), OAuth 2.0 (an industry standard protocol for authorization), and OpenAPI (an open application programming interface).

    Cons

    • In FastAPI there is insufficient Security and also it will support OAuth.
    • Because FastAPI is relatively new, the community is small compared to other frameworks, and regardless of its detailed documentation, there are very few external educational materials.

    Difference between Flask and FastAPI:

    Both offer the same features but the implementation is different. The main difference between Flask and FastAPI is that Flask is built in WSGI (Web Server Gateway Interface) and FastAPI is built in ASGI(Asynchronous Gateway Interface). So, the FastAPI will support concurrency and asynchronous codes. In FastAPI there is automatic documentation for Swagger UI(docs and redocs), But in Flask we need to add some extensions like Flasgger or Flask RESTX and some dependencies setup. Unlike Flask, FastAPI provides data validation for defining a specific data type and it will raise an Error if the user enters an invalid data type. performance-table

    Performance:

    FastAPI uses an Async library which is helpful to write concurrent code. Async is greatly helpful for doing tasks that involve something like fetching data from API and querying from a database, reading the content of the file and FastAPI has ASGI whereas Flask is a WSGI Application

    Data Validation:

    There is no data validation in Flask. So Flask allows any kind of data type. In Flask the data validation will be handled by developers. But In FastAPI there is inbuilt data validation (pydantic). So it will raise an error when it gets an invalid data type from the user. This is useful for developers to interact with the API endpoints.

    Documentation:

    Flask doesn’t have any inbuilt documentation for swagger UI. We need to add some extensions like Flassger and Flask-RESTEX and some dependency setups. But In FastAPI it generates an automatic swagger UI when the API is created. For accessing the auto-generated swagger UI hit the endpoint with /docs or /redoc. It will show all the endpoints in your application.  

    HTTP METHODS:

    Flask FastAPI
    @app.route("/get", methods= ['GET']) @app.get('/get', tags=['sample'])
     

    Production Server

    At some point, you’ll want to deploy your application and show it to the world.
    • Flask
    Flask makes advantage of WSGI, which stands for Web Server Gateway Interface. The disadvantage is that it is synchronous. This means that if you have a large number of requests, they will have to wait in line for the queue to finish.
    • FastAPI
    FastAPI is an ASGI (Asynchronous Server Gateway Interface), web server, which is lightning fast because it is Asynchronous. So, if you have a lot of requests, they don't have to wait for the others to finish before being processed.

    Asynchronous Tasks

    • Flask
    In Flask Async can be performed by thread or multiprocessing or use some tools like celery, Create await/async for handling routes

    Installations

    flask-install

    Example:

    example tasks

    FastAPI:

    In FastAPI there is a default AsyncIO. So we can simply add the async keyword before the function. fastapi-async

    FastAPI was Built with Primary concerns

    • Speed and Developer Experience
    • Open Standards.
    1. FastAPI can connect Starlette, Pydantic, OpenAPI, and JSON Schema.
    2. FastAPI uses Pydantic for data validation and Starlette for tooling making it twice as fast as Flask and equivalent to high-speed web APIs written in Node or Go.
    3. Starlette + Uvicorn supports async requests, while Flask does not.
    4. Data validation, serialization and deserialization (for API development), and automatic documentation are all included (via JSON Schema and OpenAPI).
     

    Which Framework is Best for AI/ML

    Both Flask and FastAPI are the popular Framework for developing Machine learning and web applications. But most data scientists and Machine learning developers prefer Flask. Flask is the primary choice of Machine learning developers for writing the API’s . A few disadvantages of using Flask is time consuming for running the big applications. The major disadvantage in flask is to add more dependencies by adding plugins and the other one is lack of Async support whereas FastAPI supports Async by default . FastAPI is used for the creation of ML instances and applications. In the machine learning community Flask is one of the popular frameworks.Flask is perfect for ML engineers who want to create web models. FastAPI, on the other hand, is the best bet for a framework that provides both speed and scalability.  

    Migrating Flask TO FastAPI :

    migration

    Yes, It is possible to migrate a Flask application to FastAPI. In FastAPI there is native async support. Flask also supports Async but is not as extensive as FastAPI. There is some syntactical difference between Flask and FastAPI.  

    The Application object in Flask and FastAPI is

    object-flask-fastapi

    Simple Example for Migrate Flask to FastAPI:

    • Flask Application
    migrate-fastapi  

    1.To Migrate the Flask to FastAPI we need to install and import libraries.

     

    fastapi-install

     

    2. URL Parameters (/basic_api/employees/)

     

    url-parameter

    In FastAPI the request methods are defined in the methods FastAPI objects. For Example @app.get, @app.post, @app.put.  

    The Request Methods in Flask and FastAPI is

    method-flask-fastapi Here in the put request route, we are passing a body as an Employee object. And also we will create a new class called Employee and inherit it from the base model. And pass the type of the URL parameter employee_id within the route, instead of that pass the type of the parameter in employee_get()  

    Query Parameters:

      Like URL Parameters, Query parameters are also used for managing the state(For sorting or Filtering).  
    • Flask

    query-flask
    • FastAPI

    query-fastapi  

    Run the server in Flask And FastAPI

      Main (Flask) server-flask Main (FastAPI) server-fastapi  

    And Finally the FastAPI Application looks like :

     
    • FastAPI Application
    fastapi-application Use ASGI Application web server Uvicorn to run the FastAPI application (uvicorn.run(app)).  

    When Should you choose FastAPI instead of Flask and Django?

    • Native Async Support:The FastAPI web framework was created using the ASGI web server. Native asynchronous support eliminates inference latency.
    • Improved latency: As a high-performance framework, the framework's total latency is lower when compared to Flask and Django.
    • Production-ready:With the FastAPI web framework's auto validation and short defaults, developers may easily design web apps without rewriting the code.
    • High Performance: Developers have access to the key functionalities of Starlette and Pydantic because they are compatible. Needless to say, Pydantic is one of the quickest libraries, and as a result, overall speed improves, making FastAPI the preferred library for web development.
    • Learn Simple:This is a minimalist framework so it is easy to understand and learn.
     

    Flask Or FastAPI: Which is better

     
    S.No Flask FastAPI
    1. Flask is a micro web framework to develop small-scale web applications and Rest API. Flask is depends on WSGI toolkit (werkzeug, Jinja2) FastAPI is considered one of the Fastest frameworks compared to the flask. FastAPI is built in Pydantic and starlette.
    2. Flask is built in Web Server Gateway Interface(WSGI) FastAPI is built in Asynchronous Server Gateway Interface(ASGI)
    3. It does not have any inbuilt documentation such as swagger UI and needs to add some extensions like Flasgger or Flask RESTX. In FastAPI it has inbuilt documentation like (docs and redocs).
    4. There is no Inbuilt data validation in Flask, we need to define the data type in requests. In FastApI there is an Inbuilt data validation that will raise the error if the user provides an invalid data type.
    5. Flask is more flexible than Other frameworks. FastAPI is flexible in code standards and it does not restrict the code layouts.
     

    Conclusion:

    After learning about both Flask and FastAPI. Both are used to create a Web application and Rest API. But FastAPI is better when compared with Flask. Because FastAPI has a native ASGI support (Asynchronous Server Gateway Interface). So it is Faster and High in performance. Also, it has inbuilt documentation(Swagger UI) and data validation. FastAPI has High and Fast performance, Efficiency and it's easy to understand and learn. When compared to Flask, FastAPI has less community support but it reaches a lot in a short period of time.  

    Reference link:

    Flask: https://flask.palletsprojects.com/en/2.2.x/
    FastAPI: https://fastapi.tiangolo.com/

    blog-img

    Technologies

  • Aug 13, 2021
  • Why and when choose custom Software development?

    Custom software development is the process of designing, developing, deploying and maintaining software for a certain set of Users or a specific Organization. Any software will meet the generalized need of the end-users

    Introduction

    Custom software development is the process of designing, developing, deploying, and maintaining software for a certain set of Users or a specific Organization. Any software will meet the generalized need of the end-users. The existing software may not address all the needs of the Organization. In such a case they move in for customization of the existing software. Customized solutions are developed to meet the needs of the User

    Overview of market share

    Custom Software Development Services Market is huge and is growing at a moderate speed with substantial growth rates over the last few years and is estimated that the market will grow significantly in the next few years. The Custom Software Development Services Market is driven by the growing requirements for customized software among Organizations. Moreover, organizations are always looking for reducing long-term costs. Custom software development is becoming popular among organizations that are largely looking for scaling up of their business operations. A holistic evaluation report of the market is provided by the Global custom software development services market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, competitive landscape, and factors that are playing a substantial role in the market.

    How custom software development process Works

    The process followed in custom software development is same as SDLC. It starts with Planning and Analysis followed by Design, Development, Testing, and finally maintenance of the completed product. The main goal of planning and analysis is to collect as much data as possible. The design transforms the requirements into a detailed system design requirements document. It is like a blueprint for the solution which is used for developing the code. Developing code is the actual implementation phase, which is followed by rigorous testing. Testing is done until all issues are identified and resolved. Finally, the product is deployed into the live environment. And the product gets into the maintenance phase.

    soft-process

    Reason to choose custom software development

    Generally, developing an application from scratch is a complex and time-consuming process. If there is not much time and a solution needs to be implemented as quickly as possible, then custom software development would be a better choice. The next factor to be considered is software development cost. Ready-to-use applications can save the budget if they provide the desired functions and match the standard requirements and do not need any customization. In case the ready-to-use application can’t meet the demands of all kinds and the development team needs to handle complex processes and comply with high security and industry regulations then a custom software development process would be the best option.

    What are the Benefits of the Custom Software development process

    Some of the benefits of the custom software development process

    Uniqueness

    One of the important benefits of custom applications is uniqueness. Tailored solutions are built to fit the user’s specifications. A development team experienced in custom software development help to deliver a solution that will include the features requested.

    Flexibility & Scalability

    Regular software cannot be manipulated and it will remain constant. It will become unsuitable to keep using it. But custom software can be scaled according to the needs of the company and easily integrated with business. So the user need not change according to the application but the application can be changed according to the user.

    Cost effectiveness

    Readily available software might be less expensive but it might have some recurring costs which will make it less beneficial. They might also lack some critical functionality. In such cases developing a product from scratch might cost more. When existing software is customized, a huge sum of money need not be invested.

    Security

    While customizing or developing software, the important feature that needs to be handled is security When an organization needs to support expensive security protocols, it might be an add-on cost to them. But with customized software, they can decide about the security technology to be used and choose one which is ideal for their business.

    Team Capabilities

    Team experience and technical skills A software team with strong technical skills, in-depth knowledge of the latest technologies, and experience with multiple companies need to be considered for customizing software.

    Cost Structure

    When a third party is hired for customizing software, it should be ensured that they give a clear picture of all the costs involved and do not keep the costs hidden.

    Communication Skills

    The custom software development team should be strong in communication skills. Their strong communication skills will help them to understand the details of the unique requirements needed by the client. When they have a clear understanding, they can carefully design and develop software with accuracy.

    Why choose 10Decoders for custom software development?

    • 10Decoders team has worked on customizing multiple types of applications for many clients.
    • We have also tried and tested various methodologies for successful completion.
    •  Also, we work with highly secured and safe systems. So your data will be protected in our hands.
    • Depending on the complexity of Customization our charges are reasonable. And we do not have any hidden costs.
    • We have Engineers who are highly skilled in multiple technologies, who can readily work on customizing your needs.

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="custom software development blog"]

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    Technologies

  • Aug 13, 2021
  • Voice Enabled Banking and Chatbots with Dialogflow

    Banking chatbots generate better results and superior customer experiences for the banking industry and other financial institutions

    Introduction

    Banking chatbots generate better results and superior customer experiences for the banking industry and other financial institutions. They help the customers in multiple ways like getting account balances, to apply for loan or credit card, transfer funds, pay bills, or to update the profile details. Regular customer interactions can be automated partially or fully using a banking chatbot which is available 24/7. A voice enabled

    What is Chatbot?

    chatbot is a variation of a conversational AI solution. It leverages NLP combined with speech-to-text(self-developed or already existing platforms) and automates speech recognition to deliver resolution immediately. Voice Assistants can either be a complete voice-based model or as a multimodal chatbot supporting both text and voice

    What is Dialogflow?

    Dialogflow is a natural language understanding platform used to design and integrate a conversational user interface into mobile apps, web applications, devices, bots, interactive voice response systems, and related uses

    dialogflow

    Overview of Market Share

    The global chatbot market size was estimated at USD 430.9 million in 2020. The growth is expected to be driven by the increasing adoption of customer service activities among enterprises to reduce operating costs. A chatbot is an interactive application developed using either a set of rules or artificial intelligence technology. A chatbot is basically developed using AI technology or a set of rules. It is designed in such a way that it can interact with humans through text. To assists users in various sectors, it is integrated with other messaging services. Various innovative ideas are implemented in Machine Learning (ML) and Artificial Intelligence (AI) technologies which will enhance the features of chatbots, which, in turn, will create greater demand for chatbots. Since businesses are looking for ways to automate their sales and other services Chatbots are becoming popular. This helps the organizations to stick to the schedule at reduced cost.

    How do Chatbots work?

    1. 1A user sends a text/voice message to a device or an App
    2. The App/Device transfers the message to Dialogflow( via detecting API )
    3. The message is categorized and matched to a corresponding intent (Intents are defined manually by developers in Dialogflow)
    4. We define the following actions for each intent in the fulfillment (Webhook)
    5. When a certain intent is found by Dialogflow, the webhook will use external APIs to find a response in external databases
    6. The external databases send back the required information to the webhook
    7. Webhook sends a formatted response to the intent
    8. Intent generates actionable data according to different channels
    9. The actionable data go to output Apps/Devices
    10. The user gets a text/image/voice response

    chatbots-work

    How to build your first Chatbots?

    Agent: An agent is merely another term used to refer to the chatbot. While using Dialogflow, you will find that many people start off by asking you to ‘name the agent.’ This just means giving your chatbot a name, so even in this context, it's one and the same Intent – ‘Intents’ are how a chatbot understands Expressions Responses: This is the chatbot’s output that is aimed at satisfying the user’s intent Entities: ‘Entities’ are Dialogflow’s mechanism. It helps to identify and extract useful data from the natural language inputs given by user. Actions & Parameters are also Dialogflow mechanisms Actions & Parameters These too, are Dialogflow mechanisms. They serve as a method to identify/annotate the keywords/values in the training phrases by connecting them with Entities We will see how to create a chatbot in Dialogflow using the following

    Step1: Login with DialogFlow Account

    1. Go to https://dialogflow.cloud.google.com
    2. Click ‘Go to console’ in the top right corner
    3. Login with a Gmail account

    Step2: Create a new Agent

    1. Start off by clicking ‘Create Agent’ in the column menu to your left
    2. Give your Bot a name! We’re going to call ours a ‘Testing’
    3. Be sure to select your time zone and language as required
    4. Click ‘Create’

    Step3: Create a new Intent

    1. Click “Intent” on the left side
    2. Add the Intent Name and Training Phrases
    3. If you have already created Entity, Please mark the entity for the corresponding questions. Here I have created one entity as “Cheque” and marked that keyword to that training phrasecheque
    4. After that, we need to add the response in the Intent
    5. Click “Save” in Intent

    Step4: Check Question

    We are able to check the questions on the right side of the top corner and it will give the intent name, Entity name and answer also

    Best features

    Some best features are given below
    1. Self Service Customer Support Self Service via a voice bot is more scalable and customer-centric. Giving your customers a voice bot as the first mode of communication can help them resolve their queries faster and for major queries, the AI-enabled voice bot can transfer the call or the message to the right agent
    2. Zero Wait Time Calling any customer support center can be a nightmare for most people, basically, because of the wait time and redirections. Enabling FAQs on automating general queries on IVR, Alexa or Google Assistant can save a lot of time and the agent can take over or the call can be transferred to the agent only for critical issues
    3. 24/7 Availability Humans require rest, but machines do not. Even if your agent is not available, the voice bots can resolve the queries for your customers and take their details in case of urgent queries. And your agent can contact them at their earliest convenience
    4. Break from Monotonous Texts Provide a multimodal Intelligent Virtual assistant supporting both chat and voice, rather than just a text-based chatbot. Just a text-based chatbot requires a lot of patience, and time from the user’s end. And also sometimes it becomes difficult to understand voiceless messages as it lacks sentiments. AI-enabled voice bot is highly automated, intelligent, and customer-friendly; making it a need of the hour for brand-customer engagement platforms
    5. No human contact Pandemic made it really clear the need for an automated customer support system, as most customer support offices were closed down. Many businesses and banking institutions were seen adopting IVR support for resolving customer queries like Kotak, ICICI, etc
    6. Save Cost An automated AI-enabled voice bot increases your team’s productivity, by taking care of all repetitive queries. Your team can just focus on critical queries, thus saving a lot of time and money for your business
    7. Increased Productivity Using voice bots, your customers can handle multiple tasks simultaneously, and in one call. Customers can schedule appointments, organize and modify meetings, check balance, do transactions, get account details, set reminders, etc

    Tech Stack and Team Capabilities

    A company can use Dialogflow to create messaging bots that respond to customer queries in platforms like Alexa Voice Services (AVS), Google Assistant, Facebook Messenger, Slack, Twitter, Skype, Twilio, Telegram, and several other messaging integrations. Dialogflow can be integrated into WhatsApp, too

    Other chatbot platforms

    • Google Dialogflow
    • Amazon Lex
    • IBM Watson Assistant
    • Facebook’s Wit.ai
    • Microsoft Azure Bot Service

    Programming Language support

    Dialogflow supports the following programming languages c#, Go, Java, Node.js, PHP, Python, and Ruby Choosing NodeJS is clearly a straightforward choice because NodeJS is asynchronous

    Platform case study with a link

    You can browse the sample code about Dialogflow integration from Google at GitHub with the links below
    Language Links
    C# GoogleCloudPlatform/dotnet-docs-samples/
    Go GoogleCloudPlatform/golang-samples
    Java googleapis/java-dialogflow
    Node.js googleapis/nodejs-dialogflow
    PHP GoogleCloudPlatform/php-docs-samples
    Python googleapis/python-dialogflow
    Ruby googleapis/google-cloud-ruby

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Remote Monitoring by Doctors blog"]

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    Technologies

  • Aug 12, 2021
  • Mobile Application Development Frameworks in 2021

    Mobile apps have already become a vital part of our daily lives. Whether you want to go for a ride or book a movie ticket or virtually connect with your favorite ones, etc

    Introduction

    Right from booking a movie ticket to go on a ride or to virtually connect with your loves ones, we use the respective app in smart phone. Due to the development in technology everything is in our finger tips. Now many frameworks are available for developing mobile applications. This framework is classified into three types – Web apps, Native apps and Hybrid apps. Brief overview of these categories are given below
    • Native Apps: A Native App is an application that is specifically designed for a particular platform or device
    • Web Apps: A Web App is designed to deliver web pages on different web platforms for any device
    • Hybrid Apps: A Hybrid App is a combination of both native & web applications. It can be developed for any platform from a single code base

    Overview of market share

    By 2025, the Mobile Application Development Platform market may reach $20.7 billion at a CAGR of 21.7% during the period 2021-2025. Nowadays many organizations are using mobile technology for better management of their business functions. This has increased the demand for mobile application development platforms. The rising use of mobile devices by organizations, growing adoption of bringing your own device (BYOD) trend, and adoption of cloud technology drive the mobile application development platform market. In addition, the need for automation in mobile application development and favorable government initiatives for digitalization in emerging countries are analyzed to drive the market in the forecast period 2020-2025

    What are the best features to have

    React Native

    React Native is the best JavaScript library to build native applications for all devices and platforms. With React Native, React Native can be used to develop applications for both iOS and Android. It also allows creating platform-specific versions of various components allowing easy use of a single codebase across multiple platforms

    Some of the React Native features are

    • Low-code
    • Compatible third-party plugins
    • Declarative API for predictive UI
    • Supports iOS and Android

    Why Choose React Native?

    • Cross-Platform Functionality
    • Cost-Effective Development
    • Third-Party Plugins
    • Handy Libraries
    • Allows Code Reusability
    • Most Popular Framework
    • Used Advanced JavaScript
    • Assures High-Performing App

    Developer’s tools

    • Emulator, SDK, Android Studio
    • JS Editor
    • Xcode and also needs a $100/year developer’s account for the development and publishing of apps

    Flutter

    Flutter is a UI toolkit by Google to help in building native applications for the web, mobile, and desktop. This UI toolkit is featured with fully customized widgets, which supports creating native applications in a short period. Besides, Flutter’s layered architecture ensures a faster rendering of components. Some of the striking Flutter features are
    • Built-in material design
    • Built-in Cupertino (iOS-flavor) widgets
    • Rich motion APIs
    • Supports both iOS & Android
    • Strong widget support
    • High-performance application

    Why Choose Flutter?

    • Single Codebase for Multiplatforms
    • Powerful UI Experiences
    • Less Development Time
    • Customizable Experience
    • Platform-Specific Logic Implementation
    • Native-Alike Performance
    • Perfect for MVP

    Developer’s tools

    • Emacs
    • Android Studio
    • VS Code

    Swiftic

    Swiftic is one of the best mobile app development frameworks available on the iOS platform. It is featured with an easily navigable interface

    Some of the significant features are

    • Interesting push notification
    • Become a loyal shopper with a loyalty card
    • Build your mobile store
    • In-app coupons
    • Use scratch cards to win prizes
    • Easy Communication
    • Menu & Ordering
    • Customer Engagement
    • App Promotion
    • Social & Media Feeds
    • App Publication Assistance
    • Advanced Analytics
    • Third-party integration

    sign-fearture

    Native Android Development

    It is featured with an easily navigable interface Android development gives you the maximum flexibility in terms of creating a custom complicated design with sophisticated animations and transitions, using the hardware features of the device like microphone, camera and sensors. Native apps are usually created with Java, Kotlin, or C++ languages. You can however use some other languages like Scala and even Swift, but it will require additional third-party tooling

    Java / Kotlin

    Java is often used by developers for developing native android development. Kotlin is a new programming language which is being used for android app development in the recent years. Because of its interoperability with Java and its simpler syntax, it is used for native Android app development. Kotlin’s lesser code helps in faster development. Kotlin’s code is run the same way as Java as it uses Java virtual Machine Kotlin is used for native Android app development because of its simpler syntax and its interoperability with Java. In Kotlin’s case, simpler syntax means less code and faster development In fact, Kotlin uses the Java Virtual Machine, and its code will run the same way as Java. The compiler will generate a bytecode - a set of instructions that will be executed by JVM. This is why we could see seasoned Java fans switching to Kotlin as soon as it was released

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Mobile Application Development blog"]

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    Technologies

  • Aug 12, 2021
  • How To Build An Asthma Medication And Control app

    Asthma Control App, the best medication reminder app, ensures you can take the stress out of medication schedules. A secure, data-driven service supports effective health management for you and those you care for

    Introduction

    Asthma Control App, the best medication reminder app, ensures you can take the stress out of medication schedules. For supporting effective health management, a data driven and secure service is required. Getting digital reminders and missed dose notification is a simpler and smarter way to manage your medication.

    Overview of Market share

    Today around 300 million people are suffering from asthma. In a period of 8 years it may rise to 400450 million, which is an increase by about 50%. The asthma apps are currently used by less than 1% of the target group. Analysis is being done to know the reason for this low user adoption rate. What are the reasons behind this low user adoption rate and why with the current asthma app solutions, mHealth publishers have managed to just barely scratch the surface on this market? To answer these questions, let’s look at the Top 10 asthma apps in 2017. The list is exclusive to asthma mobile apps with a core business to serve and empower asthma sufferers. The asthma apps are mainly to help and serve the people suffering from asthma. There are nearly 1,500 mobile apps for asthma patients in Google play store and Apple app store. The preferred mobile platform is iOS accounting for 100% of all top 10 core asthma apps releases from mHealth publishers. 50% of these apps are also published on Android

    overview-share

    How does the Asthma control app works?

    For many, the concept of an Asthma control app supports you to feel confident with appropriate handling and administering of medication. The asthma control app does this by utilizing digital reminders to notify you when you need to take your medication And it's not only about providing reminders, but also keeping those in your network updated. Missed medication alerts can inform family, carers, and doctors when a dosage has been forgotten to ensure the patient isn't at risk of complications related to mismanaged medication delivery. The Asthma control app, helps to take the right dosage at right time and thereby it helps to have a control over their medication schedule. Something most of us would appreciate with so many other things to remember The app isn't just useful for patients, but carers too. It is very essential to make sure that our family member or friend takes their medication at correct schedule. Everyone's medication requirements differ, which can be tricky to manage, especially if you're assisting with distributing the medication to multiple family members, perhaps elderly parents or children with health conditions. In such cases the flexibility to create customized reminders for your medication schedule helps and makes life easy. Many of us may take common medications which are taken at the same time daily such as contraceptive pills, other medicines may have complicated schedules with several medicines needing Some of us may only be taking common medications that must be taken at the same time each day such as contraception, others may be operating to more complicated schedules with various medicines needing to be taken at regular intervals throughout the day, that's where a medication reminder app can support you

    What are the best features to have

    Take full control of your asthma with Asthma Control App

    best-feature A visual dashboard presents your patient's key results. We can get a glimpse of the patient’s actual condition at any time by seeing the progress and trends for various factors like lung tests or inhaler technique rating, in real time. And because the Asthma Control app connects your Inhalers & lung monitors with your smartphone seamlessly, you know you're getting not only medical-grade results but peace of mind. Isn't that all the smarter?

    Never miss a dose

    Schedule medicine intake on the app and get reminded every single time

    The one time you want to keep your family connected

    Asthma control app will help you to your family connected with you

    Friends connect

    By connecting with your friends they will also get notified of the medication you have taken or missed or skipped by receiving a push notification

    Notifications and Reminders

    It is important for patients to have certain reminders and notifications to get their medication on time. However, the time and frequency of notifications should be adjustable

    Inhaler technique

    The asthma control app is designed to reach inside your lungs and if your medication is actually only hitting the back of your throat or, worse still, staying on your tongue, you're not giving it enough of a chance of doing its thing

    Peak flow meters and spirometers support

    By enabling Bluetooth, patients can record and share their health data measurements at anytime and anywhere. This will help the patients to regularly record Facilitating the ability for patients to regularly record and upload data sets about their lung function can keep doctors more informed about a patient's condition than periodical in-person assessments With the portability of the Asthma control app, peak flow meters, and spirometers, patients can share key lung function data with their doctors from anywhere

    Tech stack

    Mobile Platforms API Server
    Push Notification Integration
    Database Programing Language

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="E-Commerce blog"]

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    Case Studies

  • Aug 12, 2021
  • How To Build An E-Commerce for wholesale dealers

    Electronic commerce is buying and selling of products through online services. In E-commerce for wholesale the products are sold in bulk from the e-commerce site instead of selling individually to each person

    Introduction

    Electronic commerce is buying and selling of products through online services. In E-commerce for wholesale the products are sold in bulk from the e-commerce site instead of selling individually to each person. Wholesale reduces the cost of doing business and is intermediate between manufacturer and retailer. Since items are sold in bulk there might be larger orders. So the products can be sold quickly without much need for marketing. Ecommerce for wholesale is completely new but it is growing fast these days. There is a trigger in growth because of the increase in internet connection and smartphone use

    Overview of market share

    The global e­commerce market size was valued at USD 6.64 trillion in 2020 and is expected to grow by a compound annual growth rate (CAGR) of 18.7% from the period 2021 to 2028. The COVID-19 pandemic brought about a shift in wholesale dealer's preference for online shopping, creating avenues for growth. The factors that affected e­commerce business outlook are the changes in consumer behaviour, increase in order quantity, physical stores closure and disruption in supply chain While retail sales dipped in 2020,  e-commerce sales witnessed a surge. Several businesses are now focused on moving their customer online Established organizations and large enterprises are moving towards online business due to lesser expenditure in communication and infrastructure. E-commerce offers the organization an easier reach for the dealers/customers, and hence necessary exposure to business is also achieved. Nowadays, the marketing options are in abundance due to the popularity of social media applications, which helps in driving the market for e-commerce towards a growth path

    How e-commerce for wholesale dealers Works

    In wholesale e-commerce, the products are sold in bulk and the wholesaler is the middle man in the supply chain which starts from Producers. The wholesale dealers buy the product in bulk from a manufacturer or dealer through their online site. Here the dealer places his order for products on the website. The concerned organization will process the order and supply the goods to the wholesale dealer. It is then sold to another wholesale dealer or directly to the consumers

    wholesale-dealers

    What are the best features to have in e-commerce for wholesale

    Some of the best to have features of wholesale eCommerce are

    Payment Flexibility

    The payment gateway and the payment options offered will all make a difference in the success of a business. Users of e-commerce websites should have payment flexibility. They should be able to pay in any way that will work for them. A payment gateway with advanced functionalities should be integrated to support the business and its growth

    Easy to Use checkout feature

    Adding items to the cart and then checking them out to proceed with payment must be an easy process. In case the checkout feature is too complicated the buyer may feel irritated and abort the process of buying products. So this should be easy to use a feature

    Ease of Navigation

    The key to the success of any e-commerce website is east to Navigation. The navigation should be easy, clear, and user-friendly. Extreme care should be taken while designing and developing the User Interface (UI). Clear navigation will improve the User Experience (UX) which will attract more users

    User Reviews

    Most people who shop on the website read the reviews before purchasing the product. People think that negative reviews will diminish sales. But it is actually not true. It is often positive to have negative reviews. When there are only positive reviews people think that they are fake. When there are true reviews, it will attract more people to the website

    Security

    The e-commerce platform should be secure for the users. Using features like an SSL certificate for a secure connection between user and e-commerce site, firewall to provide a gateway between networks and allow only authorized traffic, two-factor authentication for a user to log in would be ideal for any e-commerce site

    Tech Stack

    Front end for E-commerce

    The front end for an e-commerce website can be developed using JavaScript libraries like Angular or React, CSS, HTML

    Back end for E-commerce

    The programming languages used for server-side coding are C#, PHP, and Python. Depending on the requirement of the project and the goals of the business-appropriate language is selected

    Third-party Services

    The e-commerce website needs to be integrated with third-party services like payment gateways, shipping modules, CRM, and analytics tools for the effective functioning of the e-commerce site

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="E-Commerce blog"]

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    Case Studies

  • Aug 10, 2021
  • How To Build A Productivity Tracking App

    Productivity Tracking App is a free time tracking software that notes and analyzes productivity at work. It is a tool that has been chosen by startups and large enterprises that employ hundreds of people.

    Introduction

    Time tracking software helps both employees and managers to track the project time along with expenses and other operations of the enterprise effectively. There will be good growth in the time tracking software industry because of prevailing remote work, use of cloud­ based time tracking software, and mobile phones being used for official work

    Overview of Market Share

    Time tracking software enables managers and employees to manage and track project time and expense, payroll, and other enterprise operations effectively. Furthermore, due to the emergence of cloud-based time tracking software, the prevalence of remote work, and the use of mobile phones for official purposes, it is expected that the time tracking software industry will grow during the forecast period. The Global time tracking software market is expected to register at a CAGR of 20.69% By the end of 2027, the Time tracking software market size is estimated to be USD 2043.83 billion. The major factors that are driving the market are the improvement in inventory management, asset tracking, and the usage of consumer goods, especially in the North-America

    productivity

    How does Productivity Tracking App work?

    Time Tracking

    It tracks the time worked by each and everyone on your team and gives you a breakdown by client, project, and task. It helps you to track the time spent working and time wasted and also to identify the inefficiencies

    Screenshots

    Productivity Tracking app captures Screenshots of employee monitors every 5 minutes (or turned off). It helps you to monitor exactly what your team is doing and how. By this, you can identify time-wasting, distractions, and inefficiencies. Screenshots are only taken when team members indicate that they’re working to eliminate privacy concerns

    Time Use Alerts

    Employees get a pop-up or notification alerts if they sit idle for too long, or if they are back from sleep mode Sitting idle for too long will be notified as “You are in idle mode for long. Please start the timer to continue”

    functions

    Best Features to have

    Here are the basic key features required for a productivity tracking app to make it more user-friendly and accommodating

    Signup and Login

    It allows users to have the option of creating their account or if you are running a LARGE ENTERPRISE, it lets you create multiple organizations with multiple users

    Users and Projects

    Users and projects can be created for each Organization. For each user project can be assigned. This will help to track the user’s activities for that particular project. Track in which project they are working on and how much time they spent on each project

    Clients Feature

    Give your clients access to the Productivity Tracking app at no extra cost. The client can see the screenshots and can also get reports regarding the tasks that were worked. Your clients will be restricted to seeing only data about work that you’ve done for them, rather than all work done in your company

    All Devices

    It can be used on desktops, tablets, and mobile phones – wherever the work is, we track it

    Activity Monitoring

    It helps you to track your employees’ activities during their work time at 0 Cost. So you can easily monitor where they are in the project and how they are working

    View Screenshots

    You can also find how your employees are spending every five minutes of your workday by capturing the screenshots

    Technological Stack

    React JS

    ReactJs is a toolkit for creating user interfaces introduced by Facebook in the year 2011. To merely put across, React is a solution that helps developers to resolve issues faced when building user interfaces. It enables developers to create intricate user interfaces that have components that will change regularly over time without writing tricky JavaScript codes every time

    Angular

    Angular is a TypeScript-based free and open-source web application framework led by the Angular Team at Google and our team create a web application using angular with responsiveness and deliver good products

    Electron

    We create desktop applications using Electron for cross platforms support with UI frameworks like angular and deliver effective user-friendly application

    Frequently Asked Questions

    Understand the common challenges or questions in the mind of our customers

    [rc_faq limit="-1" terms="Productivity Tracking blog"]

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    Technologies

  • Jul 28, 2021
  • How To Enable Green Field Systems on Azure

    A MAJOR ENERGY player, multinational integrated oil and gas company, is one of the seven big oil companies in the world

    A MAJOR ENERGY player, multinational integrated oil and gas company, is one of the seven big oil companies in the world, needed some governance and framework around provisioning of azure resources. The main objective of client was to come up with an integrated solution for Azure Service Orchestration for various mobile, web, analytics and machine learning projects

    Current Challenges

    1. The client has an existing architecture and system setup to support specific topology of applications in pre-production. The cost involved in building the infrastructure and the technical dependencies to maintain and enhance is too high
    2. Industry-standard well-architected framework principles were not followed. The client is stuck with a solution that is not scalable. Ex: takes weeks to add support for a different topology of apps
    3. Time taken to set up and tear down infrastructures is causing a huge delay in business deliveries and directly impacting the business deliveries and operational cost
    4. Testing the service configuration and having a first-time-right infrastructure for each system type is a major challenge in any cloud provider

    Present System

    In the existing system, the Engineer has to know about azure resources and every service to provide the resources through the Azure portal. Creating or updating the resource with right configuration is a time consuming process. Also, there is a huge chance for human error in configuring any specific environment for a specific project The issues faced in the current system are
    1. 80% Probability of Human errors
    2. Lack of Control in Cast and Usage
    3. Infrastructure Topology - Not Scalable
    4. Delay in provision of resources

    present-img

     Proposed system - Architecture & Benefits

    1.  A simple Do-It-Yourself UI has been delivered to all the engineers. The engineers can just click on the UI and decide what type of system they want to build and drag and drop components
    2. A role-based system is set up behind the screens to control the generation of infrastructure as per the definition in AD(Active Directory) or any other provider
    3. The opportunity was also utilized to identify resources in Azure that were causing a lot of overhead costs and maintenance costs. These were replaced with free open-source alternatives with recommended architecture standards
    4. Applications / Systems built are 100% configurable with adoption to best practices from industry standards including usage of vaults / KMS for secrets

    system-architecture

    Automated Infrastructure Generation

    • Dependency on experienced and mature engineers to be always around to build systems is impossible and costly. We eliminated this need by 100%. Anyone without prior experience can now request/generate and manage infrastructure
    • Cloud agnostic approach of engaging terraform ensured 100% portability for the client to repeat the same across other cloud providers like AWS
    • Tested code for infrastructure ensures that the developers or DevOps engineers do not end up debugging the same issues. Over a period of 3 months, the reliability of systems improved by 60% and will continue to grow
    • Modernization of existing systems as part of this opportunity also reduced unwanted licensing costs
    • Time to market for the infrastructure was reduced from 3 weeks to 1 day. This is a major win for the client to onboard new customers and delivered direct business results
    • Time taken for Change management and propagation of infrastructure changes has significantly reduced from a couple of hours to a couple of mins due to automation in place
    devops

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    Technologies

  • Jun 28, 2021
  • How to Hire Remote Developers in 2021 making no Mistakes?

    There is a great demand for hiring remote developers. Remote developers are hired to fill up the talent gap, speed up the development process, lower costs, and for flexibility. Finding the right developer is not an easy task.
    There is a great demand for hiring remote developers. Remote developers are hired to fill up the talent gap, speed up the development process, lower costs, and for flexibility. Finding the right developer is not an easy task In this article, you’ll find how to hire remote developers, including the Hiring and Interview processes

    Hiring Process

    1. Define your Requirements

    The first thing to start with, for hiring a remote developer is to identify the following:
    • Project Requirements
    • Technology Stacks for the Project and
    • Details of Must-have skills and Nice to have skills
    Using the above details, the appropriate job description should be created along with experience and skill level. The description should be clear and concise. It should be a true representation of the role. Then it will be easy to look for Developers

    2. Various Hiring Options

    There are various Hiring Options out of which three are the main hiring Options. Independent Contractors/Freelancers, In-house developers, and Sub-contractors Independent Contractors/Freelancers Freelancers can be chosen if it is a small project. Hiring freelancers will cost less for the company and they will deliver results fast. But there are few disadvantages in hiring freelancers with respect to their loyalty In-house developers In-house developers can be hired to work full time remotely as a part of your Company. The in-house developers can work on multiple projects too though this is a costly option Sub-Contractors Hiring sub-contractors is another option in which they can be hired from an Outsourcing company to work as part of your team. This method has a high level of security and is highly reliable. Either one developer can be hired or an entire team can be hired and payment need not be made at the initial stages

    3. Choosing the Hiring Destination

    You can search for hiring destinations across the globe to find the developers of your choice. Research needs to be done before investing in foreign app developers. Then there should be good communication with the developer to know about their previous works. Since this is going to be a long-term relationship like developing the app, getting feedback from the client and making improvements, adding new features, and so on the right amount of time should be invested in searching for the developers in the hiring destination. There are some popular outsourcing destinations that can be considered. With all these criteria in mind, candidates can be shortlisted hire

    Interview Process

    1. A quick background check of the short-listed candidate will be the first step of the Interview Process
    2. Initial Screening can be done over the telephone to identify if the candidate can bring any value to the Company and also to find out if they can work independently and be a good team player
    3. Then the technical interview needs to be conducted with technical questions from the technology stack presented in the Description. Technical questions can include questions about past projects, programming languages and frameworks, and software developer tools
    4. Then the next step is making the offer. Pay details and all benefits they are worth should be mentioned
    5. The last step would be the acceptance part by the Candidate. When the candidate accepts the offer the offer letter can be handed over to the candidate which completes the interview process
    hire1
    There are some common mistakes which many Organizations make while hiring a developer. Some common mistakes are,
    1. Compromise on quality because of the low-cost package offered by a less skilled developer
    2. Bypassing the technical discussion part for the candidate
    3. Hiring a developer who does not have much knowledge about your business or services
    4. Restricting Hiring options without widening the search for enthusiastic developers
    These mistakes should be re-read while hiring developers and avoided in the future. Learning from mistakes will be a step towards success  

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