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

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

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