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Case Study

How DevOps and Rapid Containerization Saved 70% Development Time and Reduced 45% Infra Cost Savings


Why product engineering teams need DevOps experts who are hands-on with rapid container deployments and orchestration?

The use of containers binds together software development and operational IT skills. It requires the ability to encapsulate code together with libraries and dependencies.  

Some Example Microservices and Dependencies:

  1. Customer Loan Account Management: This microservice handles account creation, modification, credit history mapping, collateral data, etc. It requires knowledge of data querying (e.g., PostgreSQL) to store or retrieve account information.
  2. Collateral Processing Microservice: This microservice manages collateral processing, including credit-check analysis, bill payments, and transaction history retrieval. It may utilize messaging queues (e.g., Apache Kafka) for asynchronous communication.
  3. Authentication Microservice: This microservice handles user authentication and authorization. It may rely on authentication libraries (e.g., OAuth 2.0) for identity management.

Application containerization is effective for recurring background processes involving batch jobs and database jobs. With application containerization, each job can run without interrupting other data-intensive jobs happening simultaneously.

Skills required for containerization?

Along with expertise in handling platforms like Kubernetes for container orchestration, you also need hands-on experience in container distribution management and in enabling hardened API endpoints.

Our ability to spin up new container instances helps run multiple application testing projects in parallel. Our DevOps Engineers are adept at standing-up similar runtime environments – mirroring and production without impacting any other process. Container orchestration is also the key to maintaining uniformity in development, test, and production environments. Our knowledge of code reusability ensures components are used multiple times in many different applications thereby also speeding up developers’ ability to build, test, deploy, and iterate.

The Challenge

Monolithic Architecture

  • The legacy IT system was a rigid monolith running on legacy programming language that did not support new age experiences and struggled to meet compliance
  • The existing monolithic architecture posed challenges in deployment, scalability, and reliability
  • Deploying updates or new features required deploying the entire application, leading to longer release cycles and increased risk of downtime

Limited Scalability

  • Scaling the monolithic application horizontally was difficult, as the entire application had to be replicated to handle increased load.
  • This resulted in inefficiencies and higher infrastructure costs.

Reliability Concerns

  • Monolithic applications are more prone to failures, as a single bug or issue in one part of the application can affect the entire system
  • It can lead to service disruptions and customer dissatisfaction.

Migration planning and high availability

  • Migrating a specific function to an individual microservice requires expert assessment of reusable components, code libraries, and other dependencies that can be clubbed together
  • It is essential to monitor containerized environments to ensure peak performance levels by collecting operational data in the form of logs, metrics, events, and traces


Decomposition of Monolith: Identified and decomposed monolithic components into smaller, loosely coupled microservices based on business capabilities, allowing for independent development, deployment, and scaling.

Containerization of Microservices: Packaged each microservice and its dependencies into separate containers using Docker, ensuring consistency and portability across development, testing, and production environments.

Orchestration with Kubernetes: Deployed microservices on a Kubernetes cluster to automate container orchestration, scaling, and management, enabling seamless deployment and efficient resource utilization.

Service Mesh Implementation: Implemented a service mesh to manage inter-service communication, monitor traffic, enforce security policies, and handle service discovery, improving reliability and fault tolerance.

CI/CD Pipeline Integration: Established CI/CD pipelines to automate the build, test, and deployment processes for microservices, ensuring rapid and reliable software delivery while minimizing manual intervention.


How we Helped

  • Our domain-driven design approach helped define the boundaries of the microservice from a business point of view
  • As each microservice was getting assigned to a different container resulting in a large modular architecture, we structured its management and orchestration
  • Managed Kubernetes enabled optimal pod distribution amongst the nodes
  • Observability generated data to show how much resources would any container optimally need
  • Enabled visualization on the number of clusters, nodes, pods, and other resources for each container
  • Imparted training sessions to learn about containerization tools like Docker and Kubernetes, fostering teamwork across departments
  • The shift to containerization encouraged staff to try new methods, share insights, and continuously learn from each other
  • Regular feedback sessions allowed teams to voice concerns, suggest improvements, and refine containerization strategies over time
  • Milestones in containerization progress leading to new application feature release is speeding modernization initiatives


  • Weeks, not months is the new normal for launching new applications
  • 70% decrease in the time taken for testing and infrastructure provisioning
  • Zero downtime experienced when releasing a new feature in the live environment
  • USD 40,000 saved in operating costs through optimized infrastructure management
  • 45% cost savings in infrastructure and IT operations costs other spent on expensive resources
  • 999% uptime enabled for the applications with use of optimized container orchestration


Simplified Deployment: With microservices, deploying updates became easier. Each service can be updated independently, cutting release times and downtime.

Enhanced Scalability: Microservices allow for flexible scaling of services, reducing costs and optimizing resources as needed. Improved Reliability: By separating services and using a service mesh, the system became more reliable, with fewer disruptions and better user experiences.

Agility and Innovation: Microservices and CI/CD enable quick experimentation and deployment of new features, keeping the customer competitive. Cost Efficiency: Microservices and containerization save costs by using resources more efficiently and reducing downtime expenses.



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