← All Projects

Microservices Transformation

Led a team of 12 developers to transform a monolithic legacy system with 2M+ lines of code into a modern microservices architecture.

.NET CoreDockerKubernetesAzureRabbitMQMongoDB

A large-scale migration from a monolithic legacy system to a modern microservices architecture, involving 12 developers over 18 months.

The Problem

The legacy system had accumulated over 2 million lines of code across 15 years:

  • Multiple databases with complex, undocumented dependencies
  • Quarterly release cycles due to deployment risk
  • Mounting technical debt slowing feature delivery
  • Performance limitations with no ability to scale individual components
  • Single point of failure — any bug could bring down the entire system

The Approach

Strangler Pattern

Rather than a risky full rewrite, we used the strangler pattern to gradually replace components:

  1. Domain-Driven Design workshops to identify service boundaries
  2. API gateway to route traffic between legacy and new services
  3. Phased migration prioritized by business impact and risk
  4. Complete CI/CD pipeline for each new service
  5. Centralized observability from day one

Architecture

  • Domain-focused microservices with independent databases (SQL Server + MongoDB)
  • Event-driven messaging via RabbitMQ for asynchronous communication
  • Unified authentication layer using Azure AD
  • Client-facing API gateway for routing and rate limiting
  • Integrated monitoring and alerting with Prometheus and Grafana

Team & Leadership

Led a team of 12 developers organized into 3 autonomous squads, each owning specific domain services. Established:

  • Architecture decision records (ADRs) for all major decisions
  • Shared service templates and scaffolding tools
  • Cross-squad code review process
  • Weekly architecture sync meetings

Tech Stack

  • Backend: .NET Core microservices
  • Containers: Docker, Kubernetes (AKS)
  • Cloud: Azure (App Service, AKS, Azure SQL, Cosmos DB)
  • Messaging: RabbitMQ
  • Databases: SQL Server, MongoDB
  • CI/CD: Azure DevOps
  • Monitoring: Prometheus, Grafana, Azure Application Insights

Results

  • Deployment frequency: From quarterly to daily releases
  • 60% reduction in critical production issues
  • 45% improvement in system performance through independent scaling
  • Autonomous team operations — each squad can deploy independently
  • Developer onboarding time reduced from weeks to days with clear service boundaries