Microservices
We design and implement microservices architectures that decompose monolithic applications into independently deployable services, each owning its own data store and business logic. Our microservices projects use Docker for containerization and Kubernetes for orchestration, with service mesh implementations (Istio, Linkerd) for inter-service communication, traffic management, and observability. Each service is built around a single bounded context — for example, separating user authentication, booking management, payment processing, and notification delivery into distinct services that communicate through well-defined API contracts and asynchronous event streams. This architecture enables independent scaling: a booking service can scale to 10 replicas during peak traffic while the notification service remains at 2. Typical monolith-to-microservices migrations run 12-20 weeks, while greenfield microservices projects run 10-16 weeks, both including service decomposition design, infrastructure setup, and team workflow documentation.
Decompose monolithic applications into bounded-context microservices, each with its own database, API contract, and independent deployment pipeline.
Containerize services with Docker using multi-stage builds for minimal image sizes (typically 50-150MB) and deploy on Kubernetes with Helm charts for repeatable releases.
Implement inter-service communication using synchronous REST/gRPC for request-response patterns and asynchronous messaging (RabbitMQ, Kafka, AWS SNS/SQS) for event-driven workflows.
Configure Kubernetes with horizontal pod autoscaling, resource requests and limits, liveness and readiness probes, and pod disruption budgets for zero-downtime deployments.
Set up service mesh (Istio or Linkerd) for mutual TLS encryption, traffic splitting (canary deployments), circuit breaking, and distributed tracing across services.
Implement the Saga pattern for distributed transactions that span multiple services, with compensation logic for rollback on partial failures.
Design API gateway layers (Kong, AWS API Gateway) for request routing, authentication, rate limiting, and response aggregation across multiple backend services.
Deploy centralized logging (ELK Stack, Loki) and distributed tracing (Jaeger, Zipkin) with correlation IDs for end-to-end request tracking across service boundaries.
Establish service ownership contracts: each microservice has a defined team owner, SLA targets, API versioning policy, and on-call rotation for production incidents.
Conduct domain-driven design workshops during the decomposition phase to identify bounded contexts, aggregate roots, and event boundaries before writing service code.