Why Microservices Matter
Microservices architecture has become the go-to pattern for building scalable, maintainable enterprise applications. But adopting microservices without understanding the tradeoffs can create more problems than it solves.
In this guide, we cover the patterns that actually matter and cut through the noise around the ones that don't.
Service Design Principles
Good microservices start with good boundaries. Here's what we've learned about designing services that hold up:
- Design around business capabilities, not technical layers
- Keep services small enough to rewrite, not so small they add overhead
- Own your data — each service manages its own database
- Design for failure from day one
API Gateway Patterns
An API gateway acts as the front door to your microservices. It handles cross-cutting concerns like authentication, rate limiting, and request routing.
Popular options include Kong, AWS API Gateway, and custom solutions built on NGINX or Envoy. The choice depends on your infrastructure and team expertise.
Service Mesh and Observability
As your service count grows, managing inter-service communication gets complex. A service mesh like Istio or Linkerd handles this by providing:
- Automatic mTLS encryption between services
- Traffic management and canary deployments
- Distributed tracing with Jaeger or Zipkin
- Circuit breaking and retry policies
Data Management
The biggest challenge in microservices is data management. Each service owning its data means you need strategies for:
- Event sourcing for data consistency across services
- CQRS for separating read and write models
- Saga patterns for distributed transactions
- Change Data Capture for data synchronization
Conclusion
Microservices aren't a silver bullet. They work best when you have clear service boundaries, strong DevOps practices, and teams structured around business domains. Start with a monolith, identify natural seams, and extract services when the complexity justifies the overhead.