Microservices Architecture Patterns Every Engineer Should Know

Microservices aren’t a silver bullet. They solve real problems while creating new ones. This post covers the patterns that make microservices work in practice — and the pitfalls that bring them down.

When to Go Microservices

Don’t start with microservices. Start with a monolith, then extract services when you feel the pain:

• Independent scaling — One service needs 10x more instances than others
• Independent deployment — Teams are blocked waiting for release coordination
• Technology diversity — One component genuinely needs a different language/database
• Organizational boundaries — Conway’s Law: structure follows org chart

The “microservices first” approach almost always leads to distributed monolith hell.

Decomposition Patterns

Decompose by Business Capability

Organize around business functions, not technical layers:

Decompose by Subdomain (DDD)

Use Domain-Driven Design to find service boundaries. Each bounded context becomes a service candidate.

Communication Patterns

Synchronous (REST/gRPC)

Use for operations requiring an immediate response:

Problem: Coupling. If payment service is down, the whole chain fails.

Asynchronous (Message Queue)

Use for operations that don’t require immediate response:

Benefits: Decoupling, resilience, natural retry mechanism.

The API Gateway Pattern

Never expose your internal services directly. Use an API Gateway as the single entry point:

The gateway handles:

• Authentication/Authorization
• Rate limiting
• Request routing
• SSL termination
• Response aggregation

The Saga Pattern for Distributed Transactions

ACID transactions don’t work across services. Use sagas — a sequence of local transactions with compensating transactions for rollback.

Choreography-based Saga

Services react to events:

Orchestration-based Saga

A central coordinator drives the steps:

Circuit Breaker Pattern

Prevent cascading failures when a downstream service is struggling:

Use libraries like gobreaker (Go) or resilience4j (Java) in production.

Service Mesh

For complex microservices deployments, consider a service mesh (Istio, Linkerd):

• mTLS between all services
• Distributed tracing without code changes
• Traffic management (canary, weighted routing)
• Circuit breaking and retries at the infrastructure level

The Most Important Rule

Don’t build microservices you don’t need yet. The architecture cost is real. Embrace the monolith, identify the seams, and extract thoughtfully when the business justifies it.