Architecture Patterns

Production-tested patterns and principles for building resilient, scalable distributed systems. These patterns emerge from real-world implementation experience and operational learnings.

Resilience Patterns

Circuit Breaker

Prevent cascading failures by failing fast when downstream dependencies are unhealthy.

When to Use

  • Protecting against failing or slow external services
  • Preventing resource exhaustion from blocked threads
  • Need for fast failure detection and recovery

Implementation Guidance

  • Configure failure threshold based on error rate (typically 50%)
  • Set appropriate timeout durations (30-60 seconds open state)
  • Implement half-open state for testing recovery
  • Monitor circuit breaker state transitions

Bulkhead Pattern

Isolate resource pools to prevent total resource exhaustion from a single failing component.

When to Use

  • Multiple services share common resources
  • Need to isolate critical from non-critical operations
  • Preventing complete system failure from resource exhaustion

Implementation Guidance

  • Separate thread pools per service dependency
  • Allocate resources based on criticality
  • Monitor resource utilization per bulkhead
  • Configure appropriate timeouts per pool

Data Consistency Patterns

Saga Pattern

Manage distributed transactions through compensating transactions for eventual consistency.

When to Use

  • Multi-service transactions without 2PC
  • Long-running business processes
  • Need for eventual consistency with compensation

Orchestration vs Choreography

  • Orchestration: Central coordinator manages flow
  • Choreography: Services react to events
  • Choose orchestration for complex workflows
  • Choose choreography for loose coupling

Event Sourcing

Store all state changes as a sequence of immutable events rather than current state.

When to Use

  • Complete audit trail requirements
  • Temporal queries (system state at any point in time)
  • Event-driven architectures
  • Replay capabilities for debugging

Trade-offs

  • Pros: Complete history, audit trail, temporal queries
  • Cons: Complexity, eventual consistency, storage growth
  • Requires event versioning strategy
  • Consider CQRS for read optimization

Communication Patterns

API Gateway

Single entry point for client requests that routes to appropriate microservices.

Responsibilities

  • Request routing and composition
  • Authentication and authorization
  • Rate limiting and throttling
  • Protocol translation (REST to gRPC)

Implementation Considerations

  • Avoid business logic in gateway
  • Implement comprehensive monitoring
  • Design for high availability
  • Consider edge caching strategies

Service Mesh

Infrastructure layer handling service-to-service communication with built-in reliability.

Capabilities

  • Traffic management and routing
  • Service discovery and load balancing
  • Automatic retries and circuit breaking
  • Distributed tracing and observability

When to Adopt

  • Polyglot microservices architecture
  • Need for uniform observability
  • Complex networking requirements
  • Team size supports operational complexity

Deployment Patterns

Blue-Green Deployment

Maintain two identical production environments for instant rollback capability.

Process

  • Deploy new version to idle environment (green)
  • Run smoke tests against green environment
  • Switch router to point to green
  • Keep blue as instant rollback option

Trade-offs

  • Pros: Zero downtime, instant rollback
  • Cons: Double infrastructure cost, database complexity
  • Best for stateless services
  • Requires careful database migration strategy

Canary Deployment

Gradually roll out changes to subset of users while monitoring key metrics.

Process

  • Deploy to small percentage (5-10%)
  • Monitor error rates, latency, business metrics
  • Gradually increase traffic (25%, 50%, 100%)
  • Automatic rollback on metric degradation

Success Criteria

  • Error rate within acceptable threshold
  • Latency percentiles maintained
  • Business metrics stable or improved
  • No increase in customer support tickets

Deep-Dive Technical Articles

For comprehensive implementation guidance, architectural trade-offs, and production learnings, explore the technical insights section.

Read Technical Insights →