microservice-patterns-service-mesh-and-traffic-management

Microservice Patterns Service Mesh And Traffic Management

Use When

• Fleet-wide traffic policies need consistency
• Teams require canary and security controls without app rewrites

Workflow

1. Define baseline traffic policy: timeout, retry budget, circuit behavior.
2. Enforce mTLS identity and authorization between services.
3. Configure canary, blue-green, or weighted routing rules.
4. Apply outlier detection and connection pool limits.
5. Monitor policy impact on latency and error budgets.

Required Checks

• Retry policy does not amplify downstream outages
• Service identity and policy scopes are explicit
• Canary rollback can be triggered quickly

Decision Framework

• Prefer explicit contracts and compatibility rules before implementation.
• If dependency risk is high, require timeout, retry, and fallback strategy per call path.
• If async messaging is used, require idempotency, replay, and dead-letter handling.
• If traffic patterns are volatile, require load, failover, and scaling validation before ship.

Common Rationalizations And Rebuttals

• "Retries will handle failures automatically." -> Unbounded retries can amplify outages; use budgets.
• "We can skip runbooks for now." -> Operational ambiguity delays incident recovery.
• "Contract changes are minor." -> Small breaking changes cause broad downstream regressions.

Evidence Pack

• Contract compatibility note and migration strategy (if applicable)
• Failure-mode test evidence for dependency degradation and recovery
• Observability snapshot (latency, error, saturation, or queue health)
• Rollout and rollback steps with clear trigger thresholds

Exit Criteria

• Traffic behavior is controllable and observable at platform layer
• Security and release routing are repeatable across services