resilience-checker

To audit microservices for missing resilience patterns, you check all external dependency calls for configured timeouts, retry policies with exponential backoff, per-dependency circuit breakers, and idempotency keys to prevent cascading failures.

Without dead-letter queue routing and bounded retries, message queue consumers risk poison message blocking and infinite retry loops. Validating async boundaries ensures correct visibility timeouts and prevents message loss during processing failures.

You need idempotency keys and dead-letter queues in payment processing services to prevent double-processing of write operations and message loss. These resilience patterns ensure safe retries on charge endpoints and isolate poison messages in order queues.

To verify graceful shutdown readiness, you validate SIGTERM implementation and separate liveness and readiness health check endpoints. This prevents ungraceful pod termination during orchestrator shutdowns and ensures proper traffic draining.

Yes, you can check resilience patterns across Python, TypeScript, C#, Java, C, C++, and SQL stacks. The resilience audit validates production-grade services for compliance with reliability best practices regardless of the backend language.

Chaos readiness validation checks for documented chaos testing experiments and failure injection in staging environments. It prevents production outages by ensuring distributed services have bulkhead isolation, circuit breakers, and graceful degradation under dependency failures.