Service Resilience and Fault Tolerance
In a microservices system, failure is not a question of if but when. Services will crash, networks will partition, and databases will slow down. The difference between a system that degrades gracefully and one that collapses catastrophically is the resilience patterns you build in. This lesson covers the essential patterns that keep your system running when things go wrong.
Watch: Video Walkthrough
Key Concepts
- Circuit Breaker: Stopping cascade failures by detecting and short-circuiting failing calls
- Retry with Backoff: Implementing exponential backoff with jitter for transient failures
- Timeout Budgets: Setting and propagating timeout limits across service chains
- Bulkhead Pattern: Isolating failures so one slow dependency does not consume all resources
Hands-On Exercise
Task: Implement a circuit breaker around the Payment Service call from the Order Service. Configure it to open after 3 consecutive failures, stay open for 30 seconds, then enter half-open state. Add retry logic with exponential backoff (100ms, 200ms, 400ms) and a 5-second total timeout. Test by intentionally crashing the Payment Service.
Pro Tips
Always add jitter to your retry backoff. Without jitter, when a service recovers from an outage, all the clients that were waiting will retry at exactly the same intervals, creating a thundering herd that crashes the service again. Random jitter spreads the retries out and gives the recovering service breathing room.