12.4. Testing in Distributed Systems
Testing a distributed system is fundamentally harder than testing a monolith, because the bugs live in the interactions — the timeout that fires under load, the message that arrives twice, the replica that lags — and none of them appear when services are tested in isolation. This chapter covers integration and contract testing at service boundaries, end-to-end testing and its flakiness, testing asynchronous and eventually-consistent flows, staging fidelity, load testing, and the correctness testing (Jepsen, deterministic simulation) that hunts for the consistency violations unit tests can never find.
Topics Covered
Section titled “Topics Covered”- 12.4.1. Integration Testing: Service Boundaries and Contract Verification: Covers integration testing at service boundaries and contract verification between services.
- 12.4.2. End-to-End Testing: Balancing Coverage and Flakiness: Explains end-to-end testing and the balance between coverage and the flakiness that erodes trust.
- 12.4.3. Testing Event-Driven Systems: Async Flows and Eventual Consistency: Covers testing asynchronous flows and eventual consistency where results arrive after the call returns.
- 12.4.4. Staging Fidelity: How Realistic Is Your Test Environment?: Explains staging fidelity: how realistically a test environment reproduces production behavior.
- 12.4.5. Test Data Management: Synthetic Data, Anonymization, and Seeding: Covers test data management: synthetic data, anonymization, and seeding for realistic test scenarios.
- 12.4.6. Load and Performance Testing: k6, Locust, and Capacity Validation: Explains load and performance testing with k6 and Locust to validate capacity before production.
- 12.4.7. Correctness Testing: Jepsen and Deterministic Simulation: Covers correctness testing with Jepsen and deterministic simulation that hunt for consistency violations.