Writing unit and integration tests for a single-node application is straightforward: mocks and assertions verify expected state transitions. In distributed systems, however, conventional unit tests provide virtually zero confidence. The most dangerous concurrency bugs, split-brain regressions, and silent data corruptions emerge only when asymmetric network partitions, disk fsync stalls, garbage collection pauses, and clock skew collide in production.
Testing distributed systems requires rigorous, adversarial techniques:
- Linearizability Verification (Jepsen): Black-box testing that hammers a cluster with concurrent read/write operations while injecting violent network failures, then mathematically proves whether the execution history satisfies linearizability, sequential consistency, or serializability.
- Controlled Chaos Engineering: Proactively injecting network delays, packet drops, node kills, and disk corruption into staging and production to validate system resilience invariants before real outages strike.
- Deterministic Simulation Testing: Pioneered by FoundationDB, running an entire distributed cluster, simulated network, and simulated disk inside a single-threaded deterministic process with seeded pseudorandom scheduling, enabling trillion-cycle regression tests and instant bug reproducibility.
This module provides the theoretical foundations and hands-on tooling to rigorously stress-test and verify distributed invariants.