Testing Distributed Systems
1. Implementing Unit Testing for Distributed Components
| Practice | Detail |
|---|---|
| Pure logic | No network/IO; in-memory fakes |
| Time injection | Inject Clock; avoid System.currentTimeMillis() |
| Mocks | Mockito, gomock — for boundaries only |
| Property-based | jqwik, Hypothesis — for protocols |
2. Implementing Integration Testing
| Tool | Detail |
|---|---|
| Testcontainers | Real DB/Kafka/Redis in Docker |
| LocalStack | AWS services locally |
| WireMock | HTTP service stubs |
| Embedded brokers | Embedded Kafka, embedded Postgres (less common) |
3. Implementing Contract Testing
| Tool | Detail |
|---|---|
| Pact | Consumer-driven contracts; broker |
| Spring Cloud Contract | Producer-driven, generates stubs |
| OpenAPI / proto | Schema-first; lint + diff |
| Schema Registry | Backward/forward compat enforcement |
4. Implementing End-to-End Testing
| Tool | Layer |
|---|---|
| Playwright / Cypress | UI |
| RestAssured / supertest | API |
| Karate | API + assertions DSL |
| Caveats | Slow, flaky; minimize count |
5. Implementing Chaos Testing
| Tool | Detail |
|---|---|
| Chaos Monkey | Kill instances |
| Litmus / Chaos Mesh | K8s-native; pod, network, IO chaos |
| Gremlin | Managed chaos platform |
| tc / iptables | Latency, loss, partition |
| Steady-state hypothesis | Define normal, inject, verify recovery |
6. Implementing Performance Testing
| Type | Goal |
|---|---|
| Smoke | System works under tiny load |
| Load | Expected peak |
| Stress | Beyond peak; find break point |
| Soak / endurance | Hours at load; leaks |
| Spike | Sudden burst |
7. Implementing Load Testing and Stress Testing
| Tool | Detail |
|---|---|
| k6 | JS scripting; cloud option |
| Gatling | Scala DSL; high-perf |
| JMeter | GUI + plugins |
| Vegeta | Go; constant-rate |
| Locust | Python; distributed |
8. Implementing Fault Injection
| Layer | Tool |
|---|---|
| App | Toxiproxy, Resilience4j faulty decorator |
| Service mesh | Istio HTTP fault injection (delay, abort) |
| Network | tc qdisc, Pumba |
| JVM | byteman, Chaos Monkey for Spring Boot |
9. Understanding Test Environments
| Env | Purpose |
|---|---|
| Local / dev | Per developer; testcontainers |
| CI | Ephemeral per PR |
| Staging | Prod-like; near-prod data |
| Pre-prod / canary | Real prod traffic subset |
| Ephemeral envs | Per-PR via Argo, vcluster, Octopod |
10. Implementing Test Data Management
| Approach | Detail |
|---|---|
| Factories / builders | Object Mother pattern |
| Fixtures | Shared seeded data |
| Faker | Generated synthetic data |
| Anonymized prod | Mask PII; subset by tenant |
| Snapshot reset | Restore DB between tests |
11. Implementing Simulation and Modeling
| Approach | Detail |
|---|---|
| Discrete-event sim | SimPy, Akka simulation |
| Deterministic sim | FoundationDB-style; fast-forward time, replay seed |
| Formal (TLA+) | Model invariants; check liveness/safety |
| Jepsen | Black-box correctness under partition |