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Johnathan Corgan
66c268a564
Move examples/docker-network/ to testing/static/ and add testing/chaos/ as a new stochastic simulation harness. testing/static/ — Static 5-node test harness: - Fixed mesh, chain, and mesh-public topologies with docker compose - Manual test scripts (ping, iperf, netem) - Build script, config generation, key derivation testing/chaos/ — Stochastic network simulation: - Python orchestrator generating N-node FIPS meshes with dynamic network conditions, driven by reproducible YAML scenarios - Topology generation: random geometric, Erdos-Renyi, or chain graphs with BFS connectivity guarantee - Per-link netem: HTB classful qdiscs with u32 filters for per-peer impairment (delay, loss, jitter), stochastic mutation across configurable policy profiles - Per-link bandwidth pacing: HTB rate limiting with configurable tiers (1/10/100/1000 mbps) randomly assigned per edge - Link flaps: tc netem 100% loss with graph connectivity protection - Node churn: docker stop/start with netem re-application on restart, shared down_nodes tracking across all managers - Traffic generation: random iperf3 sessions between node pairs - Down-node guards: all docker exec callers check container liveness, auto-detect crashed containers via is_container_running() safety net - Log collection and post-run analysis (panics, errors, sessions, MMP metrics, tree reconvergence) - chaos.sh wrapper with --seed, --duration, --verbose, --list options - Four scenarios: smoke-10, chaos-10, churn-10, churn-20
875 B
875 B
FIPS Testing
Integration and simulation test harnesses for FIPS, using Docker containers running the full protocol stack.
Test Harnesses
static/ -- Static Docker Network
Fixed topologies (mesh, chain) with 5 nodes. Manual scripts for building, config generation, connectivity tests (ping, iperf), and network impairment (netem). Useful for deterministic debugging and validating specific topology configurations.
chaos/ -- Stochastic Simulation
Automated randomized testing with configurable node counts, topology algorithms (random geometric, Erdos-Renyi, chain), and fault injection (netem mutation, link flaps, traffic generation, node churn). Scenarios are defined in YAML and executed via a Python harness that manages the full lifecycle: topology generation, Docker orchestration, fault scheduling, log collection, and analysis.