jepsen-test

name	jepsen-test
description	Run Jepsen-style cluster tests using Maelstrom (lightweight) or full Jepsen (heavyweight) — validates correctness of the deployed gossip-rs system with real network behavior, complementing in-process DST

Run Jepsen-Style Cluster Tests

Validate correctness of the deployed gossip-rs system using real network behavior. This complements in-process deterministic simulation testing (DST) by testing the actual binary with real (or simulated-real) networking.

Evidence Base

Source	Principle
Jepsen (jepsen.io)	Found bugs in 30+ production databases; linearizability checking
Maelstrom (jepsen-io/maelstrom)	Lightweight Jepsen for protocol testing via stdin/stdout JSON
CockroachDB (Jepsen lessons blog)	Automated Jepsen is inherently flaky — design workloads carefully
Yuan et al. (OSDI 2014)	3 nodes suffice for reproducing most distributed failures
Jepsen etcd 3.4.3	Lease/fence failures directly relevant to gossip-rs coordination
Jepsen Redis-Raft	Ambiguous failure pattern (succeed but report failure)

Key insight: DST and Jepsen are complementary, not competing. DST explores the state space exhaustively in-process with a simulated network. Jepsen validates the real deployed system with real networking and OS behavior.

When to Use

• After implementing a gossip protocol and wanting to verify convergence
• Before releases to validate coordination correctness under real conditions
• When DST passes but you suspect real networking reveals different bugs
• When testing integration between components (not just protocol logic)

When NOT to Use

• When the gossip protocol doesn't exist yet (use /sim-scaffold first)
• For testing pure state machine logic (use /sim-run instead — faster, deterministic)
• For testing detection engine correctness (no distributed aspect)

---

Two Modes

Mode A: Maelstrom (Lightweight, Development-Time)

Tests the gossip protocol in isolation using Maelstrom's simulated network. Fast iteration, no infrastructure needed.

Mode B: Full Jepsen (Heavyweight, Pre-Release)

Tests the full deployed system with real SSH, real binaries, real network partitions. Thorough but slow and potentially flaky.

Default to Mode A unless the user specifically requests Mode B or the change involves integration between multiple deployed components.

---

Mode A: Maelstrom

Prerequisites

1. Maelstrom binary installed (brew install maelstrom or from jepsen-io/maelstrom releases)
2. A Maelstrom-compatible binary wrapper exists at crates/gossip-worker/src/bin/maelstrom_gossip.rs
3. The gossip protocol implements the sans-IO pattern (from /sim-scaffold Type B)

If the Maelstrom binary wrapper doesn't exist, guide creation:

// crates/gossip-worker/src/bin/maelstrom_gossip.rs
//
// Thin wrapper that adapts the sans-IO GossipProtocol to Maelstrom's
// JSON stdin/stdout protocol.
//
// Reads Maelstrom JSON messages from stdin, translates to GossipMessage,
// passes to protocol.handle_input(), drains poll_transmit() to stdout.

use std::io::{self, BufRead, Write};
use serde::{Deserialize, Serialize};

// Maelstrom message envelope
#[derive(Deserialize, Serialize)]
struct MaelstromMsg {
    src: String,
    dest: String,
    body: serde_json::Value,
}

fn main() {
    let stdin = io::stdin();
    let stdout = io::stdout();
    let mut out = stdout.lock();

    // Initialize protocol
    // let mut protocol = GossipProtocol::new(...);

    for line in stdin.lock().lines() {
        let line = line.expect("stdin read error");
        let msg: MaelstromMsg = serde_json::from_str(&line)
            .expect("malformed Maelstrom message");

        
        

        
        
        
        
        
        
        
    }
}

Maelstrom Workloads

Workload	Maelstrom Challenge	What It Tests
Broadcast	Challenge #3 (broadcast)	Gossip convergence under partitions
Counter	Challenge #4 (g-counter)	CRDT correctness, eventual consistency
Unique IDs	Challenge #2 (unique-ids)	ID generation without coordination
Kafka-style log	Challenge #5 (kafka)	Ordered delivery, offset tracking

Running Maelstrom Tests

# Build the Maelstrom wrapper
cargo build --release --bin maelstrom_gossip

# Run broadcast challenge (gossip convergence)
maelstrom test \
  -w broadcast \
  --bin target/release/maelstrom_gossip \
  --node-count 5 \
  --time-limit 20 \
  --rate 10 \
  --nemesis partition

# Run with stricter timing
maelstrom test \
  -w broadcast \
  --bin target/release/maelstrom_gossip \
  --node-count 25 \
  --time-limit 20 \
  --rate 100 \
  --nemesis partition \
  --latency 100

Maelstrom Output Analysis

After a Maelstrom run, analyze the results:

# Open results in browser
maelstrom serve

# Or parse JSON results directly
cat store/latest/results.edn

Key metrics to check:

• :valid? — Did all operations satisfy the consistency model?
• :lost-count — Messages that were sent but never delivered
• :stable-count — Messages that converged to all nodes
• :latency — Message propagation time distribution

Report format:

MAELSTROM REPORT — {workload}
═════════════════════════════
Nodes:            {count}
Duration:         {seconds}s
Operations:       {count}
Nemesis:          {partition|none|...}

Result:           {PASS|FAIL}

Consistency:
  Valid:          {yes|no}
  Lost messages:  {count} ({percentage}%)
  Stable:         {count} ({percentage}%)

Latency (ms):
  p50:  {value}
  p95:  {value}
  p99:  {value}

Convergence:
  Rounds to full convergence: {count}
  Expected (O(log n)):        {ceil(log2(nodes))}
  Status: {WITHIN BOUND | EXCEEDS BOUND}

{if FAIL}
Anomalies found:
  - {description of consistency violation}
  - {messages lost during partition}
{/if}

---

Mode B: Full Jepsen

Prerequisites

1. Docker or Vagrant for provisioning test nodes
2. Compiled gossip-rs binaries for the target platform
3. SSH access configured for test nodes
4. Jepsen Clojure framework (or the project's custom test harness)

Cluster Configuration

Based on Yuan et al. (OSDI 2014): 3 nodes suffice for reproducing most distributed failures. Use 5 nodes for partition tolerance testing.

Cluster topology:
  Node 1 (n1): gossip-rs worker + coordination backend
  Node 2 (n2): gossip-rs worker + coordination backend
  Node 3 (n3): gossip-rs worker + coordination backend
  [Node 4 (n4): optional, for partition quorum testing]
  [Node 5 (n5): optional, for partition quorum testing]

Jepsen Workloads

Workload	What It Tests	Evidence
Shard acquisition	Linearizability of acquire/release	Core correctness
Lease exclusivity	Only one worker holds lease at a time	etcd Jepsen 3.4.3
Checkpoint fence	Stale-epoch checkpoints are rejected	D2.14, Gray & Cheriton
Split correctness	Children cover parent range exactly	Shard coverage invariant
Concurrent acquisition	Two workers race for same shard	Fence monotonicity
Crash recovery	Worker crashes mid-checkpoint, restarts	Done-ledger durability
Full partition	Network split isolates subsets	Consensus safety
Asymmetric partition	A→B works, B→A drops	Lifeguard false positives
Process pause	GC-style pause during lease hold	etcd Jepsen pattern

Nemesis Configurations

Nemesis	Description	Level
partition-random-halves	Split cluster into two random halves	Standard
partition-random-node	Isolate a single random node	Standard
kill-random-node	SIGKILL a random node process	Standard
pause-random-node	SIGSTOP/SIGCONT a node (simulates GC pause)	Standard
clock-skew	Adjust system clock on random nodes	Advanced
combined	Multiple nemeses active simultaneously	Chaos

Running Full Jepsen Tests

# Provision test cluster (Docker)
cd jepsen/gossip-rs
docker compose up -d

# Run shard acquisition linearizability test
lein run test \
  --nodes n1,n2,n3 \
  --workload shard-acquisition \
  --nemesis partition-random-halves \
  --time-limit 60 \
  --concurrency 10

# Run lease exclusivity test (etcd failure pattern)
lein run test \
  --nodes n1,n2,n3 \
  --workload lease-exclusivity \
  --nemesis pause-random-node \
  --time-limit 120 \
  --concurrency 5

# Run combined chaos test
lein run test \
  --nodes n1,n2,n3,n4,n5 \
  --workload full-lifecycle \
  --nemesis combined \
  --time-limit 300 \
  --concurrency 20

Full Jepsen Output Analysis

JEPSEN REPORT — {workload}
══════════════════════════
Nodes:            {count}
Duration:         {seconds}s
Operations:       {count} ({ok}/{fail}/{info})
Nemesis:          {type}
Concurrency:      {threads}

Result:           {PASS|FAIL}

Linearizability:
  Valid history:  {yes|no}
  Checker:        {porcupine|elle|custom}
  Anomalies:      {count}

Invariant checks:
  ┌─────────────────────────────┬────────┬────────┐
  │ Invariant                   │ Status │ Checks │
  ├─────────────────────────────┼────────┼────────┤
  │ Lease exclusivity (S1)      │ PASS   │ 1234   │
  │ Fence monotonicity (S2)     │ PASS   │ 567    │
  │ Terminal irreversibility (S3)│ PASS   │ 89     │
  │ Shard coverage (S4)         │ FAIL   │ 12     │
  └─────────────────────────────┴────────┴────────┘

{if FAIL}
Failing operations:
  t=12.3s  :invoke  acquire-shard  shard-7  worker-2
  t=12.3s  :ok      acquire-shard  shard-7  worker-2  epoch=5
  t=12.5s  NEMESIS: partition [n1,n3] | [n2]
  t=13.1s  :invoke  checkpoint     shard-7  worker-1  epoch=4
  t=13.2s  :ok      checkpoint     shard-7  worker-1  ← VIOLATION: stale epoch accepted

Reproduction:
  lein run test --nodes n1,n2,n3 --workload {workload} --nemesis {nemesis} \
    --time-limit 60 --test-seed {seed}
{/if}

---

Correctness Properties

These properties must be verified by every Jepsen run. They correspond to the project's invariant catalog and are checked by specific verifiers.

Layer	Property	Checker	Reference
Coordination	Linearizability of shard operations	Porcupine / custom	Herlihy & Wing 1990
Coordination	Fence monotonicity, lease exclusivity	Custom invariant checker	D2.14, Gray & Cheriton 1989
Gossip	Eventual convergence (all nodes informed)	Custom convergence checker	Demers et al. PODC 1987
Gossip	O(log n) round convergence speed	Timing analysis	SWIM protocol, DSN 2002
Shard lifecycle	Terminal irreversibility	State machine invariant	D2 locked decisions
Shard lifecycle	Split coverage (no gaps, no overlaps)	Algebraic verification	Shard boundary spec
Persistence	Exactly-once commit protocol	Typestate + fault injection	Stripe idempotency pattern
End-to-end	No missed secrets, no duplicate reports	Diff against ground truth	Application-specific

---

Decision: Maelstrom vs Full Jepsen

Factor	Maelstrom	Full Jepsen
Setup time	Minutes	Hours
Run time	Seconds	Minutes-hours
Network realism	Simulated JSON	Real TCP/SSH
Fault injection	Network partitions	Network + process + clock + disk
Tests protocol logic	Excellent	Good
Tests integration	Poor	Excellent
Tests deployment	No	Yes
Flakiness	Low	Medium-high (CockroachDB lesson)
When to use	Development, per-feature	Pre-release, nightly

Rule of thumb:

• Start with Maelstrom during development
• Graduate to full Jepsen when the system is deployed and integrated
• Run both in CI (Maelstrom per-PR, Jepsen nightly)

---

Relationship to DST (/sim-run)

                    Speed           Realism          Bugs Found
                    ─────           ───────          ──────────
/sim-run Level 1    ████████████    ██               Logic bugs, state machine errors
/sim-run Level 2    ██████████      ████             Concurrency, timing, lease expiry
/sim-run Level 3    ████████        ██████           Cascading failures, Byzantine
/jepsen Maelstrom   ██████          ████████         Protocol convergence, message loss
/jepsen Full        ██              ██████████████   Integration, deployment, real OS

They test different things at different layers. Both are needed:

• DST finds logic bugs fast (thousands of seeds per second)
• Jepsen finds integration bugs that DST can't (real networking, real OS)

---

Related Skills

• /sim-run — In-process deterministic simulation (complementary)
• /sim-review — Verify code is DST-compatible
• /sim-scaffold — Generate simulation harnesses and Maelstrom wrappers
• /dist-sys-auditor — Validate distributed systems design decisions