Distributed Systems Patterns

Comprehensive patterns for building reliable distributed systems. Each category has individual rule files in rules/ loaded on-demand.

Quick Reference

Category	Rules	Impact	When to Use
Distributed Locks	1	CRITICAL	Fencing tokens, owner validation; Redis/Redlock and Postgres advisory via upstream docs
Resilience	3	CRITICAL	Circuit breakers, retry with backoff, bulkhead isolation
Idempotency	1	HIGH	Idempotency keys; dedup and database-backed storage via upstream docs
Rate Limiting	2	HIGH	Token bucket, sliding window; SlowAPI integration via upstream docs
Edge Computing	2	HIGH	Edge workers, V8 isolates, CDN caching, geo-routing
Event-Driven	2	HIGH	Event sourcing, CQRS, transactional outbox, sagas

Total: 11 rules across 6 categories. Removed topics point at first-party sources in Upstream coverage; ork-specific scars live in ${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/references/ork-delta.md.

Quick Start

# Redis distributed lock with Lua scripts
async with RedisLock(redis_client, "payment:order-123"):
    await process_payment(order_id)

# Circuit breaker for external APIs
@circuit_breaker(failure_threshold=5, recovery_timeout=30)
@retry(max_attempts=3, base_delay=1.0)
async def call_external_api():
    ...

# Idempotent API endpoint
@router.post("/payments")
async def create_payment(
    data: PaymentCreate,
    idempotency_key: str = Header(..., alias="Idempotency-Key"),
):
    return await idempotent_execute(db, idempotency_key, "/payments", process)

# Token bucket rate limiting
limiter = TokenBucketLimiter(redis_client, capacity=100, refill_rate=10)
if await limiter.is_allowed(f"user:{user_id}"):
    await handle_request()

Distributed Locks

Coordinate exclusive access to resources across multiple service instances.

Rule	File	Key Pattern
Fencing Tokens	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/locks-fencing-tokens.md	Owner validation, TTL, heartbeat extension

Redis single-node locks, Redlock quorum, and PostgreSQL advisory locks are first-party documented; see Upstream coverage.

Resilience

Production-grade fault tolerance for distributed systems.

Rule	File	Key Pattern
Circuit Breaker	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/resilience-circuit-breaker.md	CLOSED/OPEN/HALF_OPEN states, sliding window
Retry & Backoff	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/resilience-retry-backoff.md	Exponential backoff, jitter, error classification
Bulkhead Isolation	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/resilience-bulkhead.md	Semaphore tiers, rejection policies, queue depth

Idempotency

Ensure operations can be safely retried without unintended side effects.

Rule	File	Key Pattern
Idempotency Keys	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/idempotency-keys.md	Deterministic hashing, Stripe-style headers

Event-consumer dedup and database-backed idempotency storage follow the Stripe pattern; see Upstream coverage.

Rate Limiting

Protect APIs with distributed rate limiting using Redis.

Rule	File	Key Pattern
Token Bucket	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/ratelimit-token-bucket.md	Redis Lua scripts, burst capacity, refill rate
Sliding Window	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/ratelimit-sliding-window.md	Sorted sets, precise counting, no boundary spikes

SlowAPI + Redis wiring and tiered limits are first-party documented; see Upstream coverage.

Edge Computing

Edge runtime patterns for Cloudflare Workers, Vercel Edge, and Deno Deploy.

Rule	File	Key Pattern
Edge Workers	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/edge-workers.md	V8 isolate constraints, Web APIs, geo-routing, auth at edge
Edge Caching	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/edge-caching.md	Cache-aside at edge, CDN headers, KV storage, stale-while-revalidate

Event-Driven

Event sourcing, CQRS, saga orchestration, and reliable messaging patterns.

Rule	File	Key Pattern
Event Sourcing	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/event-sourcing.md	Event-sourced aggregates, CQRS read models, optimistic concurrency
Event Messaging	${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/rules/event-messaging.md	Transactional outbox, saga compensation, idempotent consumers

Upstream coverage (do not restate)

These topics were removed from this skill on 2026-07-31 (wrap-plus-delta thinning) because a first-party source maintains them. Consult the source; do not re-add tutorials here. Ork-specific scars for these topics live in ${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/references/ork-delta.md.

Topic	First-party source
Redis single-node locks, Redlock algorithm and quorum	https://redis.io/docs/latest/develop/use/patterns/distributed-locks/
PostgreSQL advisory locks (session and transaction level)	https://www.postgresql.org/docs/current/explicit-locking.html#ADVISORY-LOCKS
Circuit breaker pattern, thresholds, setup and rollout guides	https://learn.microsoft.com/azure/architecture/patterns/circuit-breaker
Bulkhead pattern deep dive (thread pool, semaphore, tiers)	https://learn.microsoft.com/azure/architecture/patterns/bulkhead
Retry strategies, exponential backoff, jitter, retry budgets	https://aws.amazon.com/blogs/architecture/exponential-backoff-and-jitter/ and https://tenacity.readthedocs.io
HTTP and LLM provider error classification (retryable vs not)	https://docs.claude.com/en/api/errors and https://platform.openai.com/docs/guides/error-codes
Idempotency keys, request dedup, database-backed idempotency	https://docs.stripe.com/api/idempotent_requests
Token bucket algorithm and Redis rate-limiting patterns	https://redis.io/glossary/rate-limiting/
FastAPI distributed rate limiting (SlowAPI middleware, tiers)	https://slowapi.readthedocs.io/
LLM fallback chains, provider failover, cost tracking	https://vercel.com/docs/ai-gateway; model ids and pricing at https://docs.claude.com/en/docs/about-claude/pricing

Key Decisions

Decision	Recommendation
Lock backend	Redis for speed, PostgreSQL if already using it, Redlock for HA
Lock TTL	2-3x expected operation time
Circuit breaker recovery	Half-open probe with sliding window
Retry algorithm	Exponential backoff + full jitter
Bulkhead isolation	Semaphore-based tiers (Critical/Standard/Optional)
Idempotency storage	Redis (speed) + DB (durability), 24-72h TTL
Rate limit algorithm	Token bucket for most APIs, sliding window for strict quotas
Rate limit storage	Redis (distributed, atomic Lua scripts)

When NOT to Use

No separate event-sourcing/saga/CQRS skills exist; they are rules within distributed-systems. But most projects never need them.

Pattern	Interview	Hackathon	MVP	Growth	Enterprise	Simpler Alternative
Event sourcing	OVERKILL	OVERKILL	OVERKILL	OVERKILL	WHEN JUSTIFIED	Append-only table with status column
Saga orchestration	OVERKILL	OVERKILL	OVERKILL	SELECTIVE	APPROPRIATE	Sequential service calls with manual rollback
Circuit breaker	OVERKILL	OVERKILL	BORDERLINE	APPROPRIATE	REQUIRED	Try/except with timeout
Distributed locks	OVERKILL	OVERKILL	BORDERLINE	APPROPRIATE	REQUIRED	Database row-level lock (SELECT FOR UPDATE)
CQRS	OVERKILL	OVERKILL	OVERKILL	OVERKILL	WHEN JUSTIFIED	Single model for read/write
Transactional outbox	OVERKILL	OVERKILL	OVERKILL	SELECTIVE	APPROPRIATE	Direct publish after commit
Rate limiting	OVERKILL	OVERKILL	SIMPLE ONLY	APPROPRIATE	REQUIRED	Nginx rate limit or cloud WAF

Rule of thumb: If you have a single server process, you do not need distributed systems patterns. Use in-process alternatives. Add distribution only when you actually have multiple instances.

Anti-Patterns (FORBIDDEN)

# LOCKS: Never forget TTL (causes deadlocks)
await redis.set(f"lock:{name}", "1")  # WRONG - no expiry!

# LOCKS: Never release without owner check
await redis.delete(f"lock:{name}")  # WRONG - might release others' lock

# RESILIENCE: Never retry non-retryable errors
@retry(max_attempts=5, retryable_exceptions={Exception})  # Retries 401!

# RESILIENCE: Never put retry outside circuit breaker
@retry  # Would retry when circuit is open!
@circuit_breaker
async def call(): ...

# IDEMPOTENCY: Never use non-deterministic keys
key = str(uuid.uuid4())  # Different every time!

# IDEMPOTENCY: Never cache error responses
if response.status_code >= 400:
    await cache_response(key, response)  # Errors should retry!

# RATE LIMITING: Never use in-memory counters in distributed systems
request_counts = {}  # Lost on restart, not shared across instances

Detailed Documentation

Resource	Description
${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/scripts	Templates: lock implementations, circuit breaker, rate limiter
${CLAUDE_PLUGIN_ROOT}/skills/distributed-systems/references/ork-delta.md	Ork-specific scars and house decisions kept after the wrap-plus-delta thinning

Related Skills

• caching - Redis caching patterns, cache as fallback
• background-jobs - Job deduplication, async processing with retry
• observability-monitoring - Metrics and alerting for circuit breaker state changes
• error-handling-rfc9457 - Structured error responses for resilience failures
• auth-patterns - API key management, authentication integration