WFGY/ProblemMap/GlobalFixMap/Cloud_Serverless/stateless_kv_queue_patterns.md

Stateless KV and Queue Patterns — Guardrails

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Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

A compact repair guide for serverless and edge stacks that must survive retries, bursts, out-of-order events, and duplicate webhooks. All patterns map back to Problem Map pages with measurable targets.

When to use this page

• Functions are stateless and scale horizontally.
• You see duplicate side effects on retries or webhook storms.
• Event order is not guaranteed and you must reconcile late arrivals.
• Writes cross multiple systems and need exactly-once semantics in practice.
• You need queues for backpressure without introducing deadlocks.

Open these first

• Visual recovery map: rag-architecture-and-recovery.md
• Contracts for small, auditable payloads: data-contracts.md
• Live ops and tracing: ops/live_monitoring_rag.md · ops/debug_playbook.md
• Boot order and deploy hazards: bootstrap-ordering.md · deployment-deadlock.md · predeploy-collapse.md
• Storm control pattern: patterns/pattern_bootstrap_deadlock.md

Acceptance targets

• Duplicate side-effects ≤ 0.1 percent across 1 million events.
• P99 queue latency ≤ 5 seconds after backpressure is active.
• Lock contention ≤ 3 percent with P95 wait ≤ 100 ms.
• Exactly-once at the boundary: user-visible action never applied twice even with three retries.
• Audit fields present on every message: event_id, source_id, revision, index_hash, dedupe_key, attempt.

---

Fix in 60 seconds

1. Define the dedupe key dedupe_key = sha256(source_id + revision + index_hash) Store in kv/done/<dedupe_key> = {ts, status, result_id} with TTL ≥ max replay window. Contract: data-contracts.md

2. Use a leased lock for single-writer sections kv/lock/<resource> with value token and ttl = function_timeout - safety_margin. Only the holder token can release. On expiry, another worker may acquire.

3. Put work behind a queue with visibility timeout Visibility timeout must be greater than max_processing_time + jitter. Failed items go to DLQ after N attempts. Record attempt in the message.

4. Outbox before publish Write business record and outbox/<txid> in the same atomic store. A relay process reads the outbox and publishes to the queue. Consumers use inbox/<txid> as the dedupe ledger.

5. Idempotent side-effects Before any external call, check kv/done/<dedupe_key>. If present, return the prior result. If absent, perform the effect then write the ledger.

---

Typical breakpoints → exact fix

• Webhook storms and double billing Missing dedupe ledger or TTL too short. Add kv/done/<dedupe_key> with long TTL and verify before charge. Open: ops/live_monitoring_rag.md

• Queue grows without bound No backpressure or priority lanes. Add consumption quotas per tenant and a high-watermark shed rule. Open: ops/debug_playbook.md

• Deadlocks when multiple writers compete Locks without leases or cross-locks across resources. Replace with single resource lock per critical section and time-boxed lease. Open: deployment-deadlock.md

• Out-of-order events overwrite newer state Apply a monotonic guard: reject if revision_in_msg < current_revision. Keep a compaction job to expire stale inbox entries. Open: bootstrap-ordering.md

---

Minimal recipes you can copy

A) Leased lock with safe release

acquire(key, ttl):
  token = random()
  ok = kv.setnx("lock/"+key, token, ttl)
  return ok ? token : null

release(key, token):
  if kv.get("lock/"+key) == token:
    kv.del("lock/"+key)

B) Idempotency ledger

dedupe_key = sha256(source_id + revision + index_hash)

if kv.get("done/"+dedupe_key):
  return replay(kv.get("done/"+dedupe_key))

result = do_side_effect()
kv.set("done/"+dedupe_key, {ts: now(), result_id: result.id}, ttl=30d)
return result

C) Outbox and inbox

// producer tx
db.begin()
db.insert("orders", row)
db.insert("outbox", {txid, payload})
db.commit()

// relay
for msg in db.scan("outbox"):
  queue.send({txid, payload})
  db.delete("outbox", msg.txid)

// consumer
if kv.get("inbox/"+txid): return
handle(payload)
kv.set("inbox/"+txid, now(), ttl=30d)

D) Token bucket for backpressure

bucket = "q_tokens/"+tenant
tokens = kv.incrby(bucket, 1, ttl=1s)
if tokens > limit: requeue_with_delay()

---

Observability you must add

• queue_depth, age_of_oldest, consume_rate, requeue_rate, dlq_rate.
• lock_acquired, lock_conflicts, lock_wait_ms_p95.
• dedupe_hits, double_effects_detected.
• Trace fields on every event: event_id, dedupe_key, attempt, tenant, route.

Verification

• Fire a test that sends the same event 5 times with random delays. Only one side-effect is applied.
• Kill a worker mid-flight. Message becomes visible again and finishes once.
• Reorder by sending revision=1,3,2. State ends at 3. Open: eval/eval_rag_precision_recall.md

When to escalate

• If locks create long waits or cascades, redesign the critical section into outbox plus eventual reconciliation.
• If queue depth oscillates, split lanes by priority or tenant and apply quotas. Open: ops/live_monitoring_rag.md

---

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