wshobson/agents

saga-orchestration

Implement saga patterns for distributed transactions and cross-aggregate workflows.

Zobacz źródło

Jak używać

  1. Skopiuj polecenie instalacji i sprawdź źródła przed instalacją we własnym środowisku agenta.
  2. W oryginale sprawdź wymagane narzędzia, dane dostępowe i obsługiwane środowiska.
  3. Opisz dane wejściowe i oczekiwany rezultat; porównaj wynik ze źródłami.
npx skills add https://github.com/wshobson/agents --skill saga-orchestration

Przed rozpoczęciem

  • Instalacja nie obejmuje subskrypcji modelu, limitu API ani uprawnień do plików.
  • Gwiazdki i instalacje pokazują aktywność, a nie niezależny test jakości lub bezpieczeństwa.
Oryginalny dokument Skill

Treść z repozytorium z zachowaniem nagłówków, przykładów, kodu, tabel, linków i obrazów.

Saga Orchestration

Patterns for managing distributed transactions and long-running business processes without two-phase commit.

Inputs and Outputs

What you provide:

  • Service boundaries and ownership (which service owns which step)
  • Transaction requirements (which steps must be atomic, which can be eventual)
  • Failure modes for each step (transient vs. permanent, retry policy)
  • SLA requirements per step (informs timeout configuration)
  • Existing event/messaging infrastructure (Kafka, RabbitMQ, SQS, etc.)

What this skill produces:

  • Saga definition with ordered steps, action commands, and compensation commands
  • Orchestrator or choreography implementation for your chosen pattern
  • Compensation logic for each participant service (idempotent, always-succeeds)
  • Step timeout configuration with per-step deadlines
  • Monitoring setup: state machine metrics, stuck saga detection, DLQ recovery

When to Use This Skill

  • Coordinating multi-service transactions without distributed locks
  • Implementing compensating transactions for partial failures
  • Managing long-running business workflows (minutes to hours)
  • Handling failures in distributed systems where atomicity is required
  • Building order fulfillment, approval, or booking processes
  • Replacing fragile two-phase commit with async compensation

Detailed section: Core Concepts

Moved to references/details.md.

Detailed section: Templates

Moved to references/details.md.

Best Practices

Do's

  • Make every step idempotent — Commands may be replayed on broker reconnect
  • Design compensations carefully — They are the most critical code path
  • Use correlation IDs — The saga_id must flow through every event and log
  • Implement per-step timeouts — Never wait indefinitely for a participant reply
  • Log state transitions — saga_id, step_name, old_state → new_state on every change
  • Test compensation paths explicitly — Inject failures at each step index in integration tests

Don'ts

  • Don't assume instant completion — Sagas are async and may take minutes
  • Don't skip compensation testing — The rollback path is the hardest to get right
  • Don't couple services directly — Use async messaging, never synchronous calls inside a saga step
  • Don't ignore partial failures — A step that partially executed still needs compensation
  • Don't use a global timeout — Each step has different latency characteristics

Troubleshooting

Saga stuck in COMPENSATING state

A saga enters compensation but never reaches FAILED. This means a compensation handler is throwing an unhandled exception and never publishing SagaCompensationCompleted. Add dead-letter queue (DLQ) handling to compensation consumers and ensure every compensation action publishes a result event even when the underlying operation was already rolled back.

python
async def handle_release_reservation(self, command: Dict):
    try:
        await self.release_reservation(command["original_result"]["reservation_id"])
    except ReservationNotFoundError:
        pass  # Already released — treat as success
    # Always publish completion, regardless of outcome
    await self.event_publisher.publish("SagaCompensationCompleted", {
        "saga_id": command["saga_id"],
        "step_name": "reserve_inventory"
    })

Duplicate saga executions on restart

If your orchestrator service restarts mid-saga, it may replay events and re-execute already-completed steps. Guard every step action with an idempotency key — see Template 3 above.

Choreography saga losing events

In a choreography-based saga, a downstream service may miss an event if it was offline when published. Use a durable message broker (Kafka with replication, RabbitMQ with persistence) and store the current saga state in a dedicated saga_log table so you can replay from the last known good step.

Timeout firing before a slow-but-valid step completes

A step like create_shipment might take up to 15 minutes during peak load but your global timeout is 5 minutes, causing spurious compensation. Make step timeouts configurable per step type — see references/advanced-patterns.md for the TimeoutSagaOrchestrator implementation and the STEP_TIMEOUTS dict pattern.

Compensation order not matching execution order

When two steps both complete before a failure is detected, compensation must run in strict reverse order or you leave data in an inconsistent state. Verify that _compensate() iterates from current_step - 1 down to 0, and add an integration test that deliberately fails at each step index to confirm correct rollback order.


Advanced Patterns

The references/ directory contains production-grade implementations not needed for most sagas:

  • `references/advanced-patterns.md` — Full SagaOrchestrator abstract base class, TimeoutSagaOrchestrator with per-step deadlines, detailed bank transfer compensating transaction chain, Prometheus instrumentation, stuck saga PromQL alerts, and DLQ recovery worker.

Related Skills

  • cqrs-implementation — Pair sagas with CQRS for read-model updates after each step completes
  • event-store-design — Store saga events in an event store for full audit trail and replay capability
  • workflow-orchestration-patterns — Higher-level workflow engines (Temporal, Conductor) that build on saga concepts

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