---
name: saga-orchestration
description: Implement saga patterns for distributed transactions and cross-aggregate workflows. Use this skill when implementing distributed transactions across microservices where 2PC is unavailable, designin...
---

# 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