Saga Orchestration

--- 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, designing compensating actions for failed order workflows that span inventory, payment, and shipping services, building event-driven saga coordinators for travel booking systems that must roll back hotel, flight, and car rental reservations atomically, or debugging stuck saga states in production where compensation steps never complete. --- # 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, comp