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A Saga coordinates a business workflow across microservices by breaking it into local transactions, each committed by the service that owns the data. When a later step fails, the workflow can retry or move forward, or invoke compensating business actions for completed steps. Compensation is not a rollback: each service’s earlier commit remains real, and the workflow must manage intermediate states and recovery explicitly.
How a Saga works
A Saga links local transactions into one business process without requiring a single database transaction across all participating services. Each service commits its own change and signals the next step with an event or message. The workflow’s coordination logic tracks what has happened and determines what should happen next.
Consider an order that needs inventory and payment before it can proceed to shipping:
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- Reserve inventory and signal that the reservation succeeded.
- Process payment and signal the result.
- Continue to shipping if the required steps succeed.
If payment is rejected after inventory has been reserved, the workflow can issue business actions to release that inventory and update the order’s state. A temporary service outage, by contrast, may call for retrying the payment step or continuing forward after recovery. The appropriate response depends on the failure and the business rules, not on a universal Saga rollback procedure. Microservices.io’s Saga pattern reference and AWS Prescriptive Guidance describe this local-transaction and recovery model.
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What compensation can—and cannot—do
A compensating transaction is a new business action intended to counteract an earlier action. Releasing reserved stock can counter a reservation; it does not erase the reservation transaction from the inventory service’s history. Compensation therefore differs from an ACID rollback, which can undo uncommitted work within a transaction.
Not every action can be reversed. A notification already sent or a shipment already dispatched may be impossible to undo in the ordinary sense. Microsoft’s Saga guidance distinguishes three useful transaction roles:
- Compensable transactions: completed actions for which the workflow can define a business-level counteraction.
- Pivot transaction: the point of no return, after which the workflow is committed to completing forward rather than compensating earlier steps.
- Retryable transactions: steps that should eventually succeed after the pivot; make these idempotent so retries do not duplicate their business effects.
Compensation itself can fail. Define what operators or the business should do if an undo action cannot complete, rather than assuming every process has a fully automatic reversal.
Choreography or orchestration?
Both styles coordinate local transactions, but they place responsibility for choosing the next step differently. The right choice depends on workflow complexity, participant count, coupling, visibility needs, and who will operate the system. Microsoft’s comparison of Saga coordination styles outlines the tradeoffs.
| Decision factor | Choreography | Orchestration |
|---|---|---|
| Who selects the next step? | Participants publish and consume domain events; there is no central controller directing the flow. | An orchestrator tracks workflow state and tells participants which operation to perform. |
| Best fit | Relatively simple workflows with few participants. | More complex workflows or those needing centralized visibility and control. |
| Key advantage | No dedicated coordinator is needed; responsibility is distributed. | The workflow is explicit, separating coordination from participant logic. |
| Main cost | As steps grow, event dependencies can make the flow harder to understand and test; cyclic dependencies are possible. | Coordination logic adds complexity, and the orchestrator becomes a critical component that must be resilient. |
When choreography is a sensible fit
Choose choreography when the flow is short enough that event relationships remain understandable and no central view of the entire process is essential. Keep event ownership and participant behavior clear: as each service reacts to other services’ events, the end-to-end workflow can become difficult to trace or change.
When orchestration is a sensible fit
Choose orchestration when the process has many steps, branching or recovery paths, or a need for a visible workflow state. A coordinator makes the sequence explicit, but it also needs monitoring, failure handling, and resilience because participants depend on it to direct work.
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Consistency and isolation are not automatic
A Saga coordinates changes across service-owned databases without one global database transaction. It does not provide global ACID isolation. While a workflow is running, other requests may observe intermediate states—for example, an order awaiting payment after inventory has been reserved.
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- Semantic locks: mark a resource as being processed so conflicting operations can be restricted.
- Commutative updates: structure changes so their order does not alter the correct result, where the business rules allow it.
- Rereading values: check current state before acting on information that may have become stale.
- Version checks: reject or reconcile updates based on an outdated version.
These are different tools for different anomaly risks. Select them against the invariants the business must preserve; a Saga alone does not choose the required consistency policy.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Design and operate the workflow deliberately
Before implementation, specify the transaction sequence, failure paths, and operational evidence needed to understand a workflow’s outcome. A practical design checklist is:
- Define each local transaction and handoff. For every step, name the service-owned change and the event or command that triggers the next step.
- Classify each action. Decide whether it is compensable, irreversible, a pivot, or retryable, and write down the actual business effect of its compensation.
- Make repeated execution safe. Participants should be idempotent so duplicate messages, transient failures, or coordinator recovery do not duplicate business effects. AWS calls out idempotency as a Saga participant requirement in its implementation guidance.
- Protect the database-to-message handoff. A service can commit a database change and fail before publishing the event that advances the workflow. Consider patterns such as the transactional outbox or event sourcing to address this reliability problem; they are implementation options, not features a Saga supplies automatically. Microservices.io’s reference discusses this concern.
- Tell callers how to learn the outcome. A long-running workflow may return an identifier that callers can use to poll status, or send a completion notification.
- Make progress diagnosable. Track workflow state and use logs, distributed tracing, and correlation identifiers to locate the failed step and determine whether retry or compensation is underway.
- Plan for incomplete recovery. Define handling for failed compensation, exhausted retries, and manual recovery; automatic restoration is not guaranteed.
An orchestration example with AWS Step Functions
AWS Prescriptive Guidance presents AWS Step Functions as one option for orchestrating a Saga across multiple databases. Its example coordinates order placement, inventory updates, and payment, with compensating actions such as reverting inventory or removing an order after a failure. This is an AWS-specific implementation example, not a requirement of the Saga pattern; choreography or another orchestration mechanism may suit a different system.
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