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To resume a failed multi-step workflow without repeating completed steps, recover it from the orchestration system’s durable checkpoint or execution history—not by blindly rerunning the whole job. A durable workflow can replay its decisions using saved history and reuse recorded results for completed steps. The failed or interrupted operation may still run again, however, especially if it caused an external change before its success was recorded. Use idempotency protections or verify that change before retrying.

What “resume” means—and what it does not

Workflow platforms use recovery terms differently. A durable replay reconstructs the workflow’s decisions from saved history; a retry makes another attempt at work that did not complete. Resuming a suspended instance, restarting a failed instance, and starting a new execution are separate operations. Do not assume every platform can continue a failed run at precisely the step where it stopped.

For example, AWS Lambda Durable Execution documents replaying completed steps from checkpointed results while incomplete work may execute again (AWS Lambda: Idempotency). Azure Durable Functions’ documented HTTP resume action is specifically for a previously suspended orchestration, not a general “continue any failed run” control (Microsoft: HTTP APIs in Durable Functions).

Recover the run safely

  1. Identify the exact execution. Find its stable execution or instance ID and check whether it is running, suspended, failed, or complete. Those states may support different recovery operations.
  2. Inspect its history and failure. Determine which steps have durable completion records, which step failed, and the last error. Check that the input and workflow version are suitable for replay. In replay-based systems, workflow decisions must remain consistent with recorded history; see Microsoft’s Durable Orchestrations overview.
  3. Check whether the failed operation took effect. A read or repeat-safe upsert is usually safer to retry than a payment, one-shot message, or other external side effect. If the outcome is uncertain, query or reconcile the downstream system before another attempt.
  4. Use the platform’s supported recovery control. Apply its documented resume or retry operation and policy. If the platform only offers a restart, establish whether that creates a new execution and how it protects already-completed work from duplication.
  5. Verify the result. Confirm the new status, monitor the retried step, and check downstream state. An accepted recovery request is not proof that the workflow has succeeded.
  6. Keep an operational record. Note the execution ID, failed step, downstream outcome, idempotency key, and recovery action so later operators can distinguish a replayed result from a genuinely repeated side effect.

Protect side effects from duplicate attempts

Replay and retry can both lead to the same operation running more than once. AWS cautions that neither mechanism guarantees a step runs exactly once across an entire workflow (AWS Durable Execution: Idempotency and retries). Treat an uncertain operation as potentially completed until its outcome is checked.

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  • Use a stable idempotency key. Send the same key for every attempt of one logical operation, and follow the downstream service’s documented duplicate-request behavior. AWS advises creating the key inside the durable step so replay does not produce a different key. A duplicate-request response may indicate the first attempt succeeded; handle it according to that service’s documentation.
  • Prefer conditional writes or upserts. “Create if absent,” setting a known value, SQL conflict handling, and upserts keyed by a stable ID can make repetition safe. An unguarded insert or counter increment can change the result twice.
  • Make database checks atomic with writes. When you control the database, put the check and mutation in one transaction rather than separating them into steps that can race.
  • Deduplicate events by deterministic ID. Give a logical event a repeatable identifier and have consumers reject duplicates with that ID.
  • Use at-most-once attempts only when the trade-off is acceptable. AWS describes at-most-once-per-retry behavior, but a configured retry can still cause another attempt. In the documented SDK, constraining a step to one attempt end-to-end requires at-most-once semantics and no retry; that avoids automatic re-attempts at the cost of automatic recovery.

Compare recovery behavior before choosing a workflow platform

Evaluate the workflow type you will actually run, not just the product name. Ask these questions of its current documentation:

What to compare Question to ask
Persisted progress Are step outcomes saved, and are completed results reused on replay?
Recovery semantics Does the system replay workflow logic, retry incomplete activities, resume suspended instances, restart failed runs, or require a new execution?
Side-effect safety Can an activity run more than once? Are stable idempotency keys or conditional writes supported?
Retry controls Can retries be bounded, delayed, filtered by error type, or disabled for a particular step?
Operator visibility Can you query status and inspect history, step results, inputs, and failure details?
History and retention How long is execution history available, and does the answer differ by workflow type?

AWS Step Functions documents differences in execution guarantees and history behavior among Standard, asynchronous Express, and synchronous Express workflows. Check the current AWS Step Functions Developer Guide for the type and limits relevant to your design rather than assuming every workflow retains the same history or supports the same recovery behavior.

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Azure Durable Functions: verify a resume request

Azure’s HTTP API describes its resume operation as resuming a previously suspended orchestration. A successful HTTP 202 response means the request was accepted, not that the orchestration completed—or even that it has already reached the expected active state. Query the instance status afterward and confirm it is Running before monitoring subsequent work. The same API documentation describes the scope and response behavior: HTTP APIs in Durable Functions.

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AWS Durable Execution: replay is not a promise of one attempt

AWS Lambda Durable Execution documents that completed steps return checkpointed results without re-executing their step logic. Interrupted or incomplete work may execute again, so protect external changes with stable keys or another idempotency pattern. AWS also documents that execution-name idempotency applies to execution starts in the relevant context; do not assume it covers every invocation path, including all event source mapping behavior. See AWS Lambda: Idempotency and AWS Durable Execution: Idempotency and retries.

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