What is Assembly Replay?
Transloadit Assembly Replay re-executes an Assembly within 24 hours when its uploads succeeded and its Instructions were saved in a Template. It occurs automatically for `ASSEMBLY_CRASHED` and can be triggered manually.
How Assembly Replay works
Replay creates another processing attempt from an eligible recent execution without transferring its successfully received sources again. It relies on saved Template configuration, separating recoverable processing work from upload transport. Automatic replay addresses a crashed execution, while manual replay gives an operator explicit retry control. The mechanism belongs in failure recovery, but consumers must treat the new run as a distinct execution with its own outcome.
A client authenticates and submits files or references together with workflow instructions. The platform validates the request, schedules dependent operations, records state transitions, and exposes results through a response, polling endpoint, or notification.
Platform concepts become reliable only when their lifecycle is explicit. Authentication, idempotency, retries, timeouts, observability, quotas, and terminal states should be designed together rather than added after failures occur.
Key facts
- 1Eligibility depends on successful original uploads, Template-backed Instructions, and the 24-hour replay window; it is not a general archive restore mechanism.
- 2The replayed work receives a new execution context, so systems should preserve the relationship to the original while tracking the new Assembly identifier independently.
- 3External inputs or destinations can change between attempts, making replay non-deterministic when a Step reads mutable remote state or writes to a non-idempotent target.
When Assembly Replay matters
Replay an eligible Assembly when processing failed but re-uploading the original files would be wasteful. Confirm the Template is still appropriate, because changed external state may alter the new results.
- Running repeatable upload, import, processing, AI, storage, and notification pipelines.
- Tracking long-running media work independently from an application request.
- Applying credentials, quotas, retries, and error policies consistently across integrations.
Working with platform at scale
Guidance that holds across every platform term in this glossary, not just Assembly Replay.
What you gain
- Reusable workflows separate application intent from processing infrastructure.
- Stable job identifiers and lifecycle events improve observability and recovery.
- Managed queues and workers let products scale without embedding every media tool.
What it costs
- Synchronous responses are simple but keep connections open while long work executes.
- Aggressive retries improve recovery from transient faults but can duplicate work or overload a dependency.
- Higher concurrency reduces queue time until resource contention or a downstream limit becomes the bottleneck.
Answer these before production
- 1Define authentication, authorization, idempotency, retries, and terminal error behavior.
- 2Observe queue time, execution time, callbacks, and partial results with stable identifiers.
- 3Exercise malformed, duplicate, interrupted, and unauthorized requests before launch.
How Transloadit helps with Assembly Replay
When Assembly Replay is relevant to your workflow, you can hand the surrounding platform work to Transloadit instead of maintaining the processing stack yourself. Transloadit models file workflows as reusable Assembly Instructions. Upload, import, processing, AI, storage, delivery, status updates, and error handling can be composed without operating the underlying media tools yourself.
Support for a specific codec, container, parameter, or combination can vary by Robot and processing stack. Check the linked documentation for the exact inputs and outputs available for your use case.