What is Async Mode?
Async Mode lets a client continue after its request or upload completes while Transloadit processes the Assembly separately. An Assembly Notification later delivers the results to the client’s back end.
How Async Mode works
Async Mode changes the request lifecycle, not the processing graph: the client is released once submission is complete while the Assembly continues on service infrastructure. Final data arrives through a backend notification rather than an interactive response held open for the full job. This avoids client and proxy timeouts for costly media work. The application must maintain durable correlation state and expose its own pending, succeeded, or failed job experience.
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
- 1The initial response confirms handoff rather than successful media output, so a user-facing system needs a separate state between accepted submission and terminal completion.
- 2Async operation requires a reachable server endpoint for results; a browser tab or mobile process is not a dependable notification receiver after the upload ends.
- 3Retries and out-of-order application events are normal distributed-system concerns, so the receiver should key updates by Assembly identity and reject stale state transitions.
When Async Mode matters
Choose Async Mode when processing may outlast an interactive request or should not block the client. The receiving endpoint must authenticate notifications and handle retries or duplicate deliveries safely.
- 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 Async Mode.
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 Async Mode
When Async Mode 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.