What is the Live Queue?
The Live Queue is Transloadit’s limited, configurable processing lane for Encoding Jobs that require near-real-time handling. Jobs exceeding the applicable capacity are directed to the Batch Queue.
How the Live Queue works
This processing lane serves direct-upload work ahead of nonurgent imported or explicitly batched jobs. It is shared across customers, while each workspace’s regional Priority Job Slots bound how much of its work can occupy the lane at once. Excess live jobs wait in a backup queue and return as their workspace releases slots. Operationally, queue residence, Robot execution time, and end-to-end Assembly duration are separate measurements and should be monitored independently.
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
- 1Direct uploads normally create Live Queue jobs, while import Robots normally use the Batch Queue; a step can also opt into batch treatment with its queue setting.
- 2Live work is prioritized over shared batch work, but priority does not mean unbounded parallelism because each active Robot consumes workspace slot capacity.
- 3Queue wait estimates are exposed by processing region and measured in seconds, which lets admission logic distinguish platform backlog from a slow individual encode.
When the Live Queue matters
Urgent workflows should reserve Live Queue capacity for jobs with meaningful latency requirements. Bursts beyond the configured limit increase waiting time because excess work runs through the Batch Queue.
- 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 the Live Queue.
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 the Live Queue
When the Live Queue 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.