What is an Assembly?

A Transloadit Assembly is one execution of Assembly Instructions on files that are uploaded, imported, or generated by the workflow itself. Each execution has a unique assembly_id that identifies it in later API requests.

Request + files
Results + status
A processing platform accepts an authenticated request, executes a workflow, and returns observable results. This diagram shows platform workflows broadly, not specifically Assemblies.

How Assemblies work

An Assembly is the runtime workflow created when a request combines Assembly Instructions with input sources: uploaded files, files fetched by import Steps, or files produced by Robots that need no input, such as HTML capture or media generation. The service resolves inputs, schedules Encoding Jobs, records intermediate state, and gathers outputs under one execution identity. It differs from a reusable Template, which stores configuration rather than representing a particular run. Applications use the Assembly boundary for monitoring, auditing, callback correlation, and result collection.

Key facts

  1. One Assembly can fan a source file into multiple processing branches, and downstream Steps may consume the named results of earlier Steps within that same execution.
  2. The execution identifier is the stable correlation key across submission responses, status retrieval, logs, and completion notifications; Step names identify work inside it.
  3. A successfully accepted Assembly can still finish with processing errors, so clients must inspect its terminal state and per-Step results instead of relying on HTTP acceptance alone.

When Assemblies matter

Store the assembly_id when a workflow must poll status, retrieve results, or correlate callbacks with a request. Losing that identifier makes later execution tracking and diagnosis more difficult.

Common use cases for platform workflows

These examples cover platform workflows broadly, not specifically Assemblies.

  • Running repeatable upload, import, processing, AI, storage, and notification pipelines.
  • Tracking long-running media work independently from an application request.
  • Referencing centrally stored credentials by name instead of sending storage secrets with each request.

Working with platform workflows

This guidance covers platform workflows broadly, not just Assemblies.

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.

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.

Before production

  1. Define authentication, authorization, idempotency, retries, and terminal error behavior.
  2. Observe queue time, execution time, callbacks, and partial results with stable identifiers.
  3. Exercise malformed, duplicate, interrupted, and unauthorized requests before launch.

Turn media knowledge into a working pipeline

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