---
title: "Timeouts in Unqork"
slug: "timeouts-in-unqork"
status: "update"
updated: 2026-10-19T16:56:18Z
published: 2026-10-19T16:56:18Z
canonical: "docs.unqork.io/timeouts-in-unqork"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.unqork.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Timeouts in Unqork

A timeout occurs when a process exceeds a preset time limit. Timeouts can cause unexpected behavior, failed operations, and poor application performance. The issue becomes more significant as application scale increases.

This guide explains where timeouts occur in Unqork and how to prevent them.

## Workflow Timeouts

Automated workflow lanes have a **five-minute operation limit** in the Production environment. Each module included in the workflow has an individual **two-minute limit**. If either limit is exceeded, the workflow stops.

> [!NOTE]
> The five-minute and two-minute limits do not apply to QA or Staging environments, but workflows promoted to Production are subject to both limits.

### Preventing Workflow Timeouts

- **Process large datasets in batches**: Instead of processing all submissions simultaneously, break the dataset into smaller groups and process each group in sequence. Batches of 20 submissions are a reliable and efficient size. Larger batches risk overloading the server with simultaneous calls.
- **Use a Timer node for long-running operations**: A Timer node can extend an automated workflow beyond the default timeout window. Configure the Timer node on the task or Sub-Process node where the operation runs.

## Data Workflow Timeouts

Data Workflow components have a **two-minute execution limit**. Complex pipelines with large datasets are the most common cause of Data Workflow timeouts.

### Preventing Data Workflow Timeouts

- **Separate large Data Workflow components into smaller ones**: Each smaller pipeline runs more quickly and is less likely to time out. A modular approach also makes each step easier to troubleshoot.
- **Place Filter operators early in the pipeline**: Filtering submissions early reduces the dataset that later operators must process. This improves overall performance.
- **Use batch loops for large datasets**: Batch loops let a Data Workflow component process a subset of submissions at a time. The loop repeats until all submissions are handled, which keeps each iteration under the two-minute limit.

## Plug-In Component Timeouts

The **Set Timeout** setting in the Plug-In component controls the maximum time the component waits for a response from a called module or external service. The maximum configurable value is **300,000 milliseconds (5 minutes)**. If no value is set, the default timeout is 120,000 ms (2 minutes).

> [!WARNING]
> The Plug-In component timeout is a client-side timeout only. When the timeout is reached, the component stops waiting for a response, but the server-side module or external service might continue running. A triggered server-side module might run for longer than two minutes even though the Plug-In component has already stopped waiting.

External services have their own timeout limits. Always check the external service's documentation to verify its execution duration and timeout constraints.

## Database and Submission Performance

As submissions accumulate, query performance decreases if unnecessary submissions are not removed. The following practices keep queries fast:

- **Use indexed queries where possible**: Queries against indexed fields are significantly faster than unindexed queries, especially as submission counts grow.
- **Clean up unnecessary submissions regularly**: Build an automated workflow to delete submissions that are no longer needed. This keeps the database lean and prevents gradual performance degradation over time.

---

**Changelog**

| Date | Change |
| --- | --- |
| 2026-07-27 | Initial publication. |
| 2026-10-15 | Replaced em dashes with punctuation, converted the prevention tips to bulleted lists, removed a repeated sentence, and added See Also descriptions. |

The Production environment is the final stage of the development process. Use this environment to promote tested and functioning application so your end-user can interact with it.

Use your QA (quality assurance) environment to test applications to ensure reliability, security, and functionality before releasing them to the end-user.

The Staging environment is the first level of application building in Unqork. Use it to build, test, and style your applications.

A definition

A query lets you retrieve, access, manipulate, and delete data in a database.

A query lets you retrieve, access, manipulate, and delete data in a database.

The location of an element in an array.