---
title: History and Logs
---

When you debug a Chatflow or Workflow, Dify automatically records detailed logs — both at the run level and for individual nodes. These logs make it easier to locate issues, understand how data flows through your workflow, and fine-tune performance.

<Info>
    To explore logs from real users after your application is published, check out [Logs and Annotation](/en/guides/annotation/logs).
</Info>

There are two dimensions of execution records for applications.

## Application Run History

Each time the application runs, a **Run History** is recorded. Each run is versioned and includes the application's **Conversation Log** as well as **Tracing Logs** for all nodes in that version. These logs are displayed chronologically and provide basic information about each interaction, including execution time, status, and a summary of input/output parameters.

![](https://assets-docs.dify.ai/2025/04/08a885858cfa6e8863faac891a5be319.png)

Click on any log entry to see the detailed execution view. Each run includes three major sections:

### RESULT

<Warning>
    The result section is available only for Workflow applications.
</Warning>

This section displays the final output result of the workflow — the content the user sees. If the workflow failed to execute, this section shows error messages and reasons.

![](https://assets-docs.dify.ai/2025/06/22856751d278ffad99d0533d2d96e125.png)

### DETAIL

This section includes comprehensive input parameters, metadata, and configuration context from the execution. You can inspect:

- The original input provided by the user
- Output generated by the application
- System-generated metadata

![](https://assets-docs.dify.ai/2025/06/882b783cd843ab666f5bc3c06f78521d.png)

### TRACING

This view provides in-depth visibility into the execution path and system behavior. It includes:

- **Node execution order**: The actual runtime order of each node in the workflow.
- **Data flow tracking**: How variables are passed and transformed between nodes. This can also be explored via the [Variable Inspector](/en/guides/workflow/debug-and-preview/variable-inspect).
- **Execution time analysis**: Time spent on each node helps identify performance bottlenecks.
- **Resource usage**: Token consumption, API calls, and cost-related data.
- **Error tracking**: Identify exactly which node failed and why.

![](https://assets-docs.dify.ai/2025/06/9e614ac01b1f6e0aeadda78c91ce93b7.png)

The tracing view is especially useful for debugging complex workflows and optimizing performance. If your workflow includes branches or loops, this view helps reveal the actual path taken during execution.

## Node Execution Logs

In addition to application-level logs, you can also inspect the **last run log** for each individual node directly within the workflow editor. Click **Last run** in the node’s config panel to view its most recent execution details, including input/output data.

![](https://assets-docs.dify.ai/2025/06/9c6e57236d85f426a930424863042d7d.png)

{/*
Contributing Section
DO NOT edit this section!
It will be automatically generated by the script.
*/}

---

[Edit this page](https://github.com/langgenius/dify-docs/edit/main/en/guides/workflow/debug-and-preview/history-and-logs.mdx) | [Report an issue](https://github.com/langgenius/dify-docs/issues/new?title=Documentation%20Issue%3A%20history-and-logs&body=%23%23%20Issue%20Description%0A%3C%21--%20Please%20briefly%20describe%20the%20issue%20you%20found%20--%3E%0A%0A%23%23%20Page%20Link%0Ahttps%3A%2F%2Fgithub.com%2Flanggenius%2Fdify-docs%2Fblob%2Fmain%2Fen/guides/workflow/debug-and-preview%2Fhistory-and-logs.mdx%0A%0A%23%23%20Suggested%20Changes%0A%3C%21--%20If%20you%20have%20specific%20suggestions%20for%20changes%2C%20please%20describe%20them%20here%20--%3E%0A%0A%3C%21--%20Thank%20you%20for%20helping%20improve%20our%20documentation%21%20--%3E)
