Troubleshooting AxiosError-500 Errors

If you encounter an AxiosError: 500, or a general “500 error,” while attempting to create or preview a Data Object in Assette, this typically signifies an internal server error. These errors can disrupt your workflow but are often resolvable through systematic troubleshooting. This article outlines the potential causes and actionable steps to help you identify and resolve the issue efficiently.

Why Does This Error Occur? #

An AxiosError: 500 occurs when the server fails to complete a request due to an unexpected condition. In the context of creating or previewing a Data Object in Assette, common root causes include:

• Incorrect or malformed Data Block or Data Object inputs: Missing fields, incompatible data types, or invalid configurations can trigger server exceptions.
• Unhandled exceptions: Specific combinations of data, transformation logic, or metadata may cause unexpected failures in data execution or rendering.
• Transformation logic errors: Python-based Transform Blocks with logic errors can fail silently until invoked in a Data Object preview.
• Infrastructure timeouts or memory overload: Especially when large datasets or complex logic is involved.

Step-by-Step Troubleshooting #

Step 1: Check Your Data Inputs #

Review Data Object Inputs:

• Confirm that all required fields in the Data Object are properly filled out.
• Look for extraneous characters, such as unescaped quotes, special symbols, or unsupported text encoding.
• Ensure that the Data Object configuration is complete, especially the selected Data Block and any parameters being passed into it.

Validate Data Formats:

• Confirm that all data values comply with expected formats:
  • Date fields should follow standard ISO formats (e.g., YYYY-MM-DD).
  • Numeric fields should not contain symbols or thousands separators.
  • Text fields should remain within expected length constraints.

Tip: If you’re passing user-entered filters or variables into a Data Block or Data Object, test with simplified or static values to isolate format-related errors.

Step 2: Refresh and Retry #

Refresh the Assette Interface:

• Refresh the page in your browser to clear any stale sessions.
• Consider clearing your browser cache and cookies to remove potentially corrupted local storage.
• Log out and log back into Assette to reinitialize your session.

Retry the Action:

• After refreshing, try to create or preview the Data Object again.
• If the error is intermittent, this may resolve transient backend issues.

Step 3: Test with a Different Browser #

To rule out client-side rendering or session issues:

• Attempt the same action in a different browser.
  Supported browsers include:
  • Google Chrome (latest version recommended)
  • Mozilla Firefox
  • Microsoft Edge
• Ensure browser extensions or developer tools are not interfering with request execution.

Step 4: Inspect the Underlying Data Block #

If the Data Object depends on a custom Data Block:

• Open the Data Block in Authoring Center and review the logic.
• If the block uses Python (e.g., in Transform or Decorator categories), check for:
  • Syntax errors
  • Null or empty values being passed into functions
  • API calls or external connections that may be failing silently

Use Preview with Data for the underlying Data Block to confirm that it executes correctly outside of the Data Object context.

Step 5: Use X-Ray to Analyze Dependencies #

Before contacting support, use X-Ray View to inspect the full structure and dependencies of the Data Object. This may reveal:

• Incorrect or misaligned references to other components
• Deprecated or unavailable Data Blocks
• Mismatches between input parameters and block expectations

This insight can significantly accelerate root cause identification.

Step 6: Contact Assette Support #

If the error persists after completing all of the above steps, contact Assette Support for further assistance. To expedite troubleshooting, include the following information:

• A description of the steps you followed that led to the error.
• Screenshots of the Data Object configuration and the AxiosError message.
• A timestamp of when the error occurred (with time zone).
• The name of the Data Object and associated Data Block (if applicable).
• Whether the issue occurs consistently or intermittently.

Support may request backend logs or perform a deeper review of component configurations on your behalf.