Could someone clarify why the ‘Create Ticket’ Data Action returns a 500 Internal Server Error when mapping the Zendesk ‘comment’ field to the Genesys Cloud interaction body? The JSON payload looks valid according to the Swagger docs, but Architect fails immediately upon execution. This is confusing because Zendesk handles nested JSON in ticket notes without issue, so I expected a smoother transition to the Genesys Cloud API structure.
Here is the exact error response from the Data Action debug log: {“error_code”: “internal_server_error”, “message”: “Failed to parse request body”, “details”: “Invalid JSON structure at path $.attributes.custom_fields”}. I have verified that the custom fields exist in both systems and the OAuth token has the correct scopes. The flow works perfectly for simple text fields, but breaks as soon as I try to map the complex ticket attributes. Is there a specific transformation block I need to add before the Data Action to flatten the Zendesk JSON structure?
The 500 error typically stems from a schema mismatch in the body field rather than the Zendesk source structure itself. Genesys Cloud’s POST /api/v2/interactions endpoint expects the body to be a strictly defined object containing type and content, not a raw string or nested Zendesk note object. When the Data Action passes a complex JSON object directly into the body parameter without flattening it, the Genesys API rejects it at the validation layer, resulting in an internal server error from the integration middleware.
Adjust the Data Action mapping to ensure the payload adheres to this structure:
{
"body": {
"type": "text",
"content": "{{trigger.zendesk.comment}}"
},
"channels": [
{
"type": "web",
"address": "{{trigger.zendesk.email}}"
}
]
}
If the Zendesk comment contains HTML or special characters, the content field must be URL-encoded or stripped of markup before insertion. The Genesys Cloud API does not automatically sanitize HTML in interaction bodies for security reasons. Ensure the Data Action’s target endpoint is set to https://api.mypurecloud.com/api/v2/interactions and that the authentication header uses a valid OAuth token with interaction:write scope.
Additionally, verify the Data Action’s error handling configuration. If the Zendesk ticket has multiple comments, the trigger might be passing an array instead of a single string. Use a Data Action expression to select the latest comment: {{trigger.zendesk.comments[-1].body}}. This prevents type errors when the API expects a string but receives a list object. Cross-reference the Genesys Cloud API documentation for the InteractionCreateRequest model to confirm all required fields are present, as missing optional fields can sometimes cause unexpected 500 errors if the integration layer expects specific defaults.
You need to wrap the Zendesk comment payload in a specific structure before passing it to the Genesys Cloud Data Action. The 500 error occurs because the platform API rejects complex nested objects in the body field when the schema expects a flat or specifically typed object.
{
"body": {
"type": "text/plain",
"content": "{{zen_comment_value}}"
}
}
When integrating Zendesk with Genesys Cloud via AppFoundry or custom Data Actions, the comment field from Zendesk often arrives as a rich text fragment or a deeply nested JSON object containing formatting tags. The Genesys Cloud POST /api/v2/interactions endpoint requires the body parameter to be an object with explicit type and content properties. If you map the raw Zendesk comment directly, the serializer fails, resulting in a server-side error.
Ensure you are using a Data Action step to flatten the Zendesk comment into a simple string before mapping it to the content field. Additionally, verify that your OAuth token has the interaction:write scope. Multi-tenant setups often suffer from scope drift, where the token used for authentication lacks the specific permissions required for interaction creation.
Check the Architect logs for any serialization errors. If the payload exceeds 10KB, consider truncating the comment in a pre-processing step. Rate limiting can also trigger 500 errors if the Data Action is called in a loop without proper throttling. Implementing a retry mechanism with exponential backoff helps mitigate transient failures during high-volume ticket creation. Always test the payload in Postman first to isolate whether the issue lies with the Data Action mapping or the underlying API endpoint.