Need some help troubleshooting an Architect flow JSON parse error (400) when migrating Zendesk ticket metadata. The ‘Create Interaction’ action fails repeatedly.
In Zendesk, custom fields were available immediately. Here, the schema seems stricter. Is there a specific JSON structure required for mapping legacy ticket data to interactions? Any examples would be appreciated.
Have you tried validating the JSON payload against the strict schema requirements for the ‘Create Interaction’ action, as custom field mappings often fail if the data types or nested structures don’t align perfectly with the Genesys Cloud API expectations? Ensure that all Zendesk custom fields are explicitly mapped to compatible interaction attributes and that the payload includes all required fields without any extraneous data.
have you tried wrapping the zendesk metadata in a strict json object? i saw similar 400s in my jmeter tests when the payload structure was loose. use this format: {“external_id”: “zd_123”, “attributes”: {“key”: “value”}}
What’s happening here is that the Genesys Cloud Performance dashboard often flags these 400 errors not as validation issues, but as structural mismatches in the data ingestion pipeline. When migrating from Zendesk, the strict schema enforcement in Architect requires explicit attribute mapping rather than loose key-value pairs. The previous suggestion regarding wrapping metadata is correct, but the structure must align precisely with the interaction definition in Genesys Cloud.
Ensure the payload separates the external identifier from the custom attributes. The platform expects a clean separation to populate the conversation detail views correctly. Use this structure:
{
"external_id": "zd_123",
"attributes": {
"zendesk_priority": "high",
"zendesk_type": "incident"
}
}
Verify that the attribute keys match the custom dimension definitions in the Admin console. Mismatches here cause the flow to reject the entire block, leading to the parse error. Check the queue activity logs to confirm the data is being ingested without truncation.
It depends, but generally… the issue stems from how the Architect flow handles nested objects versus flat key-value pairs during the initial ingest. When migrating from Zendesk, the strict JSON schema for the ‘Create Interaction’ action often rejects loose structures. The previous suggestion about wrapping metadata is spot on, but it needs to align precisely with the interaction definition.
{“error_code”: “INVALID_JSON_SCHEMA”, “message”: “Attribute ‘custom_fields’ is not defined in the target interaction type.”, “trace_id”: “abc-123”}
This error log is the smoking gun. The system expects explicit attribute mapping. Try restructuring the payload to match this format:
{
"external_id": "zd_ticket_98765",
"type": "email",
"attributes": {
"zendesk_priority": "high",
"zendesk_tags": ["billing", "urgent"]
}
}
Ensure that every custom field from Zendesk is explicitly mapped to a corresponding attribute in the Genesys Cloud interaction type. If the attribute doesn’t exist, create it first. The schema enforcement is stricter here than in legacy systems. Also, check for any null values in the Zendesk export. Nulls often break the parser. Replace them with empty strings or default values.
In my weekly schedule publishing workflows, I always validate the JSON structure against the API schema before hitting the endpoint. It saves a lot of headache. The documentation suggests using the ‘Validate JSON’ step in Architect to catch these issues early. It’s a small step, but it prevents the 400 errors from cascading.
The key is consistency. If the Zendesk data has mixed types, normalize them before sending. For example, if ‘priority’ is sometimes a string and sometimes an integer, convert it to a string. The Genesys Cloud API is particular about this. Once the structure is clean, the migration should proceed smoothly. This approach has worked well for similar data migrations in the past.