Could someone clarify why the schedule export endpoint is failing?

Running into a 500 Internal Server Error when hitting /api/v2/wfm/schedules/export.

• Region: AU-East
• Python SDK: 1.0.3
• Payload: minimal date range, single user

Auth token is valid. Other WFM endpoints work fine. Just this one fails consistently.

import requests

headers = {
“Authorization”: f"Bearer {access_token}",
“Content-Type”: “application/json”
}

Explicitly define the export format and ensure timezone alignment

payload = {
“scheduleId”: “your_schedule_id”,
“startDate”: “2023-10-01T00:00:00.000Z”,
“endDate”: “2023-10-31T23:59:59.999Z”,
“format”: “csv”,
“timeZone”: “Australia/Sydney” # Match AU-East region context
}

response = requests.post(
“https://aueast.api.genesys.cloud/api/v2/wfm/schedules/export”,
headers=headers,
json=payload
)

if response.status_code == 202:
print(“Export initiated. Check Location header for job ID.”)
else:
print(f"Error: {response.status_code} - {response.text}")

- Verify the `scheduleId` parameter maps to an active schedule in the WFM module. A 500 error often surfaces when the backend attempts to resolve a schedule that exists in the UI but lacks underlying resource group associations.
- Inspect the date range format. The API expects ISO 8601 with explicit timezone offsets. Missing the `Z` or using a local time string without offset can trigger internal parsing failures in the AU-East region servers.
- Check the Python SDK version compatibility. Version 1.0.3 is quite old. The WFM APIs have undergone significant changes regarding export job handling. Upgrading to the latest `genesyscloud` SDK ensures the correct headers and payload structures are sent, avoiding deprecated endpoint behaviors.
- Review the WFM service account permissions. The token must have `wfm:schedule:read` and `wfm:export:write` scopes. Insufficient permissions sometimes return generic 500 errors instead of 403s in older SDK versions.
- Monitor the Genesys Cloud status page for AU-East. If the issue persists across multiple accounts, it may indicate a transient backend service degradation affecting the export pipeline specifically for that region.

the problem here is the endpoint expects a schedule id, not a user id. check the payload structure in the wfm api docs because 500s often stem from malformed request bodies.

You need to verify that the payload structure aligns precisely with the WFM API documentation, as 500 errors often indicate a server-side processing failure due to malformed input rather than authentication issues. The suggestion above regarding the schedule ID is correct, but there are additional configuration details that frequently cause this specific endpoint to fail.

The following steps outline the necessary corrections:

• Replace any user-level identifiers with the specific scheduleId obtained from the WFM schedule list endpoint.
• Ensure the startDate and endDate fields adhere to the ISO 8601 format, including the timezone offset (e.g., 2023-10-01T00:00:00+10:00 for AU-East).
• Explicitly define the export format in the headers or payload, as the default may not be compatible with all client libraries.
• Validate that the access token has the wfm:schedule:export permission, as missing scopes can sometimes manifest as internal errors in older SDK versions.

The Python SDK version 1.0.3 is known to have serialization quirks with complex date objects. It is advisable to construct the payload manually using standard JSON strings before passing it to the request method. This approach provides greater visibility into the exact structure being sent to the Genesys Cloud backend.

Additionally, consider checking the WFM configuration for any custom fields that might require specific handling during export. If the schedule contains custom attributes not defined in the export schema, the server may reject the request. A common fix is to simplify the schedule configuration temporarily to isolate whether the issue stems from the payload structure or the underlying schedule data.

Testing the request with a minimal, valid schedule ID and a narrow date range can help confirm if the issue persists. If the error continues, reviewing the server logs via the Genesys Cloud admin console may provide further insight into the specific validation failure.