Could someone explain why WebRTC softphone interactions are failing the chain of custody validation in our bulk export jobs? The audio files arrive in S3, but the associated JSON manifest is missing the required legal_hold_flag and media_type metadata.
We are using the v2 Recording API with the latest Genesys Cloud SDK. The Architect flow is set to capture digital channels, yet the export job returns a 400 error citing ‘missing_required_fields’ for these specific interaction types.
Voice recordings export correctly with all tags. This gap is blocking our discovery requests. Need a fix for the WebRTC metadata injection.
What’s happening here is that WebRTC sessions often bypass the standard media processing pipeline during high-concurrency load tests. When the system is under heavy load, the metadata injection service might lag behind the actual media stream ingestion. This delay causes the export job to pick up the audio file before the JSON manifest is fully populated with the legal_hold_flag. It is not necessarily a configuration error in the Architect flow, but rather a race condition triggered by throughput spikes.
To fix this, you should implement a wait condition in your export script. Before triggering the bulk export, query the GET /api/v2/recordings/recording/{id} endpoint. Check if the metadata field contains the required keys. If the response is incomplete, retry the check with an exponential backoff strategy. This ensures the manifest is synchronized with the media file. Also, verify that your JMeter thread groups are not saturating the WebSocket connection limits, as this can cause partial writes.
The main issue here is that WebRTC sessions often bypass the standard media processing pipeline during high-concurrency load tests. When the system is under heavy load, the metadata injection service might lag behind the actual media stream ingestion. This delay causes the export job to pick up the audio file before the JSON manifest is fully populated with the legal_hold_flag. It is not necessarily a configuration error in the Architect flow, but rather a race condition between media storage and metadata indexing.
Cause:
The asynchronous nature of Genesys Cloud’s recording engine means that for digital channels like WebRTC, the media file is written to S3 immediately upon session termination. However, the associated metadata object undergoes additional validation steps, including legal hold tagging. If the bulk export job initiates before this validation completes, the manifest lacks the required fields.
Solution:
Implement a polling mechanism or a delay in your export script. Check the status field of the recording resource via the API before attempting the bulk export. Ensure the status is completed and that the metadata object contains the legal_hold_flag. Alternatively, configure your Architect flow to trigger a webhook upon session end, which can then initiate the export process only after confirming metadata integrity. This ensures the chain of custody is maintained without manual intervention.
If I recall correctly, the discrepancy stems from how the Platform API handles asynchronous metadata propagation for WebRTC sessions compared to traditional PSTN calls. The issue is rarely a race condition in the storage layer, but rather a timing mismatch in the export job’s query execution. When you trigger a bulk export immediately after interaction completion, the legal_hold_flag and media_type attributes may not yet be persisted in the searchable index, even if the audio file is available in S3.
From an AppFoundry integration perspective, we often see this when clients attempt to pull recordings without implementing a retry mechanism with exponential backoff. The v2 Recording API returns a 200 OK for the export job creation, but the underlying manifest generation is still processing. To mitigate this, you should validate the interaction status before initiating the export. Specifically, check the state field of the recording object. If it is PROCESSING, delay the export trigger.
Here is a recommended logic flow for your SDK implementation:
import time
def wait_for_metadata_ready(recording_id, max_retries=5):
for attempt in range(max_retries):
recording = api_client.recordings_api.get_recording(recording_id)
if recording.state == "COMPLETED" and recording.legal_hold_flag is not None:
return True
time.sleep(2 ** attempt) # Exponential backoff
return False
Additionally, ensure your Architect flow explicitly sets the legal_hold_flag to true at the start of the interaction, not just at the end. If the flag is set late, the metadata injection service might miss the window for the initial manifest creation. Verify that your OAuth token has the recordings:read and recordings:export scopes. If the problem persists, check the Genesys Cloud logs for any 429 rate limits on the metadata update service during peak hours, as this can also delay attribute propagation.