Could someone explain the discrepancy between the screen recording metadata and the actual call disposition data when using BYOC trunks? We have configured screen pop recordings to trigger via Data Actions upon call completion, but the recording files often lack the correct callId linkage in the storage bucket, especially during failover events. The recordings are stored correctly, but the recording_id returned by the API does not match the call_uuid in the analytics report for 15% of our trunk traffic. This breaks our post-call quality assurance workflow. We are using the latest Integrations API version, and the Data Action payload includes the correct trunk ID and carrier name. However, when the primary carrier drops and the call routes to the secondary BYOC trunk, the screen recording service seems to lose the context of the original call_uuid. The error log shows a 404 Not Found when attempting to fetch the recording metadata for these specific calls. Is there a known limitation with screen recording metadata synchronization during trunk failover, or is this a configuration issue with how we are passing the call context in the Data Action payload? How can we ensure consistent call_uuid mapping in screen recordings across BYOC trunk failover scenarios?
The problem here is the Data Action execution timing. Ensure the screen recording metadata update happens in a separate, delayed flow triggered by the call disposition event, not the immediate completion hook.
This seems like a standard race condition where the recording file lands in storage before the metadata index is fully populated. The previous suggestion about delaying the flow is correct, but simply adding a delay isn’t enough. You need to handle the 404 or empty response from the recording API during high-concurrency periods. If you trigger the metadata sync immediately after call completion, the system might not have finished writing the final segment of the recording. This is especially true during failover when the trunk status is fluctuating.
The safest approach is to implement a retry loop with exponential backoff in your Data Action script. Do not rely on a static sleep. Instead, poll the /api/v2/recordings/{recordingId} endpoint until the status changes from PENDING to COMPLETED. If the status remains PENDING after three retries, log the call_uuid to a separate queue for manual reconciliation. This prevents the Data Action from timing out and ensures the callId linkage is accurate.
Here is a simple pseudo-code structure for the retry logic. It checks the status and waits progressively longer between attempts. This handles the latency spikes common in BYOC environments without blocking the main thread indefinitely.
let maxRetries = 3;
let delay = 2000; // Start with 2 seconds
for (let i = 0; i < maxRetries; i++) {
let recordingStatus = await getRecordingStatus(recordingId);
if (recordingStatus === 'COMPLETED') {
break; // Success
}
await sleep(delay);
delay *= 2; // Exponential backoff
}
Be careful with the API rate limits here. If you have many concurrent calls ending, polling every recording can trigger 429 errors. Group the polling requests or add a jitter to the delay to avoid hammering the API. This setup worked for our load tests when we hit 500 concurrent calls.