Configuration is broken for some reason when the Data Action attempts to fetch trunk utilization stats during peak SGT hours. The integration fails with a 504 Gateway Timeout after 30 seconds, despite the API endpoint being responsive via curl. I have verified the OAuth token validity and network latency from our Singapore VPC. The payload includes a date range spanning 24 hours across 15 trunks. Is there a known payload size limit or specific header requirement for bulk BYOC metric retrieval that I might be missing in the request configuration?
Cause: The 24-hour date range for 15 trunks exceeds the Data Action’s processing threshold, triggering a 504 timeout.
Solution: Split the query into four 6-hour segments. This aligns with standard Performance dashboard aggregation logic and prevents backend overload. Verify queue activity metrics post-split to ensure data consistency.
It depends, but generally…
Splitting the time range helps, but the real bottleneck is often the WebSocket keep-alive dropping during aggregation.
Try adding X-Genesys-Client: jmeter to bypass some queue logic, or reduce the trunk count to 5 per request. The platform API struggles with bulk BYOC metrics when concurrent sessions spike in SG.
If I remember correctly… splitting the query is the right first step, but you need to watch the JMeter thread count closely. When testing bulk BYOC metric retrieval, the 504 error often masks a deeper issue with how the Data Action handles concurrent WebSocket connections. The platform has strict limits on simultaneous metric aggregation requests, especially when pulling from multiple trunks in a high-latency region like Singapore.
The suggestion above to split into 6-hour segments is good, but if you are still hitting timeouts, the issue is likely the request concurrency. The Data Action does not automatically batch these calls; it sends them sequentially or in small parallel bursts depending on the flow configuration. If your load test simulates high concurrent user traffic, the API rate limiter might be throttling the metric fetches before they even reach the aggregation engine.
Try reducing the number of trunks queried per Data Action call to 3-5, and increase the number of parallel threads in your JMeter test to simulate the load. This approach aligns better with the API’s throughput limits. Also, ensure you are using the correct OAuth scope. The analytics:metrics:read scope is required, but sometimes the token refresh latency adds to the timeout.
Here is a sample JMeter configuration for the Data Action:
| Parameter | Value |
|---|---|
| Thread Count | 50 |
| Ramp-Up | 10 seconds |
| Loop Count | 10 |
| Trunks per Request | 3 |
| Timeout | 45 seconds |
This setup helped me stabilize the metric aggregation in similar load tests. The key is to avoid overwhelming the single Data Action instance with too many trunks at once. If you still see 504 errors, check the Genesys Cloud logs for any rate-limiting warnings. The documentation suggests that bulk metric retrieval can be resource-intensive, so pacing the requests is critical.
It depends, but generally… splitting the query helps, but the real bottleneck is often the WebSocket keep-alive dropping during aggregation. Try adding X-Genesys-Client: jmeter to bypass some queue logic, or reduce the trunk count to 5 per request. The platform API struggles with bulk BYOC metrics when concurrent sessions spike in SG.