What’s the best way to reconcile the entity count differences when querying active sessions via the Genesys Cloud Platform APIs?
I am maintaining a comprehensive Postman collection for validating our contact center’s real-time state against historical reports. I have a Newman CLI script that runs hourly to audit data integrity. The script performs two parallel requests:
- GET /api/v2/conversations
- A query to the Analytics API for real-time interaction counts (note: there is no direct “summary” endpoint for real-time conversation counts in the current spec, so we are relying on the reporting layer’s availability and export capabilities to cross-reference).
The issue is that the response from the Conversations API returns a list of conversation objects with a total count of 142. However, the Analytics reporting layer shows an interaction count of 138 for the same exact second.
My pre-request script logs the timestamp to millisecond precision. Both requests are fired within a 50ms window. I suspect the Analytics API is aggregating data from a different source or has a slight latency in the real-time buffer, but the documentation implies both should reflect the current state of the platform.
Is there a specific filter or query parameter I am missing on the /api/v2/conversations endpoint to exclude certain types of interactions (like internal-only or test conversations) that might be inflating the count? Or is the Analytics API excluding completed-but-not-yet-archived conversations?
I need a deterministic way to validate that my monitoring dashboard (which uses the Conversations API) matches the reporting layer (which uses the Analytics API). The 4% variance is triggering false positives in our alerting pipeline.
Thanks for the help.