Could someone explain the correlation between WebRTC softphone connection instability and the resulting data gaps in the Performance Dashboard for our Europe/Paris queue? We are observing a specific pattern where agents using the standard Genesys Cloud softphone experience frequent disconnections, logged as SIP 408 Request Timeout or ICE Connection Failed in the conversation detail views, while those on BYOC trunks remain stable. This discrepancy is causing significant skew in our agent occupancy and handle time metrics within the custom analytics reports, as disconnected calls are often categorized differently or dropped from the active queue metrics entirely. The environment is running the latest Genesys Cloud release, and the issue persists despite standard network checks showing sufficient bandwidth. We need to understand if these WebRTC failures are being filtered out of the real-time queue activity views or if they are counted as abandoned interactions, thereby artificially inflating our abandonment rate. Clarification on how the Performance Dashboard ingests these specific WebRTC error codes versus standard SIP trunk failures would be invaluable for adjusting our service level calculations accurately.
I’d suggest checking out at the WebSocket keep-alive intervals in your JMeter test plan. If you’re hammering the signaling endpoints too hard, you’ll trigger rate limits that masquerade as ICE failures.
Check your WebSocket keep-alive configuration in the JMeter test plan. The suggestion above highlights a critical point about signaling endpoints. When you hammer these endpoints too aggressively, the platform enforces rate limits that often manifest as ICE Connection Failed errors rather than standard 429 responses. This creates a false positive for connection instability.
For our legal discovery exports, we see similar artifacts when bulk export jobs trigger during peak load. The metadata timestamps become inconsistent if the underlying WebRTC session drops unexpectedly. This complicates the chain of custody for digital channel recordings, particularly for WhatsApp and Web Chat sessions where session continuity is vital for audit trails.
Ensure your test script respects the Retry-After header values dynamically. A static delay often fails to account for the burst capacity of the signaling service. Aligning your JMeter pacing with the actual API rate limits prevents these spurious disconnections. This allows the Performance Dashboard to reflect true agent activity rather than testing artifacts.
Make sure you isolate the WebRTC drops from WFM adherence calculations, since shift swap windows often trigger these SIP timeouts and skew performance metrics.
- Shift swap configurations
- WFM schedule adherence
- Agent self-service availability