Just noticed that the real-time queue occupancy metrics in the Performance dashboard are failing to update during specific SIP trunk registration cycles. The environment is configured with Genesys Cloud Edge (BYOC) nodes deployed in the EU-West region to ensure data residency compliance. While the historical data exports via the Data API remain accurate, the live performance views display significant delays or complete stagnation when traffic is routed through these specific edge nodes.
The issue appears isolated to the Performance dashboard’s real-time views, particularly the Queue Activity and Agent Performance tabs. When agents are assigned to skills that route exclusively through the BYOC infrastructure, the ‘Occupancy’ metric often freezes or reports values that do not align with the actual call volume observed in the Conversation Detail views. This discrepancy is critical for our workforce management team, who rely on these live metrics for intraday staffing adjustments during peak business hours in the Paris timezone.
We have verified that the edge nodes are healthy and that the SIP trunks are registered correctly with no packet loss indicated in the network diagnostics. The problem persists across different browser instances and user roles, suggesting the root cause lies within the data synchronization mechanism between the edge nodes and the central Genesys Cloud performance reporting engine. The error is not accompanied by any visible system alerts in the Admin portal, making it difficult to pinpoint whether this is a configuration oversight or a known limitation of the current edge deployment architecture.
Can anyone clarify if there are specific latency thresholds or configuration parameters that affect the propagation of real-time metrics from BYOC nodes to the central dashboard? We are seeking a workaround to ensure our performance reporting remains reliable without having to route all traffic through the public cloud, which would violate our data sovereignty requirements. Any insights into the data flow architecture or potential configuration fixes would be greatly appreciated.
TL;DR: Edge node telemetry often lags.
Have you tried forcing a genesyscloud_edge_node refresh via CLI? The HCL state might be stale.
resource "genesyscloud_edge_node" "eu_west" {
name = "eu-west-node"
}
Run terraform refresh then push.
The documentation actually says…
Hey there. Looking at the BYOC latency issue, the dashboard stall might not be a network problem but a client-side polling bottleneck. When pushing high concurrency through JMeter, the WebSocket connections for real-time stats often hit the per-tenant rate limit on the metrics endpoint. The platform batches these updates, so if the ingest rate exceeds the publish rate, the UI freezes.
Try adjusting your load test to reduce the frequency of metric polling requests. In JMeter, add a Constant Throughput Timer set to 60 req/min for the /api/v2/analytics/queue/realtime calls. This mimics standard agent behavior and prevents the telemetry pipeline from backlogging.
Also, check the X-Request-Id headers in the response. If you see 429s, the edge node is throttling the reporting traffic, not the media. Switching to a lower polling interval in the dashboard config or using the Data API for aggregated snapshots instead of real-time streams usually resolves the stagnation. Keep the media path separate from the stats path in your test design.
To fix this easily, this is to decouple the real-time metric ingestion from the edge node registration heartbeat by implementing a custom Data Action that buffers occupancy events before pushing them to the ServiceNow instance or local analytics store. Directly relying on the native WebSocket stream for BYOC nodes often triggers the same tenant-level throttle limits mentioned in previous threads, especially when combined with high-concurrency SIP trunk cycles. The Genesys Cloud platform batches these updates to prevent database contention, but this creates a false positive of “stagnation” in the UI if the ingest rate exceeds the publish rate. Instead of forcing a Terraform refresh, which only updates the HCL state and not the actual telemetry pipeline, you should configure a Data Action with an increased timeout to handle the latency between the edge node and the core platform. This approach aligns with the documentation regarding webhook payload handling and prevents the truncation of critical metadata. By routing the occupancy metrics through a dedicated API endpoint in ServiceNow, you can bypass the UI polling bottleneck entirely. This ensures that historical data remains accurate while providing a more reliable real-time view through the custom integration. It is also worth noting that the EU-West region may have specific data residency rules that add slight latency to the telemetry pipeline, so adjusting the retry logic in the Data Action is crucial. This method has been tested in similar BYOC environments and significantly reduces the perceived lag in performance dashboards.