Could someone explain the significant latency and data mismatch we are seeing between the real-time telephony metrics API and the historical analytics reports for our BYOC trunks. We are managing fifteen trunks across APAC regions, specifically focusing on Singapore and Sydney endpoints. When querying the GET /api/v2/analytics/real-time/telephony endpoint, the concurrent call counts align perfectly with our SBC logs. However, the same metrics exported via the historical analytics API for the previous hour show a 15-20% deviation in utilization rates. This discrepancy makes it difficult to validate carrier failover logic effectiveness during peak load testing scenarios.
The environment involves Genesys Cloud version 2023-09 with custom outbound routing rules tied to specific carrier pools. We have configured strict SIP registration monitoring and failover thresholds that trigger based on real-time jitter and packet loss metrics. The issue appears isolated to the aggregation layer of the analytics engine. The real-time API returns granular JSON objects per trunk, but the historical report aggregates these into broader time buckets. We suspect the bucketing algorithm might be dropping calls that terminate within the same second, leading to the undercounting observed in the final CSV exports.
We have verified that the service account used for the API calls has full analytics permissions and that the timezone settings are consistently set to Asia/Singapore across all configurations. The API responses return HTTP 200 OK, but the payload structure differs slightly in how idle calls are counted. The real-time API excludes calls in the ‘queued’ state from the active count, whereas the historical report seems to include them until the call is explicitly dropped or answered. This inconsistency creates a false positive in our carrier performance dashboards.
Has anyone encountered similar aggregation issues with BYOC trunk analytics? We are considering implementing a custom middleware to reconcile these datasets before feeding them into our SIEM for compliance reporting. Any insights into the specific logic Genesys uses for historical bucketing versus real-time snapshots would be appreciated. We need to ensure our failover triggers are based on accurate historical baselines to prevent unnecessary trunk switching during minor network fluctuations.