Looking for advice on optimizing the latency between our BYOC Edge deployment and the Genesys Cloud WFM schedule API. We have implemented a custom Edge Worker to dynamically route calls based on agent availability and specific skill proficiency overrides. The goal is to bypass the standard predictive routing weights for a specific VIP queue and ensure immediate connection to the most qualified agent who is currently scheduled as ‘Available’ in WFM.
The current setup uses a Python 3.9 runtime for the Edge Worker. The worker makes an authenticated request to GET /api/v2/wfm/schedules/{scheduleId}/agents/{agentId}/status to verify real-time status before routing. However, we are experiencing intermittent 504 Gateway Timeout errors when the worker attempts to fetch this data during peak load (approx. 150 concurrent requests). The timeout occurs consistently after 30 seconds, which is the default limit for our Edge execution environment.
Here is the relevant configuration snippet from our edge-config.yaml:
edge_worker:
runtime: python3.9
timeout_seconds: 30
retry_policy:
max_retries: 3
backoff: exponential
api_endpoints:
- path: /api/v2/wfm/schedules/{scheduleId}/agents/{agentId}/status
method: GET
cache_ttl: 0 # No caching for real-time accuracy
The issue seems to stem from the lack of caching (cache_ttl: 0) combined with the high latency of the WFM API response during peak hours. We have verified that the API tokens are valid and the Edge Worker has the correct wfm:schedule:view permissions. Reducing the timeout is not an option as it causes immediate failures. Increasing it further risks hitting the platform’s hard limits.
Is there a recommended pattern for caching WFM schedule status data on the Edge side without compromising real-time accuracy? Or should we be leveraging a different API endpoint that is optimized for low-latency status checks? We are currently based in America/Chicago, so network latency to US-East endpoints should be minimal, but the API response time itself appears to be the bottleneck. Any insights on best practices for this integration would be greatly appreciated.