Hey everyone,
I’ve hit a weird snag while trying to build a real-time dashboard for our WFM adherence tracking. We’re monitoring service levels across multiple queues in the US/Central timezone, and I need live data on waiting counts and available agents. I figured the Statistics API would be the way to go, specifically the /api/v2/analytics/queues/realtime/intervals endpoint.
I wrote a quick Python script using the Genesys Cloud SDK to fetch this data every 30 seconds. Here’s the relevant snippet:
from gen_cloud_py import PlatformClientV2
api_instance = PlatformClientV2.AnalyticsApi()
queue_id = "my-queue-id-123"
interval = "PT1M"
try:
result = api_instance.get_queue_realtime_intervals(
queue_id=queue_id,
interval=interval,
group_by="queue"
)
print(result.entities[0].metrics)
except Exception as e:
print(f"Error: {e}")
The issue is that the agents.available metric seems to lag by about 5-10 minutes compared to what I see in the Genesys Cloud admin console. I checked the interval parameter and tried switching to PT1S for second-by-second granularity, but the numbers still don’t match the live view. The API call itself succeeds with a 200 OK status, and the JSON payload looks well-formed. For example, one response showed:
{
"agents": {
"available": 2,
"busy": 15
},
"calls": {
"waiting": 3
}
}
But in the UI, I clearly saw 5 agents available. I’ve verified the OAuth token has the analytics:read scope. Is there a known delay with the Statistics API for real-time metrics? Or am I missing a parameter to force a fresh query? I’ve been staring at the docs for hours and can’t find anything about caching behavior for this endpoint. Any help would be appreciated.