- Environment: Genesys Cloud Production (EU-West-1)
- Tool: Genesys Cloud CLI v3.2.1
- Language: Python 3.9 wrapper for bulk data extraction
- Endpoint:
GET /api/v2/analytics/users/summary - Frequency: Every 5 minutes via cron job
- Error: HTTP 429 Too Many Requests
Does anyone know the exact sliding window logic for the Analytics API rate limits? The documentation states a limit of 60 requests per minute, but my automated script hits a 429 after roughly 45 calls.
The setup uses a simple loop to iterate through user IDs and fetch summary metrics. The headers return X-RateLimit-Remaining: 0 and Retry-After: 15. This happens consistently during the Sydney morning peak (09:00 AEST).
Snippet of the request logic:
for user_id in user_list:
response = client.get(f"/api/v2/analytics/users/summary/{user_id}")
if response.status_code == 429:
time.sleep(int(response.headers.get('Retry-After', 10)))
continue
save_to_s3(response.json())
The Retry-After value fluctuates between 10-20 seconds. I have tried adding a static 2-second delay between requests, which reduces the error frequency but does not eliminate it. The total dataset is approximately 200 users.
Is there a specific header or parameter to optimize batch retrieval? Or is the limit strictly per IP address rather than per API key? The CLI uses a service account with full admin permissions.
Previous attempts to use the GET /api/v2/analytics/details/query endpoint resulted in similar throttling behavior when paginating through large result sets. The system logs show no 5xx errors, only 429s. This breaks the nightly data pipeline for the reporting dashboard.
Looking for a workaround or confirmation of the actual limit threshold. The current implementation assumes a linear 1 request per second pace, which should be well within the documented limits. Any insights on how Genesys calculates the quota for this specific endpoint would be appreciated.
The issue persists even when using the X-Genesys-Request-Id header for tracing. Support tickets have been unhelpful, suggesting standard retry logic which is already in place. Need a more robust solution for high-frequency analytics queries.