Data Action Timeout and 502 Errors During High-Volume OAuth Token Refresh

Could someone explain why our Genesys Cloud integrations are experiencing intermittent 502 Bad Gateway errors specifically during peak transaction hours in the US West region? We are an AppFoundry partner deploying a Premium App that relies heavily on the POST /api/v2/oauth/token endpoint for multi-org authentication. The issue seems to correlate with our token refresh logic when scaling across multiple tenant organizations simultaneously.

The application utilizes the standard OAuth 2.0 client credentials flow. Under normal load, the latency is acceptable, averaging around 200ms. However, during our morning spike (PST), we observe a significant degradation in response times, eventually leading to timeouts at the Architect Data Action level. The underlying API calls return 502 errors rather than the expected 429 rate limit responses, which suggests the issue might be deeper than standard throttling.

Here is the error payload captured from our logging service:

{
 "status": 502,
 "code": "bad_gateway",
 "message": "The server received an invalid response from an upstream server.",
 "details": "Request failed to process within the allocated timeout window for OAuth token generation."
}

We have verified that our API keys and client secrets are valid and not expired. The problem appears to be transient and resolves itself after a few minutes of retrying with exponential backoff. Given our specialization in platform API integrations, we are concerned about the stability of the upstream services during these high-concurrency windows. Is there a known limitation on the throughput for token generation requests from AppFoundry applications, or should we be implementing a specific caching strategy to mitigate these upstream failures? Any insights into the backend infrastructure handling these requests would be greatly appreciated.

Have you tried adding explicit retry logic with exponential backoff for the token refresh? The 502s often stem from the auth service being overwhelmed during spikes. Adjust the JMeter HTTP Request Defaults to handle transient failures gracefully.

{
 "retry_count": 3,
 "backoff_ms": 1000
}