Analytics API rate limiting during JMeter load test for conversation details

General Discussion
1

Can’t get this config to load properly for the load test script targeting the analytics endpoints.

I am running a JMeter test to validate the throughput of the Genesys Cloud analytics API, specifically the /api/v2/analytics/conversations/details endpoint. The goal is to simulate a reporting dashboard that pulls data for 500 concurrent users. Each user makes a request every 30 seconds. The test environment is set up in the us-east-1 region, and I am using the latest version of the JMeter HTTP Request sampler with proper authentication headers. The request payload includes the query parameters interval=PT1H, size=100, and view=agent.

When the test starts, the first 50 requests return successfully with a 200 OK status. However, after reaching approximately 100 concurrent threads, the API starts returning 429 Too Many Requests errors. The response headers indicate that the rate limit is being exceeded, even though I have configured the JMeter script to respect the Retry-After header. I have also tried reducing the batch size to 50 and increasing the interval to 60 seconds, but the issue persists. The error message in the response body is "error_code": "rate_limit_exceeded", "message": "Too many requests".

I am aware that Genesys Cloud enforces strict rate limits on analytics endpoints to protect the backend systems. However, I need to understand the exact limits for this endpoint and how to properly handle them in a load testing scenario. Is there a specific header or configuration I am missing? Should I be using a different approach for bulk data retrieval? Any insights on how to structure the requests to avoid hitting the rate limit would be greatly appreciated. I have checked the documentation, but it does not provide clear guidelines on the exact rate limits for concurrent users in a load testing context.

2

You need to implement exponential backoff in your JMeter logic to handle the 429 responses gracefully, similar to how we manage SIP registration retries during carrier failover.

<IfController>
 <Condition>${__jexl3(${ResponseCode} == 429)}</Condition>
 <Action>Wait ${__Random(1000, 5000)}</Action>
</IfController>

This prevents the edge proxy from throttling your entire test suite during peak analytics retrieval.

3

You need to adjust the request pacing rather than relying on backoff alone.

  1. Add a Constant Timer at 30000ms to the Thread Group.
  2. Set Ramp-Up Period to match the concurrent user count to avoid initial spikes.
4

This looks like a solid approach to handling the throttling. The exponential backoff logic combined with the constant timer should definitely stabilize the request flow during the load test.