Agent Scripting API 429s during JMeter load test - Is there a hidden burst limit?

HTTP/1.1 429 Too Many Requests
Retry-After: 1
Content-Type: application/json
{
 "message": "Rate limit exceeded for resource: /api/v2/scripts",
 "status": 429
}

We are hitting a wall with the Agent Scripting API (/api/v2/scripts) while running a JMeter script to simulate high-concurrency script updates. The goal is to validate how the platform handles simultaneous script version pushes from multiple agents during a peak shift. We are targeting a throughput of 50 requests per second from a single load generator instance located in the Asia/Singapore region.

The script is straightforward: it fetches the current script version, updates a minor text field, and posts it back. Under low load (5 RPS), everything works fine. Once we ramp up to 20 RPS, we start seeing intermittent 429 errors. At 50 RPS, the error rate jumps to nearly 60%. The Retry-After header is consistently set to 1 second, which seems aggressive for a platform that claims to handle enterprise-scale concurrency.

We have checked the standard documentation for Genesys Cloud API rate limits, but the specific limits for the Scripting API are not clearly defined in the public rate limit tables. The general limit of 100 requests per minute per user seems too low for a load test, but we are using a service account with elevated permissions. We are not using OAuth token rotation in this test, so the rate limit is tied to the single access token.

Is there a specific burst limit for the /api/v2/scripts endpoint that is lower than the general API limit? We are wondering if we need to implement a more sophisticated backoff strategy in our JMeter script or if we are hitting a hard capacity ceiling for script operations. We have tried staggering the requests with a constant timer, but the 429s still appear. Any insights into the backend throttling behavior for scripting resources would be appreciated. We are currently using the latest Genesys Cloud SDK for Java in our test harness.

The main issue here is likely a misunderstanding of the intended API usage pattern within the performance monitoring scope. Agent Scripting endpoints are designed for administrative configuration, not high-concurrency runtime updates from agents. The 429 errors indicate that the platform’s rate-limiting logic is correctly protecting the configuration store from excessive write operations, which is standard behavior for enterprise stability.

Do not treat configuration APIs as transactional endpoints for real-time agent interactions.

Instead of simulating script pushes during peak shifts, consider evaluating the impact on Agent Performance metrics and Queue Activity views. If the goal is to test system resilience under load, focus on conversation detail views and routing efficiency rather than configuration changes. The documentation suggests that script updates should be batched or scheduled during off-peak hours to avoid impacting dashboard latency. Reviewing the Performance views for any anomalies during these tests might reveal if the configuration locks are affecting agent availability reports.

I’d suggest checking out at the Retry-After header in the 429 response. While the API protects the config store, your JMeter script should implement exponential backoff based on that value. Hardcoding a fixed delay ignores the server’s specific throttling state, which often leads to persistent failures during load tests.