Architect Bot API 429 Rate Limit During JMeter Spike Test

My current config is completely failing…

I am running load tests against a Genesys Cloud Architect flow that uses the “Send to Bot” action. The environment is Genesys Cloud v2.16.0. When I simulate a sudden spike of 500 concurrent users using JMeter 5.4.1, the API gateway returns 429 Too Many Requests before the rate limit counters reset.

The JMeter thread group is configured with a ramp-up period of 10 seconds. The goal is to test the bot’s capacity handling under high concurrency. However, the responses fail immediately after the initial burst. The browser console and JMeter response data show the following error:

“Error 429: Rate limit exceeded. Please wait 15 seconds before retrying. Retry-After: 15”

I have checked the API rate limit headers, specifically the Retry-After field, but the issue persists even when I add a Constant Throughput Timer in JMeter to limit requests per second. The bot logic itself is simple, just echoing back the user input. I suspect the issue is related to how Genesys Cloud handles WebSocket connections during high load.

Is there a specific configuration in Architect to handle rate limiting for bot actions? Or should I adjust the JMeter settings to mimic realistic user behavior more closely? I want to ensure the bot can handle peak call volumes without dropping connections. Any insights on best practices for load testing Architect flows with bots would be appreciated. I am new to this and trying to understand the limits of the platform.

It depends, but generally… The 429 error during a 10-second ramp-up for 500 users is expected behavior for the Architect Bot API. The platform enforces strict per-tenant rate limits to prevent cascade failures. Check the official limits here: support.genesys.cloud/articles/api-rate-limits-bot-actions.

In JMeter, you need to implement the Retry-After header logic. Add an HTTP Header Manager to capture the delay value and use a BeanShell PreProcessor to pause the thread accordingly. Do not just retry immediately. Also, consider increasing the ramp-up time to 60 seconds to simulate a more realistic traffic curve. A sudden spike of 500 concurrent bot interactions overwhelms the initial token bucket. Adjusting the concurrency settings in your Thread Group to match the documented API throughput will help identify the true capacity bottleneck instead of hitting the gateway limit first.

API gateway returns 429 Too Many Requests before the rate limit counters reset.

The suggestion to adjust the ramp-up period aligns with the Performance Dashboard’s view of queue activity. Reducing the initial burst prevents immediate edge connection saturation. Monitor the “Handled In” metric to verify the flow execution capacity absorbs the load without triggering the 429 limit.