No idea why this is happening, the Predictive Routing API returns 429 errors when simulating 200 concurrent calls in Singapore. Using JMeter 5.6 to trigger a simple SQL query via the platform API. The docs mention rate limits but do not specify exact thresholds for campaign updates during load tests.
Environment:
- Genesys Cloud API v2
- Asia/Singapore region
- 100 concurrent threads ramping to 200
- JMeter 5.6 with custom WebSocket sampler
The error starts appearing after 30 seconds of steady load. Response headers show Retry-After: 60 but the actual blockage lasts longer. Tried adding exponential backoff in JMeter but it breaks the concurrent call simulation logic.
What is the correct way to handle rate limits on /api/v2/predictiverouting/campaigns when ramping up volume? Is there a specific header or configuration in the Singapore region that affects WebSocket connection limits for predictive routing campaigns?
Any insights would be appreciated.
Have you tried adjusting the pacing controller in JMeter to respect the specific rate limits for the Asia region? The documentation often overlooks that Singapore has slightly lower throughput caps compared to US East, especially for Predictive Routing campaign updates. Instead of ramping 200 threads immediately, use a Constant Throughput Timer to cap requests at 60 per minute per tenant ID. This usually prevents the 429 errors without needing to reduce concurrency significantly. Also, check if your custom WebSocket sampler is holding connections open longer than necessary, which can exhaust the pool faster. I faced similar issues when testing with 150 concurrent users and found that adding a 2-second delay between API calls for campaign status checks stabilized the load. The key is to simulate realistic agent interaction patterns rather than pure machine speed. Try reducing the ramp-up time to 10 seconds and see if the error rate drops.
TL;DR: Rate limit headers are explicit.
The documentation actually says X-RateLimit-Remaining and X-RateLimit-Reset dictate the ceiling. JMeter ignores these by default. Add an HTTP Header Manager to capture them, then use a BeanShell PreProcessor to calculate the sleep duration.
long reset = Long.parseLong(prev.getHeaderValue("X-RateLimit-Reset"));
long now = System.currentTimeMillis();
if (now < reset) {
ctx.getCurrentThread().interrupt();
Thread.sleep(reset - now);
}
The problem here is the origin distribution for your JMeter load. A single IP cluster triggers aggressive throttling on the edge. Switch to a distributed origin strategy to bypass this. See the internal note on handling WebSocket handshake limits at scale: support.genesys.cloud/articles/pr-429-singapore.