Stuck on rate limiting while testing interaction creation throughput. Running JMeter with 100 threads hitting /api/v2/interaction. Getting 429 errors after just 20 requests. The x-rate-limit-remaining header drops to zero instantly. Docs mention burst limits, but I can’t find the exact cap for this endpoint. Here is the payload:
{
"to": {"phoneNumber": "+1234567890"},
"from": {"phoneNumber": "+0987654321"},
"type": "voice"
}
Is there a way to increase the burst limit for load testing?
The root of the issue is that Genesys Cloud enforces strict rate limits on interaction creation endpoints to protect system stability, which differs significantly from how Zendesk handled bulk ticket creation. In Zendesk, we often relied on simple API key authentication with higher tolerance for burst traffic. However, Genesys Cloud uses a sliding window mechanism for these limits. The /api/v2/interaction endpoint typically allows a burst of 10-20 requests per second, depending on your organization’s tier and specific configuration.
To mitigate this in JMeter, you need to implement exponential backoff logic rather than just flooding the endpoint. Here is a simple JSR223 PostProcessor snippet to handle the 429 response gracefully:
import org.apache.http.HttpStatus
int statusCode = prev.getResponseCode()
if (statusCode == HttpStatus.SC_TOO_MANY_REQUESTS) {
// Extract retry-after header if present, otherwise default to 1s
String retryAfter = prev.getResponseHeader("Retry-After")
int delay = retryAfter != null ? Integer.parseInt(retryAfter) * 1000 : 1000
SampleResult.setSuccessful(false)
// Force JMeter to wait before next request
Thread.sleep(delay)
}
Additionally, ensure you are reusing the same OAuth token across threads instead of generating new tokens for each request, as token generation also consumes rate limit quota. In our migration from Zendesk, we found that batching interactions where possible or using the Async API for bulk operations reduced load significantly. Check your integration settings to see if there are any custom rate limit overrides applied.
The best way to fix this is to implement exponential backoff logic within the JMeter test plan to respect the rate limiting headers returned by the platform. While the initial burst capacity for the interaction endpoint is relatively low, the system is designed to handle sustained traffic if requests are spaced correctly rather than hammered in a single second. This approach aligns with standard enterprise integration patterns where stability is prioritized over raw throughput during initial load testing phases.
<!-- Add this to your JMeter Thread Group or as a Post-Processor -->
<elementProp name="Header Manager" elementType="HeaderManager">
<collectionProp name="HeaderManager.headers">
<elementProp name="x-rate-limit-remaining" elementType="Header">
<stringProp name="Header.name">x-rate-limit-remaining</stringProp>
</elementProp>
</collectionProp>
</elementProp>
<!-- Logic: Check header value; if 0, introduce a delay of 1000ms * 2^retry_count -->
Monitoring the queue activity dashboard during these tests will provide clearer visibility into how the platform processes these throttled requests compared to raw API metrics.