Is it possible to configure the predictive routing engine to handle sudden bursts of 200 concurrent inbound calls without hitting 429 Too Many Requests on the /api/v2/routing/queues endpoint?
We are running a load test from our Singapore office (Asia/Singapore edge) using JMeter 5.6.2. The goal is to simulate a high-volume support scenario where call volume spikes rapidly. The test script initiates SIP INVITEs at a rate of 100 per second, which should theoretically fit within the documented capacity, but the Genesys Cloud platform starts rejecting requests almost immediately after the concurrent call rate hits 80.
We have verified that the integration user has the routing:queue:read and routing:conversation:create permissions. The test environment is a standard production-like sandbox. We are not using any custom plugins or advanced routing strategies, just basic longest idle agent assignment.
The issue seems to be tied to the frequency of the queue status checks. The JMeter script polls the queue metrics every 500ms to log wait times, which might be contributing to the rate limit hits. However, even when we reduce the polling frequency to 5 seconds, the SIP INVITEs themselves start failing with 429s.
Is there a way to increase the throughput limit for routing APIs during load testing? Or is there a specific header or parameter we can send to indicate this is a test environment? We need to validate the system’s capacity before going live with a new campaign.
Any insights on how to structure the load test to avoid hitting these limits would be appreciated. We are currently blocked on our performance validation phase.
This is typically caused by the predictive routing engine hitting its internal rate limits when the SIP INVITE rate exceeds the platform’s capacity to process queue assignments. The 429 errors are a protective measure, not a bug in your JMeter script alone.
To resolve this, you need to throttle the test to match realistic WFM capacity.
Adjust the JMeter throughput controller to cap at 50 calls per second.
Implement exponential backoff on the /api/v2/routing/queues endpoint calls.
Verify that your WFM schedule has enough available agents to handle the predicted volume.
If you push 100 calls per second, the system cannot assign them fast enough. The API rejects the excess. Align your load test with your actual published schedule capacity. This prevents false positives in your testing.
If you check the docs, they mention that bypassing rate limits is not a supported configuration path. the 429 errors are intentional safeguards to protect the queue state consistency. instead of trying to force the routing engine to accept more invocations, consider adjusting the test strategy to mimic realistic agent availability.
when running high-volume load tests, the system expects a corresponding number of active agents to accept interactions. if the queues fill up faster than agents can accept calls, the platform throttles the ingress to prevent memory leaks and state corruption.
try modifying your jmeter script to include a “think time” or a delay between sip invites. also, ensure your test environment has enough virtual agents configured to accept the load. you can script the agent login and availability changes via the api to match the call volume.
here is a quick python snippet to adjust agent status in sync with your load test:
import requests
def set_agent_available(agent_id, token):
url = f"https://api.mypurecloud.com/api/v2/users/{agent_id}/presence"
headers = {
"authorization": f"bearer {token}",
"content-type": "application/json"
}
payload = {
"type": "available",
"reason": "test_load"
}
response = requests.put(url, headers=headers, json=payload)
return response.status_code
# call this function before each batch of 50 calls
focus on the metadata and audit trails of the interactions rather than just the raw volume. legal hold tags and export jobs need accurate session data. if the routing engine drops calls due to throttling, the recording export will be incomplete. this affects chain of custody for any compliance reviews. stick to the documented throughput limits. the system is designed for stability, not infinite spikes. check the wfm capacity planning docs for the exact numbers for your region.