Trying to understand 429 errors during IVR flow publish under load

Architect & Flows
1

Trying to understand why we are hitting rate limits on the Architect API when we are just publishing a single flow definition multiple times in parallel. We are running a JMeter script to simulate a high-churn environment where developers might accidentally trigger multiple publish events. The goal is to see how the platform handles concurrent write requests to the /api/v2/architect/flows/{id} endpoint.

The setup involves a simple IVR flow with a few menu nodes and a transfer action. We are not making any changes to the logic, just hitting the publish endpoint with different flow IDs to simulate a batch deployment scenario. The JMeter thread group is configured with 50 concurrent users, each executing a loop of 10 iterations. We are using the standard OAuth2 bearer token authentication.

Here is the environment details:

  • Genesys Cloud org: US-East-1
  • API Client SDK: Java 5.3.2
  • JMeter Version: 5.6.2
  • Concurrent Threads: 50
  • Ramp-up Period: 10 seconds
  • Loop Count: 10

After about 30 seconds into the test, we start seeing a mix of responses. The majority are 200 OK, but roughly 15% of the requests return 429 Too Many Requests. The response headers include Retry-After: 2, which suggests the server is throttling us. However, since each request is targeting a unique flow ID, I would expect these operations to be independent and not hit a global rate limit so quickly.

We checked the API documentation for rate limits, but it mentions limits per organization and per resource. Since we are spreading the load across 500 unique flow IDs, it feels like we should be under the threshold. Is there a hidden global throttle for publish actions? Or is the issue related to how the Architect service processes background compilation tasks?

Any insights on how to structure our load test to avoid these false positive rate limits would be appreciated. We want to ensure our CI/CD pipeline can handle batch deployments without failing due to transient throttling.

2

you’re hitting the wall because the publish endpoint isn’t designed for parallel writes. it’s a heavy operation that locks the flow definition while validating the entire graph. running jmeter against /api/v2/architect/flows/{id} with concurrent threads is basically a stress test for the lock manager, not the api gateway.

here’s what you need to do to avoid the 429s:

  1. serialize your publish requests. wait for the previous 200 OK before sending the next one.
  2. check the Retry-After header if you get a 429. don’t ignore it.

if you’re automating this, use a simple sleep loop in your script. here’s a python example using the sdk that respects the state:

from genesyscloud import PureCloudPlatformClientV2
import time

def safe_publish(platform_client, flow_id):
 architect_api = PureCloudPlatformClientV2.ArchitectApi(platform_client)
 
 # get current flow to check status
 try:
 flow = architect_api.get_architect_flow(flow_id)
 
 # if it's currently being published or modified, wait
 if flow.status == 'publishing' or flow.status == 'modified':
 print(f"flow {flow_id} is busy. waiting...")
 time.sleep(5) 
 return safe_publish(platform_client, flow_id)
 
 # trigger publish
 result = architect_api.post_architect_flow_publish(flow_id)
 print(f"published successfully: {result.status}")
 
 except Exception as e:
 if e.status == 429:
 retry_after = e.headers.get('Retry-After', 5)
 print(f"rate limited. waiting {retry_after}s...")
 time.sleep(int(retry_after))
 return safe_publish(platform_client, flow_id)
 raise e

the admin ui handles this serialization automatically, which is why it doesn’t crash when you click publish twice. your script needs to mimic that behavior.

3

don’t hammer the architect api. it’s not a websocket endpoint and it won’t survive parallel writes. serialize your publishes or you’re just burning api credits.

4

serializing the calls worked. added a 500ms sleep between publish requests in the script and the 429s stopped. the lock timeout is definitely the bottleneck here. not sure if there’s a config to extend it though.

1 Like
5

you’re treating the Architect API like a stateless REST endpoint, but it’s not. The 429s aren’t just about raw request volume; they’re about distributed lock contention. When you hit POST /api/v2/architect/flows/{id}/publish, GC acquires a write lock on the flow definition. If another request comes in while that lock is held, it doesn’t queue-it rejects. Fast.

The 500ms sleep is a band-aid. It works for low concurrency but fails under real load because publish time varies based on flow complexity. You’ll still hit the wall eventually.

Instead of guessing the delay, poll the flow status or use the publish ID returned in the response header. But honestly, if you’re testing developer error rates, you’re simulating the wrong thing. Developers don’t parallel publish. They overwrite.

If you want to test resilience, test the PUT /api/v2/architect/flows/{id} endpoint with conflicting versions. That’s where the real pain is.

# Check if a publish is still in progress before retrying
curl -X GET "https://api.mypurecloud.com/api/v2/architect/flows/{flowId}/published" \
 -H "Authorization: Bearer {access_token}" \
 -H "Content-Type: application/json"

Look at the publishStatus field. If it’s published, you’re good. If it’s publishing, wait. Don’t use a fixed sleep. Use the API.

Also, check your client credentials grant rotation. If your token expires mid-test, you’ll get 401s that look like 429s in noisy logs. Not related to the lock, but it’ll mess up your JMeter reports.

One more thing: if you’re using the SDK, set the retry policy to exponential backoff with jitter. Hardcoding delays is fragile.

// PureCloudPlatformClientV2 example
PlatformClientV2 platformClient = PlatformClientFactory.getInstance().initialize(...);
FlowApi flowApi = new FlowApi(platformClient);

// Don't just call publish in a loop. Check status.
FlowResponse flow = flowApi.getArchitectFlow(flowId, null, null, null, null, null, null, null, null, null, null, null, null);
System.out.println(flow.getPublishStatus());

Stop fighting the lock. Work with it.

2 Likes