PUT /api/v2/users/{id} returning 429 despite exponential backoff implementation

Docs state: “Rate limits are applied per endpoint and may vary based on your account tier. Clients should handle 429 responses by waiting for the duration specified in the Retry-After header.”

I’ve built a bulk user sync service that updates SCIM profiles via the Genesys Cloud REST API. It’s a simple loop processing a queue of user objects. The logic seems sound, but I’m hitting a wall with 429 Too Many Requests errors that don’t clear even after waiting the specified time.

Here’s the core update function in Python using requests:

import requests
import time

def update_user(client_id, user_id, payload):
 url = f"https://api.mypurecloud.com/api/v2/users/{user_id}"
 headers = {
 "Authorization": f"Bearer {get_token()}",
 "Content-Type": "application/json"
 }
 
 response = requests.put(url, headers=headers, json=payload)
 
 if response.status_code == 429:
 retry_after = int(response.headers.get('Retry-After', 5))
 print(f"Hit rate limit. Waiting {retry_after}s...")
 time.sleep(retry_after)
 # Recursive call to retry once
 return update_user(client_id, user_id, payload)
 
 return response

The weird part is the Retry-After header. Sometimes it says 0. Sometimes it says 30. When it says 0, I wait 1 second just to be safe, then retry, and I get another 429 with Retry-After: 0. This creates an infinite loop of instant 429s.

I’m running this from Amsterdam (eu-02). The concurrency is low, maybe 5 requests per second. The docs mention a limit of 100 requests per second for most endpoints, so I shouldn’t be hitting the ceiling. Is there a secondary bucket for PUT requests specifically? Or is the Retry-After: 0 a bug in the gateway?

I tried adding a random jitter (0.5 to 2 seconds) when Retry-After is 0. It helps a bit, but the success rate drops to 40%. The logs show no pattern. One user updates fine, the next three fail instantly. No 5xx errors. Just 429.

Any ideas on what else triggers this? I’ve checked the request body size, it’s tiny. Just email and department updates. Nothing heavy.

// Don’t just parse the header. Check the body too.
if (response.status === 429) {
const retryAfter = response.headers.get(‘Retry-After’);
const body = await response.json();
const waitSeconds = retryAfter ? parseInt(retryAfter) : (body.retry_after || 5);

// Add jitter to avoid thundering herd if multiple threads hit this
const jitter = Math.random() * 1000;
console.log(Rate limited. Waiting ${waitSeconds}s + jitter...);

await new mise(r => setTimeout(r, (waitSeconds * 1000) + jitter));
}

The issue usually isn't your backoff logic itself. It's that you're hitting the endpoint in a tight loop from a single IP or using a single OAuth token for everything. Genesys Cloud rate limits are often scoped to the client ID or the specific user context, not just the raw endpoint.

If you're doing a bulk sync, you need to stagger the requests. A simple `sleep` isn't enough if you have multiple worker threads all waking up at the same time. Add some random jitter to your wait time. Also, check if you're hitting the global API limit or a specific user limit. Sometimes splitting the load across multiple client credentials helps, but that's messy. For now, add the jitter. It stops the synchronized retry storm.

The jitter helps, but the real issue is usually shared rate limit buckets. Updating users often shares the quota with other identity operations. If you’re hitting 429s despite backoff, check if other services are also calling identity endpoints. The limit isn’t just per endpoint, it’s often per account tier for the whole resource group.