Bulk PATCH /api/v2/users hitting 429s despite exponential backoff logic

We’re running a nightly sync to update user skills and wrap-up codes via the Python SDK. The script iterates through a list of 2,000 users and sends PATCH requests to /api/v2/users/{id}. I’ve implemented a standard exponential backoff with jitter, but the script still chokes hard after about 50 successful updates. It throws a 429 Too Many Requests error, and the subsequent retries fail immediately because the Retry-After header isn’t being respected by the SDK’s default retry mechanism.

Here’s the core loop:

for user in users:
 try:
 client.users_api.update_user(user_id=user.id, body=user_data)
 except platform_api_client.rest.ApiException as e:
 if e.status == 429:
 wait_time = min(2 ** attempt + random.uniform(0, 1), 60)
 time.sleep(wait_time)
 attempt += 1
 continue

The issue is that once the 429 hits, the next request also returns 429 instantly, regardless of the sleep. It feels like the rate limit window is per-IP or per-tenant rather than per-request. I’ve checked the Retry-After value in the response headers, and it’s usually 5-10 seconds, but my sleep is set to double that. Is there a specific header I’m missing, or does the Genesys Cloud API require a different approach for bulk operations? The admin UI shows the updates pending, but the API is blocking the flow. I need to process this batch without manual intervention.

The SDK’s default backoff usually handles transient spikes, but 429s on bulk user updates are often tied to specific rate limit buckets, not just general throughput. You’re probably hitting the per-resource limit for /users, which is stricter than the global limit.

Try switching to the bulk endpoint instead of iterating. It’s much more efficient and respects the batch limits properly.

from purecloudplatformclientv2 import PlatformApiClient, UsersApi, PatchUsersRequest

api_instance = UsersApi(api_client)
patch_request = PatchUsersRequest(
 items=[
 {"id": "user-id-1", "skills": [...]},
 {"id": "user-id-2", "skills": [...]}
 ]
)

try:
 api_instance.patch_users(body=patch_request)
except ApiException as e:
 print(f"Status: {e.status}, Reason: {e.reason}")

This sends up to 1,000 users in one call. It reduces the HTTP overhead significantly. Make sure your token has user:write scope.