- Genesys Cloud v2024.1
- JMeter 5.6
- 50 concurrent threads
Why does this setting trigger a 403 Forbidden when exporting user permissions via the Admin API? The endpoint works fine with single requests. Under load, the response body shows “Rate limit exceeded for security operations”. I checked the documentation but found no specific throttle for bulk permission reads. Is there a hidden limit for this category?
check your rate limit headers in the response, specifically the x-rate-limit-remaining field. this 403 is not a hidden limit for bulk permission reads, it is the standard api gateway throttling kicking in because the admin api has stricter security controls than the recording export endpoints. when you hit 50 concurrent threads, you are likely exceeding the default 100 requests per minute for that specific tenant tier.
for legal discovery or bulk data pulls, we never hammer the api directly. instead, we use the asynchronous job queue. here is how we structure the request to avoid the 403:
from purecloudplatformclientv2 import PlatformClient, BulkApi
client = PlatformClient()
client.login_client_credentials('your_client_id', 'your_client_secret')
bulk_api = BulkApi(client)
# define the export scope
body = {
"name": "legal_perm_export_001",
"destination": {
"type": "s3",
"bucket": "your-bucket-name",
"prefix": "permissions/"
},
"filters": {
"division_id": "your_division_id"
}
}
# this creates a job, not a direct read
job = bulk_api.post_bulkjobs(body=body)
print(f"job id: {job.id}")
this moves the load from the sync api to the background worker. the job will process the permissions export without hitting the 403 limit. also, ensure your s3 bucket policy allows write access from the genesys cloud service principal. if you need the full chain of custody for these permission changes, you might want to enable the audit trail filter in the job definition. this ensures the metadata includes the timestamp of the export request, which is critical for discovery. the job status can be polled via the get bulk jobs endpoint. this is the only reliable way to handle bulk admin data under load.