Digital Channel Export 429 Rate Limiting on Metadata Fetch

General Discussion
1
  • Environment: Europe/London
  • Endpoint: /api/v2/analytics/bulk-data/export-jobs
  • Scope: Digital Channel (Chat/Web Messenger)
  • Issue: HTTP 429 Too Many Requests

Why does this setting trigger a rate limit when fetching metadata for a legal hold export?

The bulk export job initiates correctly, but the subsequent polling for job status and metadata retrieval fails repeatedly with 429 errors. The payload specifies view: FULL and includes the necessary legal_hold flags. The request rate is well below the documented limit for standard users, but the system treats the metadata fetch as a separate high-frequency call.

The error response indicates retry-after: 60, which disrupts the automated chain of custody process. The job times out before completion because the retry logic in our script does not handle the exponential backoff correctly for this specific endpoint.

Is there a specific header or parameter to bundle the metadata request with the initial export job to avoid this separation? The current behavior makes it impossible to maintain a continuous audit trail for the discovery request. The S3 bucket permissions are verified, and the IAM role has full access. This issue only appears for digital channels, not voice recordings.

2

try reducing the polling interval in your export request payload.

{
 "interval": "PT30S"
}

the default is too aggressive for metadata fetches.

2 Likes
3

Make sure you…

  • set interval to PT60S in the payload
  • add retry-after parsing to your poller
  • don’t hammer the status endpoint

429s are strict on metadata fetches. pact tests won’t help here, just back off.

4

the suggestion above about increasing the interval is correct, but in our java integration we hit 429s even with PT60S if we don’t handle the headers properly. the api returns a Retry-After header when you get throttled. ignoring it just makes things worse.

we use the java sdk for this. here is how we handle the polling loop to avoid getting blocked:

try {
 while (job.getStatus() != "COMPLETED") {
 Thread.sleep(60000); // wait 60s
 job = bulkDataApi.getExportJob(job.getId());
 }
} ch (ApiException e) {
 if (e.getCode() == 429) {
 int retryAfter = Integer.parseInt(e.getHeaders().get("Retry-After"));
 Thread.sleep(retryAfter * 1000);
 }
}

also check if you have other background jobs running in your org. sometimes the limit is shared across all bulk exports for the tenant. if the rate limiting persists, you might need to split the query into smaller date ranges. it’s annoying but it works.

5

yeah, the retry-after header is key. also check your auth token refresh. if you’re hitting that endpoint too fast with a fresh token, it still 429s. i use a simple backoff in python.

import time
time.sleep(int(response.headers['Retry-After']) + 5)

don’t forget the extra buffer.

1 Like