Screen Recording API 429 errors during JMeter load test

Stuck on rate limiting when triggering screen recordings via the API during peak load simulation. Using JMeter with 200 concurrent threads, the /api/v2/interactions/screenrecordings endpoint returns 429 Too Many Requests after just 50 calls.

429 Too Many Requests: Rate limit exceeded for tenant scope.

Is there a specific concurrency cap for screen recording initiation that I am missing in the docs?

Have you tried staggering the JMeter thread groups instead of firing all 200 at once? The screen recording endpoint has a strict tenant-wide burst limit.

Batching requests usually prevents the 429s without needing config changes.

You need to align the JMeter pacing with the tenant’s actual burst capacity. The suggestion above regarding staggering threads is correct, but the specific throughput rate needs adjustment for screen recording endpoints. These endpoints are resource-intensive and often have lower rate limits than standard interaction APIs.

The payload structure itself is likely fine, but the request frequency is the bottleneck. Ensure the JSON body includes the correct interaction ID and recording type to avoid unnecessary validation overhead on the server side.

{
 "interactionId": "valid-interaction-id",
 "recordingType": "screen",
 "metadata": {
 "source": "load-test"
 }
}

Reduce the concurrent threads to 50 initially. Monitor the Retry-After header in the 429 response. It usually indicates a 60-second cooldown. Implement an exponential backoff strategy in the JMeter script. This approach prevents the tenant-wide rate limit from triggering during peak simulation. Verify the queue activity metrics afterward to ensure the recordings are starting as expected without impacting agent performance dashboards.

You need to adjust your JMeter configuration to respect the tenant-level burst limits, but also consider the downstream storage implications for legal discovery workflows. The 429 error is a protective mechanism, not just a cap on initiation. When screen recordings start, metadata is immediately written to the audit trail. If you initiate 200 concurrent sessions, the metadata ingestion pipeline can bottleneck before the audio/video streams even stabilize.

For digital channels, we often see similar rate-limiting behaviors when bulk exporting metadata for legal holds. The system prioritizes data integrity over speed. Staggering threads is correct, but you must also implement exponential backoff in your JMeter script. A simple linear ramp-up is insufficient because the tenant’s effective capacity fluctuates based on current system load.

Consider using a Constant Throughput Timer in JMeter instead of a fixed concurrency model. Set the target throughput to 15 requests per minute per tenant scope initially. This aligns better with the asynchronous nature of screen recording initialization.

Warning: Do not ignore the 429 response by blindly retrying immediately. This can trigger temporary IP bans or degrade performance for actual agents.

Here is a sample JSON payload structure that minimizes overhead during the initiation phase. Keep the body lean:

{
 "interactionId": "string",
 "recordingType": "screen",
 "metadata": {
 "legalHold": true,
 "retentionPeriod": "7y"
 }
}

Including minimal metadata reduces the parsing load on the API gateway. For large-scale testing, simulate realistic agent behavior rather than pure burst volume. The documentation suggests that screen recording APIs share resources with interaction routing, so high concurrency here can impact call quality. Monitor the X-RateLimit-Remaining header in your responses to dynamically adjust your test pace. This approach ensures your load test reflects actual production constraints while maintaining chain of custody for any test data generated.