POST /api/v2/conversations/voice/{id}/recording/start returns 409 Conflict during active recording

NICE CXone API & Integrations
1

Looking for advice on handling the race condition when programmatically toggling call recordings via the Genesys Cloud REST API for my Datadog trace ingestion pipeline.

I am building a custom metric that tracks the latency between a specific IVR node execution and the start of a recording. To ensure clean data, I stop the default recording immediately after the node executes and start a new one with specific metadata tags. However, I am hitting a 409 Conflict error intermittently.

Steps to reproduce:

  1. Initiate a voice conversation and let the default recording start (handled by org settings).
  2. Wait for the specific IVR node to complete (approx 500ms latency).
  3. Call DELETE /api/v2/conversations/voice/{conversationId}/recording to stop the initial recording.
  4. Immediately call POST /api/v2/conversations/voice/{conversationId}/recording/start with a JSON body containing custom recordingSettings.

The DELETE returns 204 No Content, but the subsequent POST fails with:

I suspect there is a propagation delay in the backend state machine. Should I implement an exponential backoff retry loop in my Node.js SDK wrapper, or is there a more reliable way to query the current recording state via GET /api/v2/conversations/voice/{id} before attempting the restart? I want to avoid dropping metrics due to this API contention.

{
 "code": "conflict",
 "message": "A recording is already in progress for this conversation."
}
2

This looks like you are ignoring the state machine. Check the recording status first. See https://genesys.cloud/support/voice-recording-race-conditions for the proper polling logic.

3

Oh, this is a known issue… Error: 409 Conflict {“code”: 409, “message”: “Conflict”, “status”: “Conflict”, “errors”: [“A recording is already in progress for this conversation.”]} You are hitting the race condition because you are firing the start command before the previous stop request has fully propagated through the backend state machine. The suggestion above about polling is correct but adds unnecessary latency. In my Postman test suites, I handle this by implementing a pre-request script that checks the current recording status via GET /api/v2/conversations/voice/{id}/recordings before attempting to toggle. If the status is “active”, the script waits 500ms and retries once. If it is “stopped” or “none”, it proceeds. This prevents the 409 without blocking the main execution thread. For Newman CLI runs, I wrap this in a retry logic loop with exponential backoff. Here is the pre-request snippet:

const recordingStatus = pm.environment.get("recordingStatus");
if (recordingStatus === "active") {
 console.warn("Recording still active. Retrying...");
 // Logic to delay or retry handled in collection flow
}

Do not ignore the 409. It means your pipeline is desynchronized.

4

If you check the docs, they mention the recording lifecycle is strictly stateful. you cannot simply fire-and-forget start/stop commands. the 409 conflict occurs because the backend state machine has not yet processed the previous stop request.

  1. verify the recording state before attempting to start a new one. use GET /api/v2/conversations/voice/{id}/recordings.
  2. filter the response for state: "active". if active, wait.
  3. implement a retry loop with exponential backoff. do not poll aggressively.

here is a terraform-compatible retry logic snippet for your external automation script:

import time

def start_recording_with_retry(conv_id, client, retries=5):
 for i in range(retries):
 try:
 recs = client.conversation_api.get_conversation_recordings(conv_id)
 active = [r for r in recs.entities if r.state == "active"]
 if not active:
 return client.conversation_api.post_conversation_recording_start(conv_id, body=recording_config)
 except Exception as e:
 if "409" in str(e):
 time.sleep(2 ** i)
 continue
 raise

this avoids the race condition without excessive latency. ensure your terraform modules expose the recording configuration as a variable for flexibility.

5

It’s worth reviewing at the exact payload composition for the HMAC calculation. The documentation states: “The signature is an HMAC-SHA256 hash of the raw request body using the OAuth client secret…”

{
 "recording": {
 "id": "generated-id",
 "state": "stopped"
 }
}

Ignoring the state transition latency will cause your dashboard metrics to diverge from actual recording files.