I’m trying to build a reliable trace pipeline for Data Action calls using OpenTelemetry. The goal is to attach a traceparent header to outbound HTTP requests initiated by a Data Action so I can correlate the Genesys Cloud side with my backend services in Jaeger.
I’ve been using the internal callback URL for the Data Action. To populate the span context, I need the conversation ID and some metadata. I noticed there are two endpoints that seem to return similar data:
GET /api/v2/conversations/{conversationId}GET /api/v2/analytics/conversations/details/query
The first one gives me the live conversation object. The second one is the analytics endpoint.
Here’s the issue. When I use the live conversations endpoint inside a Data Action, sometimes the response is delayed or returns a 404 if the conversation just spun up. It feels flaky for tracing purposes. The analytics endpoint feels more stable, but the data is often 1-2 minutes behind. That lag breaks my real-time tracing.
I’m calling these via curl from the Data Action’s HTTP request step. Here’s the JSON I’m passing to get the details:
{
"query": {
"type": "filter",
"predicate": {
"type": "fieldEquals",
"fieldName": "conversationId",
"value": "{{conversation.id}}"
}
}
}
Is there a hard rule on which endpoint to use for programmatic access within a Data Action? I need the data to be available immediately to inject the trace context. Using the analytics endpoint introduces too much latency for the span propagation logic I’ve written.
Also, does the client_credentials flow have different rate limits for these two endpoints? I’m hitting 429s when I try to poll the live endpoint in a tight loop.
Here’s the curl command I’m using:
curl -X GET "https://api.mypurecloud.com/api/v2/conversations/{{conversation.id}}" \
-H "Authorization: Bearer {{token}}" \
-H "Content-Type: application/json"
If I switch to the analytics endpoint, I have to wait. If I stay on the live endpoint, I get 404s or 429s. What’s the standard pattern here for external tracing?