Struggling to figure out why participant attributes written via the Conversations API are not persisting or visible in subsequent requests during a live voice call. I am building a Datadog integration that needs to tag calls with specific trace IDs and custom metadata for APM correlation. The goal is to update the participant attributes in real-time as the call progresses, so I can filter metrics in Datadog based on these tags.
Here is the flow I am implementing:
- I receive a webhook event when a conversation starts.
- I extract the
conversationId and participantId.
- I issue a
PATCH request to /api/v2/conversations/voice/{conversationId}/participants/{participantId} to set custom attributes.
The code snippet looks like this:
const response = await fetch(
`https://api.mypurecloud.com/api/v2/conversations/voice/${convId}/participants/${partId}`,
{
method: 'PATCH',
headers: {
'Authorization': `Bearer ${token}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({
attributes: {
'datadog_trace_id': '123456789',
'custom_metric_tag': 'high_priority'
}
})
}
);
The PATCH request returns a 204 No Content status, which usually indicates success. However, when I immediately fetch the conversation details using GET /api/v2/conversations/voice/{conversationId} to verify the attributes, the attributes object on the participant is empty or missing the new keys. I have waited up to 10 seconds between the write and the read, but the data never appears.
I am using a valid OAuth token with the conversations:read and conversations:write scopes. I have also tried including the If-Match header with the ETag from the initial participant creation, but that results in a 412 Precondition Failed error, suggesting the ETag might be stale or I am not handling concurrency correctly.
Is there a specific rate limit or delay for attribute propagation in the voice API? Or am I missing a required field in the PATCH body to ensure the attributes are saved? Any insights would be appreciated.
Thanks for the help.
I normally fix this by ensuring the payload includes the specific participant ID and uses the correct media type. The API ignores updates if the target isn’t explicitly addressed. Use this curl structure to patch the attributes correctly:
curl -X PATCH "https://api.mypurecloud.com/api/v2/conversations/{conversationId}/participants/{participantId}" \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json" \
-d '{"attributes": {"traceId": "abc123"}}'
The best way to fix this is to stop relying solely on the REST PATCH endpoint for real-time tagging and switch to a data action in architect. the rest api has latency issues and often fails to persist attributes before the next analytics tick, especially for voice calls. you need to trigger the update from within the call flow itself.
set up a data action to call your external rest endpoint (or even a purecloud webhook) to generate the trace id, then immediately use a ‘set participant attributes’ action. you can’t just write to the api from an external service and expect it to sync instantly with the conversation state engine. architect handles the persistence transactionally.
here is how you structure the architect node:
{
"name": "Set Datadog Trace",
"type": "data",
"properties": {
"httpMethod": "POST",
"url": "https://your-internal-api.com/trace-id",
"headers": {
"Authorization": "Bearer {{oauth_token}}"
},
"body": "{\"callId\": \"{{conversation.id}}\"}"
}
}
follow this immediately with a ‘set participant attributes’ action targeting {{participant.id}}. map the response from the data action to a custom attribute like dd.trace.id. this ensures the attribute is locked into the conversation object before any subsequent routing or recording events.
also, make sure your oauth token has conversation:update scopes. if you are using a guest token, it won’t work. you need an app token or a user token with the right permissions. i hit this wall last week with a react native app trying to push metadata back to the cloud. the rest call succeeded (200 ok) but the attribute never showed up in analytics. moving to architect fixed the timing issue. stick to the flow for state changes.
Check your participant ID resolution logic. The issue isn’t the PATCH endpoint itself, but likely a mismatch between the participantId you are sending and the internal server-side ID.
In a live voice conversation, the participantId returned by the initial POST /api/v2/conversations call is often transient or client-specific. You must fetch the canonical conversation entity to get the persistent server-side participantId before attempting to patch attributes. If you are using the Node.js SDK in a Lambda function, ensure you are using PureCloudPlatformClientV2 correctly.
Here is the correct pattern using the Node.js SDK:
const platformClient = PureCloudPlatformClientV2.build();
await platformClient.auth.loginServiceAccount({
clientId: process.env.GC_CLIENT_ID,
clientSecret: process.env.GC_CLIENT_SECRET
});
const conversationsApi = new platformClient.ConversationsApi();
// 1. Fetch the conversation to get valid participant IDs
const conversation = await conversationsApi.getConversation({
conversationId: req.body.conversationId
});
// 2. Identify the correct server-side participant ID
const targetParticipant = conversation.participants.find(p => p.address === req.body.address);
if (!targetParticipant) {
throw new Error('Participant not found');
}
// 3. Patch attributes using the server-side ID
await conversationsApi.patchConversationParticipant({
conversationId: req.body.conversationId,
participantId: targetParticipant.id,
body: {
attributes: {
"datadog.traceId": req.body.traceId,
"custom.metadata": "value"
}
}
});
Using participantId from the webhook event directly without verification often leads to 404s or ignored updates because the webhook payload might reference a different ID scope. Always validate the ID against the live conversation object.
- Verify
participantId against GET /api/v2/conversations/{id}
- Check
X-Genesys-Signature for webhook integrity
- Ensure
routing:queue:read scope if fetching queue details
- Use
application/json content type strictly
it depends, but generally… you are fighting against state drift if you attempt to manage ephemeral conversation data via terraform. the suggestion above regarding the participantId resolution is technically correct for the api layer, but it misses the architectural anti-pattern here. you should not be using a provisioning tool like terraform to patch live runtime entities.
in my modules for cx as code, i strictly separate infrastructure from operational data. if you need persistent tagging for datadog, you must handle this within the architect flow or via a webhook integration, not through rest api calls triggered by external scripts during the call.
here is the correct pattern i use in my terraform modules to provision the necessary webhook for this exact use case:
resource "genesyscloud_integration_action" "datadog_trace" {
enabled = true
name = "datadog_trace_injector"
description = "injects trace id into participant attributes"
action_type = "http"
configuration {
endpoint = var.datadog_webhook_url
method = "POST"
headers = {
"Content-Type" = "application/json"
}
body_template = jsonencode({
trace_id = "{{traceId}}"
call_id = "{{conversationId}}"
})
}
}
- define the integration action in terraform.
- reference this action in your architect flow using a “webhook” block.
- update participant attributes using the “set participant attribute” block immediately after the webhook returns.
this ensures the attributes are set synchronously within the call flow, avoiding the latency issues mentioned earlier. relying on external api calls for real-time participant data is unreliable and introduces race conditions. keep your terraform state clean by only managing static configuration.