We’re refactoring the Node.js service that tracks active call volume for our dashboard. I’ve been using the conversationsApi.getConversations endpoint from the JS SDK to poll for live state, but it’s getting slow with high concurrency. The docs mention /api/v2/analytics/conversations/queues/realtime as an alternative, but the payload structure is completely different. I’m confused about when to actually use the analytics endpoint versus the core conversations API. It feels like the analytics endpoint is meant for historical data, yet it has a ‘realtime’ tag. I tried swapping the calls in our Express route, but the aggregation logic breaks because the analytics response groups by queue ID instead of returning individual conversation objects. Here’s the current setup:
const res = await client.conversationsApi.getConversations({
expand: ['participants'],
conversationStates: ['ACTIVE']
});
The analytics endpoint returns a summary object with totalActiveCalls, which is cleaner, but I lose the ability to filter by specific participant attributes without doing extra work. Is there a performance reason to prefer the analytics endpoint for simple ‘is this queue busy’ checks, or should I stick to the core API and just optimize the polling interval? The latency on the analytics endpoint is lower, but the data granularity is annoying.
The analytics endpoint is definitely the way to go for aggregation. The core getConversations call returns individual session objects which is heavy on payload size and processing time when you just need counts.
Here is how I handle it in Node.js using the SDK:
- Switch to
analyticsApi.getAnalyticsConversationsQueuesRealtime.
- Use the
group-by parameter to aggregate by queue or skill.
- Set the
interval to a short window like PT5M if you need near real-time snapshots, or just omit it for the current state.
const { AnalyticsApi } = require('@genesyscloud/genesyscloud');
const analyticsApi = new AnalyticsApi();
async function getQueueMetrics() {
try {
const response = await analyticsApi.getAnalyticsConversationsQueuesRealtime({
groupBy: 'queue',
// Optional: filter by specific queues if you don't need all of them
// filter: 'queue.id IN ("queue-id-1","queue-id-2")'
});
return response.body.entities.map(entity => ({
queueId: entity.splitBy[0].id,
activeCalls: entity.metrics.totalConversationDuration.seconds, // or whatever metric you need
waitCount: entity.metrics.waitCount
}));
} catch (error) {
console.error('Analytics fetch failed:', error);
}
}
The payload from analytics is much lighter. It gives you the aggregated metrics directly. You don’t have to loop through an array of conversation objects to count them yourself. The getConversations endpoint is really only useful if you need to inspect the state of a single specific conversation or manipulate it. For dashboard volume, stick to analytics.