Okay, so -1 to anyone suggesting it’s just a simple throttling issue.
We’re polling the queue metrics endpoint - you know, standard queue stats - every 30 seconds. It’s to power a small widget on our internal portal. The idea is, if agents are on AUX, show it, if not, show the queue length. Pretty basic.
The code itself is in a SvelteKit server route. It’s using fetch with the platformClient for auth. That’s the official method, right? It’s all OAuth proxied, so the token should be valid. The platformClient version is 6.1.0.
But we’re getting intermittent 429 Too Many Requests errors. Which is… strange.
I’ve checked the rate limits documentation - it says 60 requests per minute. We’re well below that, even allowing for a bit of buffer. The widget is only tracking a handful of queues. It’s not like we’re hammering it with hundreds of requests.
Here’s a sample error payload. It’s not consistent - sometimes it’s a different error message, but always a 429.
{
"message": "Rate limit exceeded. Please try again later.",
"code": 429,
"details": [
{
"field": null,
"message": "Rate limit exceeded"
}
]
}
The logs show the request going out with a valid access token. We’re handling the token refresh properly. It’s not a token issue. I think it’s something with the endpoint itself. +1 if someone’s seen this before. Is there a hidden rate limit I’m missing? It’s breaking the widget, and we need it to be RELIABLE.
Is the queueId static, or are you dynamically resolving it?
- genesyscloud-client-app-sdk’s analytics API is sensitive to concurrent requests - try capping the concurrent
fetch calls to 5-10. Something like: for (let i = 0; i < queueArray.length; i++) { await limitConcurrent(async () => { fetch(...) })}.
- That 429 likely isn’t the rate limit itself, but a burst - add jitter to your 30s polling interval.
random(25 - 35).
2 Likes
genesys-cloud-sdk’s analytics API is pretty sensitive. The approach above is right to suggest jitter - we’ve seen that help, but it’s not always enough. From what I’ve seen, the 429s happen when the queueId is changing frequently. If you’re looping through queues and the IDs aren’t cached, you’re hitting it repeatedly. Try caching the queue IDs and only refetching them if the queue name changes.
Here’s a basic example of how to do that in Node:
const queueCache = {};
async function getQueueId(queueName) {
if (queueCache[queueName]) {
return queueCache[queueName];
}
// fetch the queue ID from /api/v2/users
// store in queueCache[queueName]
}
2 Likes
That jitter suggestion - it’s good, yes? We’ve seen similar with the embeddable framework when we try to get real-time stats for the agent desktop. The API…it doesn’t like being called too quickly.
But, small thing - the caching idea is also important. The queue IDs…are they strings? Or numbers? I always forget. If they’re strings, maybe there is a diffing problem.
Also, are you sure the platformClient is using the correct app context? We had a case where the permissions weren’t set up properly on the app, so it was getting 429s even though the user had the right role. Check the app settings in Genesys Cloud - the OAuth Client part.
Here’s a snippet - it’s not tested, sorry - of how we handle the queue list. We cache it in the component state.
import { usePlatformClient } from '@genesyscloud/genesys-cloud-sdk-client-app';
function useQueues() {
const { platformClient } = usePlatformClient();
const [queueList, setQueueList] = React.useState<any[]>([]);
const [loading, setLoading] = React.useState(true);
React.useEffect(() => {
const fetchQueues = async () => {
try {
const response = await platformClient.api.getQueues();
setQueueList(response.data);
} catch (error) {
console.error('Error fetching queues', error); // log cuts off...
} finally {
setLoading(false);
}
};
fetchQueues();
}, [platformClient]);
return { queueList, loading };
}
Not 100% sure this helps. We are also having issues with the recording webhook.
yeah that caching thing As noted above is super key - we ran into something similar a while back. It’s not just the queue ID changing, it’s the whole analytics context.
Cause:
The analytics API is kinda picky about how often you ask for the same data, especially if the underlying queue structure changes a lot. Every time you hit that endpoint, it’s re-evaluating the whole query, and if you’re bouncing around queue IDs quickly, it interprets that as a denial-of-service attempt - hence the 429. It’s not a hard rate limit, it’s more like “chill out for a sec”.
Solution:
Caching is good, but we found we needed to be a little more aggressive about it. We actually store the queue’s entire analytics config (including associated users and wrap-up codes) in a Redis cache. When the queue name changes, then we refresh everything. It sounds like overkill, but it cut down our 429s to almost zero.
Here’s a simplified example of how we do that - it’s Node, but you can adapt it. We’re using node-cache for this, but Redis is better if you have it.
const NodeCache = require( "node-cache" );
const myCache = new NodeCache( { stdTTL: 3600 } ); // 1 hr TTL
async function getQueueAnalytics(queueName) {
const cachedData = myCache.get(queueName);
if (cachedData) {
return cachedData;
}
// Fetch analytics from Genesys Cloud
// ... your fetch code here ...
const analyticsData = await fetchAnalyticsFromGC(queueName);
// Store in cache
myCache.set(queueName, analyticsData);
return analyticsData;
}
It’s a bit more code, yeah, but trust me, it’s worth it. We’re on Genesys Cloud and these APIs can be…temperamental.