Struggling to figure out why my POST to /api/v2/analytics/conversations/aggregates returns a 400 Bad Request. My gRPC service needs a custom interval for high-throughput processing. I am using this config:
query:
interval: PT1H
dateFrom: 2023-10-01T00:00:00Z
dateTo: 2023-10-02T00:00:00Z
groupBy:
- queueId
metrics:
- answeredCount
The error says interval is invalid. Is PT1H unsupported? How do I structure this correctly?
What’s happening here is that the interval parameter in the Genesys Cloud Analytics API strictly requires an ISO 8601 duration string, but the validation logic often fails if the input is not explicitly formatted or if the date range exceeds the maximum allowed window for that specific granularity. While PT1H is technically valid ISO 8601, the API sometimes rejects it if it is passed as a raw string without proper escaping in certain SDK wrappers or if the dateFrom and dateTo span a period that creates too many buckets. Ensure your JSON payload explicitly quotes the interval as "PT1H" and verify that the total number of intervals does not exceed 200. If you are using the Python SDK, construct the query object using PureCloudPlatformClientV2.AnalyticsApi and ensure the interval field is set via the AnalyticsQuery model rather than a raw dictionary. Also, check that your OAuth token includes the analytics:query scope. A common pitfall in CI pipelines is using environment variables that inadvertently strip quotes, causing the parser to reject the duration format.
The simplest way to resolve this is ensuring the ISO 8601 duration string is correctly parsed by the SDK client. The raw string often causes serialization issues in request bodies.
Use the PureCloudPlatformClientV2 configuration to explicitly set the interval. This ensures proper JSON encoding before the HTTP POST request is executed.
config = PureCloudPlatformClientV2.Configuration()
query.interval = "PT1H"I’d recommend looking at at how you are constructing the request body. The issue isn’t necessarily the ISO 8601 format of PT1H, but rather how the JSON serializer handles the groupBy and metrics arrays when mixed with scalar strings in some Node.js environments.
I ran into this recently while building a webhook consumer that needs to pull hourly aggregates for a queue performance dashboard. The 400 error often masks a serialization mismatch where the API expects specific object structures for the grouping dimensions.
Here is a working curl example that bypasses SDK serialization quirks entirely. Notice the explicit structure for the query object:
curl -X POST "https://api.mypurecloud.com/api/v2/analytics/conversations/aggregates" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <YOUR_ACCESS_TOKEN>" \
-d '{
"query": {
"interval": "PT1H",
"dateFrom": "2023-10-01T00:00:00Z",
"dateTo": "2023-10-02T00:00:00Z",
"groupBy": [
"queueId"
],
"metrics": [
"answeredCount"
]
}
}'
If you are using the Node.js SDK, ensure you are not passing the interval as a raw string outside the query object. The SDK method getAnalyticsConversationsAggregates requires a QueryAnalyticsRequest object.
const apiInstance = new platformClient.AnalyticsApi();
const body = {
query: {
interval: 'PT1H',
dateFrom: '2023-10-01T00:00:00Z',
dateTo: '2023-10-02T00:00:00Z',
groupBy: ['queueId'],
metrics: ['answeredCount']
}
};
apiInstance.getAnalyticsConversationsAggregates(body).then(
(data) => {
console.log('Success:', data);
},
(error) => {
console.error('Error:', error);
}
);
Check your dateFrom and dateTo values. If the range spans more than 30 days with an hourly interval, the API will reject it. Break it into smaller chunks if needed. Also, verify your token has the analytics:query scope.
Have you tried validating the date range against the interval? a 24-hour window with PT1H works, but larger ranges often trigger hidden limits.
the platform rejects queries where the resulting bucket count exceeds internal thresholds. check your dateFrom and dateTo values carefully.
use a smaller window first to isolate the serialization issue from the validation logic.
{ "dateFrom": "2023-10-01T00:00:00Z", "dateTo": "2023-10-01T02:00:00Z" }