I’ve spent hours trying to figure out why the bulk export job fails immediately after initiation when including specific custom dimensions in the query body.
The standard interaction export works perfectly. No issues with base metrics like total_handle_time or abandoned_count.
Problem starts when adding routing_queue_id alongside a custom dimension defined in our CX-as-Code pipeline.
Error response from POST /api/v2/analytics/reporting/interaction/exports:
Status: 400 Bad Request
Body: {"message": "Invalid dimension combination. Dimension 'custom_attr_01' is not compatible with 'routing_queue_id' in this context.", "code": "invalidDimensionCombination"}
Terraform configuration for the custom attribute:
resource "genesyscloud_routing_custom_attribute" "attr_01" {
name = "custom_attr_01"
type = "string"
scope = "interaction"
}
This issue stems from the custom dimension schema not matching the expected format for the analytics export endpoint. when you push custom dimensions via cli, they need to be pre-registered in the org settings first. check if those dimensions exist in admin > analytics > custom dimensions. if they are missing, the api returns a 400 bad request because it cannot map the field. also, verify the time zone. since we are on central time here, sometimes the utc conversion in the query body gets messed up if the runner is in a different zone. try adding the explicit timezone parameter to the curl command. another thing to check is the data action timeout. if the external endpoint is slow, the cli might drop the connection before the schema validation completes. restart the job with a longer timeout value. usually, this resolves the immediate failure.
It’s worth reviewing at how the dimension registration process differs from the legacy Zendesk workflow. In Zendesk, custom ticket fields were often available immediately after creation. Genesys Cloud requires a stricter handshake between the Admin configuration and the Analytics engine. The 400 error usually signals that the CLI is querying a dimension that hasn’t fully propagated through the internal schema cache.
Try validating the dimension ID directly in the Admin console under Analytics > Custom Dimensions. Ensure the status is “Active” and not “Draft.” If it is active, wait ten minutes before retrying the CLI command. This propagation delay is a common hurdle during migrations. We often see similar latency when moving from Zendesk’s real-time field updates to GC’s batched indexing. Double-check that the dimension key in your JSON payload matches the internal ID exactly, not just the display name.
Make sure you verify that the custom dimensions referenced in your CLI export query are explicitly mapped within the Genesys Cloud Admin console under Analytics settings before initiating any bulk data retrieval process. The 400 Bad Request error typically indicates a schema mismatch where the analytics engine cannot locate the field definition corresponding to the dimension ID provided in the JSON body. From a performance monitoring perspective, this often occurs when teams attempt to pull metrics for dimensions that are still in a draft state or have not been fully propagated across the regional data centers, such as ap-southeast-2. It is critical to confirm that the dimension status shows as ‘Active’ and that the associated data types align with the export format requirements. Additionally, consider reviewing the time zone configuration within the query parameters, as discrepancies between the server UTC time and the local agent shift schedules can cause validation failures during the initial handshake. The documentation suggests that pre-registering these fields ensures the internal schema cache is updated, preventing immediate rejection by the API gateway. If the dimensions appear correctly configured, check for any recent changes to the Architect flow that might have altered the interaction metadata structure, as this can invalidate previously working export templates. A systematic review of the dimension mapping table in the Admin UI usually resolves these connectivity issues without requiring complex API debugging.
This looks like a schema mismatch. Ensure the custom dimension IDs in query.dimensions match exactly what is registered in Admin, as the analytics engine rejects unmapped fields with a 400.