---
title: "Get jobs/queries calling a model serving endpoint"
method: GET
path: "/api/v1/databricks/ai-ml-services/endpoints/{endpoint_name}/callers"
tags: ["DATABRICKS", "Databricks", "Databricks AI/ML Services"]
---

# Get jobs/queries calling a model serving endpoint

`GET /api/v1/databricks/ai-ml-services/endpoints/{endpoint_name}/callers`

Get list of jobs/queries that are calling a model serving endpoint.

This endpoint identifies the source of model serving endpoint calls by analyzing:
- Query history for AI function calls (ai_classify, ai_summarize, etc.)
- Job information from query_source metadata
- Notebook IDs for notebook-based calls

Path Parameters:
- endpoint_name: Endpoint name (required)

Query Parameters:
- start_date: Start date (YYYY-MM-DD), defaults to 30 days ago
- end_date: End date (YYYY-MM-DD), defaults to today
- limit: Max rows to return (default: 50, max: 1000)
- offset: Pagination offset (default: 0)

Returns:
- callers: List of jobs/queries with call frequency metrics
- pagination: Pagination info (total, limit, offset)

## Path parameters

- `endpoint_name` string, required

## Query parameters

- `start_date` string, date, nullable — Start date (YYYY-MM-DD), defaults to 30 days ago
- `end_date` string, date, nullable — End date (YYYY-MM-DD), defaults to today
- `limit` integer — Max rows to return
- `offset` integer — Pagination offset
- `navigationSource` string, nullable

## Headers

- `x-tenant` string, required

## Response `200`

Successful Response

- EndpointCallersListResponse — Response for listing jobs/queries calling an endpoint.
  - `callers` EndpointCallerItem[] — List of callers (jobs/queries)
    - `job_id` string, nullable — Job ID from Lakeflow/Workflows
    - `job_name` string, nullable — Job name
    - `notebook_id` string, nullable — Notebook ID if called from notebook
    - `executed_by` string, nullable — User who executed the query (for direct queries)
    - `caller_type` string, required — Type of caller: 'job', 'notebook', or 'query'
    - `query_count` integer — Total number of queries/invocations
    - `unique_queries` integer — Number of unique query statements
    - `first_execution` string, nullable — First execution timestamp
    - `last_execution` string, nullable — Last execution timestamp
    - `days_active` integer — Number of days with activity
    - `avg_queries_per_day` number — Average queries per active day
    - `cost_per_inference` number — Estimated cost per inference in the endpoint currency. The endpoint's billed cost is allocated to this caller by its share of tokens, then divided by its invocations; falls back to the flat endpoint rate (endpoint cost / total invocations) when token counts are unavailable.
  - `pagination` AppSchemasDatabricksAiServicesPaginationInfo, required — Pagination information.
    - `total` integer, required — Total number of items
    - `limit` integer, required — Items per page
    - `offset` integer, required — Current offset

## Other responses

- `403` — Not authorized
- `404` — Resource not found
- `422` — Validation Error

---

[API](https://skmtc.dev/myaltimate/apis/fastapi.md) · [All operations](https://skmtc.dev/myaltimate/apis/fastapi/llms.txt) · [OpenAPI document](https://skmtc-service-production.skmtc.workers.dev/v1/apis/myaltimate/fastapi/revisions/b8f442483dc9/schema)