Hi @varshini_reddy ,

What you can do is to add another task at the end of the job to run if one/all dependencies failed.


This task would be a notebook that would make a call to REST API to stop the job.

# Set up the Databricks API endpoint and token
databricks_instance = "<your-databricks-instance>"  # e.g., "https://<your-region>.azuredatabricks.net"
job_id = <your_job_id>  # Replace with the ID of the job you want to disable
personal_access_token = "<your_personal_access_token>"

# API endpoint to update the job
api_url = f"{databricks_instance}/api/2.1/jobs/update"

# Function to disable the job by setting the pause status to PAUSED
def disable_job():
    # Set the payload to pause the job
    payload = {
        "job_id": job_id,
        "new_settings": {
            "schedule": {
                "pause_status": "PAUSED"
            }
        }
    }

    # Send the API request
    response = requests.post(
        api_url,
        headers={"Authorization": f"Bearer {personal_access_token}"},
        json=payload
    )

    # Check if the request was successful
    if response.status_code == 200:
        print(f"Job {job_id} has been successfully paused.")
    else:
        print(f"Failed to pause the job. Status Code: {response.status_code}")
        print(f"Response: {response.text}")

disable_job()