Add notifications on a job

You can set up notifications to be sent on runs of a job and individual job tasks for the following events:

• Start
• Successful completion
• Failure
• The duration exceeds a configured threshold

You can send notifications to one or more email addresses or third-party destinations such as Slack, Microsoft Teams, PagerDuty, or any webhook-based service. This article describes the different ways you can set up job-level notifications.

Add third-party system destinations

You can set up notifications to be delivered to third-party systems. Third-party system destinations integrate with popular notification tools, including Slack, PagerDuty, Microsoft Teams, and HTTP webhooks. An administrator must configure system destinations.

note

Some external systems, such as Amazon SES and SNS, can integrate using email notifications. See Setting up Amazon SES email receiving.

To configure system destinations, go to the admin settings page, click Edit system notifications and then click Create new destination. For each job or task, you can configure a maximum of three system destinations for each notification event type. See admin settings page.

important

The content of Slack and Microsoft Teams messages might change in future releases. You should not implement clients or processing that depend on the specific content or formatting of these messages. If you require a specific schema or formatting for notifications, Databricks recommends configuring a user-defined webhook.

Configure notifications on a job

Before you begin, consider the following:

• Job-level notifications aren't sent when failed tasks are retried. To receive a failure notification after every failed task, use task notifications instead. To add notifications for task runs, click Add next to Notifications in the task panel when you add or edit a job task.
• For each job or task, you can configure a maximum of three system destinations for each notification event type.
• A job that has been completed in a Succeeded with failures state is considered to be in a successful state. To be notified when jobs have been completed in this state, you must select Success when you configure notifications.
• To be notified when your job exceeds a duration limit, you must set the limit.

To add one or more notifications when a job run begins, is completed, or fails, do the following:

1. In the Job details panel for your job, scroll down to the Job notifications section, and then click Edit notifications.
2. In the lower-left corner, click Add notification.
3. In Destination, select Email address or a system destination.
4. Select the check boxes for each type of event that you want to be notified about: Start, Success, Failure, Duration warning, or Streaming backlog.
5. To configure another destination, click Add notification again and follow the previous steps.
6. After you have configured all of the notifications, click Save.

Configure notifications for slow jobs

If you have configured an expected duration for a job, you can add an email or system notification if the job or task exceeds the configured threshold. To receive a notification for a job or task that exceeds a duration threshold, select Duration Warning when you add or edit a notification. To receive a notification for a job or task that exceeds a streaming backlog metric, select Streaming backlog when you add or edit a notification.

The following applies to streaming backlog metrics:

• Notifications are sent when the average backlog over a 10-minute period exceeds the defined threshold.
• To prevent excessive messages, Databricks waits 30 minutes before determining whether to send another message. While the backlog remains high, you'll receive updates at 30-minute intervals.

Filter out notifications for skipped or canceled runs

You can reduce the number of notifications sent by filtering out notifications when a run is skipped or canceled. To filter notifications, select Mute notifications for skipped runs or Mute notifications for canceled runs when you add or modify email notifications or system notifications.

By default, tasks are retried three times before failing fully. When configuring task notifications, you can select Mute notifications until the last retry to filter out all notifications until the final retry.

note

When you select Mute notifications for skipped runs or Mute notifications for canceled runs for a job, it doesn't filter out notifications configured for job tasks. To filter all notifications for skipped or canceled runs, you must also filter out any task-level notifications you have configured.

HTTP webhook payloads

You can configure HTTP webhooks to be sent on the events listed in the following table.

Event_type code	When is it sent?
jobs.on_start	Sent when a run starts.
jobs.on_success	Sent when a run stops and is completed in a successful or succeeded with failures state.
jobs.on_failure	Sent when a run stops in an unsuccessful state.
jobs.on_duration_warning_threshold_exceeded	Sent when a run has been running for more than the configured expected duration.

The following are example payloads sent by Databricks to your configured endpoint. These webhooks can be applied to either jobs or tasks.

Notification for a job run start event:

JSON

{
  "event_type": "jobs.on_start",
  "workspace_id": "your_workspace_id",
  "run": {
    "run_id": "run_id"
  },
  "job": {
    "job_id": "job_id",
    "name": "job_name"
  }
}

Notification for a task run start event:

JSON

{
  "event_type": "jobs.on_start",
  "workspace_id": "your_workspace_id",
  "task": {
    "task_key": "task_name"
  },
  "run": {
    "run_id": "run_id_of_task"
    "parent_run_id": "run_id_of_parent_job_run"
  },
  "job": {
    "job_id": "job_id",
    "name": "job_name"
  }
}

Notification for a job run failure:

JSON

{
  "event_type": "jobs.on_failure",
  "workspace_id": "your_workspace_id",
  "run": {
    "run_id": "run_id"
  },
  "job": {
    "job_id": "job_id",
    "name": "job_name"
  }
}

Notification for a task run success:

JSON

{
  "event_type": "jobs.on_success",
  "workspace_id": "your_workspace_id",
  "task": {
    "task_key": "task_name"
  },
  "run": {
    "run_id": "run_id_of_task"
    "parent_run_id": "run_id_of_parent_job_run"
  },
  "job": {
    "job_id": "job_id",
    "name": "job_name"
  }
}