Automations overview

​

Core classes

​

Events (Triggers)

​

Actions

​

Filters

​

Common use cases

​

Model performance monitoring

• Alert when model accuracy drops below a threshold
• Notify team when training loss plateaus
• Trigger retraining pipelines based on performance metrics

​

Artifact Management

• Send notifications when new model versions are created
• Trigger deployment workflows when artifacts are tagged
• Automate downstream processing when datasets are updated

​

Experiment tracking

• Alert on failed or crashed runs
• Notify when long-running experiments complete
• Send daily summaries of experiment metrics

​

Integration workflows

• Update external tracking systems via webhooks
• Sync model registry with deployment platforms
• Trigger CI/CD pipelines based on W&B events

​

Example usage

import wandb
from wandb.automations import OnRunMetric, RunEvent, SendNotification

api = wandb.Api()

project = api.project("<my-project>", entity="<my-team>")

# Use the first Slack integration for the team
slack_hook = next(api.slack_integrations(entity="<my-team>"))

# Create a trigger event
event = OnRunMetric(
     scope=project,
     filter=RunEvent.metric("custom-metric") > 10,
)

# Create an action that responds to the event
action = SendNotification.from_integration(slack_hook)

# Create the automation
automation = api.create_automation(
     event >> action,
     name="my-automation",
     description="Send a Slack message whenever 'custom-metric' exceeds 10.",
)