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Slack Alerter

How to send automated alerts to a Slack channel
The SlackAlerter enables you to send messages to a dedicated Slack channel directly from within your pipelines.
The slack integration also contains the following two standard steps:
  • slack_alerter_post_step takes a string, posts it to Slack, and returns True if the operation succeeded, else False.
  • slack_alerter_ask_step does the same as slack_alerter_post_step, but after sending the message, it waits until someone approves or rejects the operation from within Slack (e.g., by sending "approve" / "reject" to the bot in response). slack_alerter_ask_step then only returns True if the operation succeeded and was approved, else False.
Interacting with Slack from within your pipelines can be very useful in practice:
  • The slack_alerter_post_step allows you to get notified immediately when failures happen (e.g., model performance degradation, data drift, ...),
  • The slack_alerter_ask_step allows you to integrate a human-in-the-loop into your pipelines before executing critical steps, such as deploying new models.

How to use it

Requirements

Before you can use the SlackAlerter, you first need to install ZenML's slack integration:
zenml integration install slack -y
See the Integrations page for more details on ZenML integrations and how to install and use them.

Setting Up a Slack Bot

In order to use the SlackAlerter, you first need to have a Slack workspace set up with a channel that you want your pipelines to post to.
Then, you need to create a Slack App with a bot in your workspace.
Make sure to give your Slack bot chat:write and chat:write.public permissions in the OAuth & Permissions tab under Scopes.

Registering a Slack Alerter in ZenML

Next, you need to register a slack alerter in ZenML and link it to the bot you just created. You can do this with the following command:
zenml alerter register slack_alerter \
--flavor=slack \
--slack_token=<SLACK_TOKEN> \
--default_slack_channel_id=<SLACK_CHANNEL_ID>
Here is where you can find the required parameters:
  • <SLACK_CHANNEL_ID>: Open your desired Slack channel in a browser, and copy out the last part of the URL starting with C.....
  • <SLACK_TOKEN>: This is the Slack token of your bot. You can find it in the Slack app settings under OAuth & Permissions.
After you have registered the slack_alerter, you can add it to your stack like this:
zenml stack register ... -al slack_alerter

How to Use the Slack Alerter

After you have a SlackAlerter configured in your stack, you can directly import the slack_alerter_post_step and slack_alerter_ask_step steps and use them in your pipelines.
Since these steps expect a string message as input (which needs to be the output of another step), you typically also need to define a dedicated formatter step that takes whatever data you want to communicate and generates the string message that the alerter should post.
As an example, adding slack_alerter_ask_step() into your pipeline could look like this:
from zenml.integrations.slack.steps.slack_alerter_ask_step import slack_alerter_ask_step
from zenml.steps import step
from zenml.pipelines import pipeline
@step
def my_formatter_step(artifact_to_be_communicated) -> str:
return f"Here is my artifact {artifact_to_be_communicated}!"
@pipeline
def my_pipeline(..., formatter, alerter):
...
artifact_to_be_communicated = ...
message = formatter(artifact_to_be_communicated)
approved = alerter(message)
... # Potentially have different behavior in subsequent steps if `approved`
my_pipeline(
...
formatter=my_formatter_step(),
alerter=slack_alerter_ask_step(),
).run()
For complete code examples of both Slack alerter steps, see the slack alerter example, where we first send the test accuracy of a model to Slack and then wait with model deployment until a user approves it in Slack.
For more information and a full list of configurable attributes of the Slack alerter, check out the API Docs.