Slack Alerter
Sending automated alerts to a Slack channel.
Slack Alerter
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:
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:
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.
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:
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 withC....
.<SLACK_TOKEN>
: This is the Slack token of your bot. You can find it in the Slack app settings underOAuth & Permissions
. IMPORTANT: Please make sure that the token is theBot User OAuth Token
not theUser OAuth Token
.
After you have registered the slack_alerter
, you can add it to your stack like this:
How to Use the Slack Alerter
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()
to your pipeline could look like this:
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