Model Performance Alerting with Custom Thresholds

Question

Pulumi · Accepted Answer

To set up model performance alerting with custom thresholds, we could use a monitoring system provided by one of the major cloud providers or a third-party service like New Relic or Dynatrace. These systems allow you to monitor metrics and log data for your applications and create alerts based on custom thresholds.

For this example, I will demonstrate how to use New Relic to configure custom alert policies and conditions that will notify you when your model performance deviates from certain thresholds. We will create an alert policy and establish conditions for it.

Here's a high-level overview of what we'll do:

1. Create an Alert Policy: This policy groups together several conditions and specifies how notifications should be sent.
2. Establish Alert Conditions: We define the specific criteria that trigger an alert under the policy. Here you can set up custom thresholds for your model's performance metrics.
3. Assign Notification Channels: These are methods by which you're alerted (e.g., email, Slack, webhooks).

The following program will set up an alert policy with New Relic using Pulumi:

```python
import pulumi
import pulumi_newrelic as newrelic

# Create a New Relic alert policy
alert_policy = newrelic.AlertPolicy("modelPerformancePolicy",
    name="Model Performance Policy",
    incident_preference="PER_POLICY"
)

# Define performance conditions with custom thresholds
# For example, this could be a condition where the response time of an endpoint used by your model is too high
# To fill in the actual details, you would use specific New Relic metrics applicable to your model
alert_condition = newrelic.AlertCondition("highResponseTime",
    policy_id=alert_policy.id,
    type="apm_app_metric",
    entities=["YOUR_APPLICATION_ID"],
    metric="response_time_web",
    condition_scope="application",
    terms=[newrelic.AlertConditionTermArgs(
        duration=5,
        operator="above",
        priority="critical",
        threshold=1.5,  # Custom threshold set here
        time_function="all"
    )]
)

# pulumi.export to output the IDs of created policy and condition
pulumi.export("alert_policy_id", alert_policy.id)
pulumi.export("alert_condition_id", alert_condition.id)
```

In this program:
- We import the necessary modules from Pulumi and New Relic.
- We create an alert policy named "Model Performance Policy".
- We then establish an alert condition for a high response time, where you'd replace `"YOUR_APPLICATION_ID"` with your New Relic application id, and set the custom threshold you desire for the response time metric.
- In the `terms` list, you define the actual threshold parameters like duration, threshold value, and the condition's priority. You would replicate this alert condition or create multiple conditions to cover all the performance metrics you want to monitor for your model.
- Finally, we export the alert policy and condition IDs so that you can reference them as needed.

Please replace `"YOUR_APPLICATION_ID"` with your actual New Relic Application ID and configure the threshold according to your model's performance characteristics.

You should already have the New Relic provider set up with the appropriate API keys and access permissions. If not, you must configure them as prerequisites before deploying this Pulumi program. Save this program in a `.py` file and run it using the Pulumi CLI to apply the configurations to your New Relic account.