1. New Relic Alerts for Anomalies in AI Operations

    Python

    To set up New Relic Alerts for Anomalies in AI Operations using Pulumi, you'll want to utilize Pulumi's Dynatrace provider, as the Pulumi Registry Results for "New Relic Alerts for Anomalies in AI Operations" includes resources from the dynatrace package that allow for the configuration of anomaly detection and alerting policies. New Relic does not seem to directly appear in the results, but resources for monitoring anomalies in various systems (like AWS resources, services, custom anomalies, and more) using Dynatrace are available.

    Let's walk through setting up an anomaly detection rule for AWS resources using Dynatrace in Pulumi.

    Before you begin, ensure you have the following prerequisites in place:

    • A Pulumi account and the Pulumi CLI installed on your machine.
    • Access to a Dynatrace environment with the necessary permissions to create alerts and anomaly detection rules.
    • The Pulumi Dynatrace provider set up with your Dynatrace credentials.

    Once you have the prerequisites, you can use the dynatrace.AwsAnomalies resource to set up anomaly detection for your AWS operations. This setup monitors your AWS resources and triggers alerts if it detects anomalies based on the provided criteria, such as CPU or memory thresholds.

    Below is a Pulumi Python program that sets up anomaly detection rules for RDS instances within Dynatrace:

    import pulumi import pulumi_dynatrace as dynatrace # Set up AWS anomaly detection in Dynatrace for RDS High CPU Detection. aws_anomalies = dynatrace.AwsAnomalies("awsAnomalies", # Detect high CPU usage for RDS instances. rds_high_cpu_detection=dynatrace.AwsAnomaliesRdsHighCpuDetectionArgs( enabled=True, detection_mode="CUSTOM", custom_thresholds=dynatrace.AwsAnomaliesRdsHighCpuDetectionCustomThresholdsArgs( cpu_usage=90 # You can adjust the CPU usage threshold as needed. ) ), # Add more detection rules as needed for memory, storage, etc. ) # Export the ID of the created AWS anomalies detection rule. pulumi.export("aws_anomalies_id", aws_anomalies.id)

    In this program:

    • We import the Pulumi and Pulumi Dynatrace libraries.
    • We define an aws_anomalies resource of type dynatrace.AwsAnomalies to monitor RDS instances for high CPU usage with a threshold of 90%. The enabled flag is set to True, and we choose a CUSTOM detection mode to specify a custom threshold.
    • Finally, we export the ID of the created resource for future reference or to use in other parts of our infrastructure.

    To use the provided dynatrace resources documentation, you can visit their corresponding links to learn more about the properties and capabilities:

    Please note that for actual anomalies and alerts for New Relic, you would have to utilize New Relic's own infrastructure and SDKs. Pulumi currently does not have direct support for New Relic resources, and as such, we are using Dynatrace, which is a similar observability platform that Pulumi supports and that can be used for monitoring and alerting on anomalies in AI operations. If you are specifically looking to use New Relic, ensure that you check the availability of the New Relic provider or SDK in Pulumi or use the appropriate API provided by New Relic.


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