Real-time Alerts for Anomaly Detection Services

Question

Pulumi · Accepted Answer

Real-time alerts for anomaly detection are crucial in a cloud environment to quickly identify and respond to unusual activities that might indicate security incidents, performance issues, or potential system failures. Different cloud providers offer services that can be set up to monitor your infrastructure and applications for anomalies and send alerts when such are detected. In Pulumi, these services can be defined as Infrastructure as Code, enabling repeatable, consistent, and fast deployments.

For this explanation, I'm going to focus on setting up a Dynatrace service for anomaly detection, using the `dynatrace.ServiceAnomaliesV2` resource, which is designed to detect anomalies in service availability. Dynatrace is an AI-driven cloud monitoring platform that can automatically learn the normal behavior of your applications and services and alert you in real-time about any deviations. Utilizing the Dynatrace Service Anomalies resource allows users to define various parameters such as load drops, load spikes, failure rates, and response times, which are essential for identifying potential issues in the services.

Here's a program that creates a Dynatrace Service Anomalies resource:

```python
import pulumi
import pulumi_dynatrace as dynatrace

# Create an Anomaly Detection Service with Dynatrace for monitoring service availability
service_anomalies = dynatrace.ServiceAnomaliesV2("serviceAnomalyDetection",
    # The identifier of the monitored scope (environment or management zone).
    scope="myScopeId",
    # Configuration for detecting load drops.
    load_drops=dynatrace.ServiceAnomaliesV2LoadDropsArgs(
        enabled=True,  # Whether the detection for load drops is enabled.
        load_drop_percent=0.5,  # Percentage of load drop to trigger an alert.
        minutes_abnormal_state=5,  # Number of minutes the service stays in an abnormal state to trigger an alert.
    ),
    # Configuration for detecting load spikes.
    load_spikes=dynatrace.ServiceAnomaliesV2LoadSpikesArgs(
        enabled=True,  # Whether the detection for load spikes is enabled.
        load_spike_percent=0.5,  # Percentage of load spike to trigger an alert.
        minutes_abnormal_state=5,  # Number of minutes the service stays in an abnormal state to trigger an alert.
    ),
    # Configuration for anomaly detection in failure rate.
    failure_rate=dynatrace.ServiceAnomaliesV2FailureRateArgs(
        enabled=True,  # Whether the detection for failure rate anomalies is enabled.
        auto_detection=dynatrace.ServiceAnomaliesV2FailureRateAutoDetectionArgs(
            absolute_increase=0.1,  # The absolute increase (in percentage points) of failure rate to trigger an alert.
            relative_increase=0.2,  # The relative increase (as a factor) of the failure rate to trigger an alert.
            over_alerting_protection=dynatrace.ServiceAnomaliesV2FailureRateOverAlertingProtectionArgs(
                requests_per_minute=10,  # Minimum number of requests per minute to consider for triggering an alert.
                minutes_abnormal_state=5,  # Number of minutes the service stays in an abnormal state to trigger an alert.
            ),
        ),
        detection_mode="DETECT_AUTOMATICALLY",  # The mode of detection for anomalies in the failure rate.
        fixed_detection=dynatrace.ServiceAnomaliesV2FailureRateFixedDetectionArgs(
            threshold=0.05,  # Fixed threshold for failure rate to trigger an alert.
            sensitivity="SENSITIVE",  # Sensitivity level of the fixed anomaly detection.
            over_alerting_protection=dynatrace.ServiceAnomaliesV2FailureRateOverAlertingProtectionArgs(
                requests_per_minute=10,  # Minimum number of requests per minute to consider for triggering an alert.
                minutes_abnormal_state=5,  # Number of minutes the service stays in an abnormal state to trigger an alert.
            ),
        ),
    ),
    # Configuration for anomaly detection in response time.
    response_time=dynatrace.ServiceAnomaliesV2ResponseTimeArgs(
        enabled=True,  # Whether the detection for response time anomalies is enabled.
        auto_detection=dynatrace.ServiceAnomaliesV2ResponseTimeAutoDetectionArgs(
            response_time_all=dynatrace.ServiceAnomaliesV2ResponseTimeAllArgs(
                degradation_percent=0.5,  # Percentage of degradation in response time to trigger an alert.
                degradation_milliseconds=200,  # Milliseconds of degradation in response time to trigger an alert.
            ),
            response_time_slowest=dynatrace.ServiceAnomaliesV2ResponseTimeSlowestArgs(
                slowest_degradation_percent=0.5,  # Percentage of degradation in the slowest response times to trigger an alert.
                slowest_degradation_milliseconds=200,  # Milliseconds of degradation in the slowest response times to trigger an alert.
            ),
            over_alerting_protection=dynatrace.ServiceAnomaliesV2ResponseTimeOverAlertingProtectionArgs(
                requests_per_minute=10,  # Minimum number of requests per minute to consider for triggering an alert.
                minutes_abnormal_state=5,  # Number of minutes the service stays in an abnormal state to trigger an alert.
            ),
        ),
        detection_mode="DETECT_AUTOMATICALLY",  # The mode of detection for anomalies in the response time.
    ),
)

# Export the resource's ID
pulumi.export('serviceAnomalyDetectionId', service_anomalies.id)
```

This Pulumi program sets up anomaly detection for a specific scope within your Dynatrace-monitored environment. You can adjust the settings to match the expected behavior of your services and the level of sensitivity you want for the alerts.

When using this in your environment, you'll replace `"myScopeId"` with the identifier of the environment or management zone you wish to monitor in Dynatrace.

After applying this configuration with Pulumi, the Dynatrace service will begin monitoring the specified parameters and generate alerts based on the thresholds and settings you have defined. You can take actions on these alerts by integrating them with your incident management systems or custom alert handling mechanisms.

For more detailed information about each property and possible values, please refer to the [Dynatrace Service Anomalies V2 documentation](https://www.pulumi.com/registry/packages/dynatrace/api-docs/serviceanomaliesv2/).