How do I create GCP Cloud Logging Custom Metrics?

Introduction

In this guide, we will demonstrate how to create custom metrics for GCP Cloud Logging. Custom metrics help you monitor your application’s performance by creating alerts or aggregations specific to your needs. We will walk through setting up the required resources and configuring a custom metric.

Key Points

• Define a custom logging metric in GCP Cloud Logging.
• Understand the basic setup and components.
• Implement resources with reusable configurations.

Implementation

Let’s dive into the configuration. This program sets up a custom logging metric in GCP, allows us to monitor specific logs, and create custom metrics based on those logs.

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const customMetric = new gcp.logging.Metric("custom_metric", {
    name: "custom-error-metric",
    description: "A custom metric to count error logs",
    filter: "severity>=ERROR",
    metricDescriptor: {
        metricKind: "DELTA",
        valueType: "INT64",
        labels: [{
            key: "example-identifier",
            valueType: "STRING",
            description: "An identifier to distinguish logs",
        }],
    },
});
export const metricName = customMetric.name;
export const metricFilter = customMetric.filter;

Key Points Summary

• The provider block configures the GCP project and region.
• The google_logging_metric resource defines the custom metric with a specific log filter (severity>=ERROR).
• The metric_descriptor block specifies the kind and type of the metric.
• Outputs are provided for visibility of the metric name and filter.

Conclusion

In this example, we created a custom logging metric within GCP Cloud Logging. Custom metrics are powerful for tailored monitoring and alerting solutions. You can further utilize these metrics for specific dashboards and alerts in GCP.