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Showing content from http://cloud.google.com/kubernetes-engine/docs/how-to/app-performance-metrics below:

Use application performance metrics | Google Kubernetes Engine (GKE)

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You can configure your workloads on Google Kubernetes Engine (GKE) to send application performance metrics to Cloud Monitoring. You can then use these metrics to detect performance regressions in your application. Google Kubernetes Engine provides visualizations for the following kinds of performance measures for your workloads:

• Requests: shows the per-second request rate, grouped by operation when available.
• Errors: shows error rates, grouped by operation and response code.
• Latency: shows 50th and 95th percentile response latency by operation.
• CPU and memory: shows the utilization of CPU and memory as a percentage of a requested amount.

These metrics correspond to the golden signals recommended in the Google Site Reliability Engineering book for monitoring distributed systems.

You can also view and explore logs for your workloads.

Before you can use application performance metrics, your application must have a way to send the metrics to Cloud Monitoring. For information about recommended approaches, see Collect application performance metrics.

You can collect application performance metrics for Google Kubernetes Engine by using the following supported integrations:

• Cloud Service Mesh: If you use Cloud Service Mesh, then application performance metrics are collected automatically.
• Istio: If you use open source Istio, then we recommend that you collect the metrics by using Google Cloud Managed Service for Prometheus.
• GKE Ingress: When you configure GKE Ingress for Application Load Balancers, performance metrics are automatically collected for the HTTP/S load balancers that route traffic to your GKE Service and Deployment resources behind GKE Ingress.
• NGINX Ingress: If you are using NGINX Ingress, then we recommend that you collect the metrics by using Google Cloud Managed Service for Prometheus.
• Prometheus HTTP and gRPC metrics: If your application exposes Prometheus HTTP or gRPC metrics, then we recommend that you follow the HTTP server and gRPC server documents to collect the metrics by using Google Cloud Managed Service for Prometheus.

After the performance data is available for analysis, you can view the metrics for a Deployment on the application dashboard.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-12 UTC.

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