Anda dapat mengonfigurasi beban kerja di Google Kubernetes Engine (GKE) untuk mengirim
metrik performa aplikasi ke Cloud Monitoring. Kemudian, Anda dapat menggunakan metrik ini untuk mendeteksi regresi performa di aplikasi Anda.
Google Kubernetes Engine menyediakan visualisasi untuk jenis pengukuran performa berikut untuk workload Anda:
Permintaan: menampilkan tingkat permintaan per detik, yang dikelompokkan menurut operasi jika tersedia.
Error: menampilkan rasio error, yang dikelompokkan menurut operasi dan kode respons.
Latensi: menampilkan latensi respons persentil ke-50 dan ke-95 menurut operasi.
CPU dan memori: menampilkan pemakaian CPU dan memori sebagai persentase dari jumlah yang diminta.
Anda juga dapat melihat dan menjelajahi log untuk workload Anda.
Sebelum dapat menggunakan metrik performa aplikasi, aplikasi Anda harus memiliki cara untuk mengirim metrik ke Cloud Monitoring. Untuk mengetahui informasi tentang
pendekatan yang direkomendasikan, lihat
Mengumpulkan metrik performa aplikasi.
Mengumpulkan metrik performa aplikasi
Anda dapat mengumpulkan metrik performa aplikasi untuk Google Kubernetes Engine menggunakan
integrasi yang didukung berikut:
Cloud Service Mesh: Jika Anda menggunakan Cloud Service Mesh, metrik performa aplikasi akan dikumpulkan secara otomatis.
GKE Ingress: Saat Anda mengonfigurasi
GKE Ingress untuk Load Balancer Aplikasi,
metrik performa akan otomatis dikumpulkan untuk load balancer HTTP/S
yang merutekan traffic ke resource Layanan dan Deployment GKE Anda
di belakang GKE Ingress.
NGINX Ingress: Jika Anda menggunakan
NGINX Ingress, sebaiknya
kumpulkan metrik
menggunakan Google Cloud Managed Service for Prometheus.
Metrik HTTP dan gRPC Prometheus: Jika aplikasi Anda mengekspos metrik HTTP atau gRPC Prometheus, sebaiknya Anda mengikuti dokumen server HTTP dan server gRPC untuk mengumpulkan metrik menggunakan Google Cloud Managed Service for Prometheus.
Melihat metrik performa aplikasi
Setelah data performa tersedia untuk dianalisis, Anda dapat
melihat metrik
untuk Deployment di dasbor aplikasi.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-01 UTC."],[],[],null,["# Use application performance metrics\n\n[Autopilot](/kubernetes-engine/docs/concepts/autopilot-overview) [Standard](/kubernetes-engine/docs/concepts/choose-cluster-mode)\n\n*** ** * ** ***\n\nYou can configure your workloads on Google Kubernetes Engine (GKE) to send\napplication performance metrics to Cloud Monitoring. You can then\nuse these metrics to detect performance regressions in your application.\nGoogle Kubernetes Engine provides visualizations for the following kinds of performance\nmeasures for your workloads:\n\n- Requests: shows the per-second request rate, grouped by operation when available.\n- Errors: shows error rates, grouped by operation and response code.\n- Latency: shows 50th and 95th percentile response latency by operation.\n- CPU and memory: shows the utilization of CPU and memory as a percentage of a requested amount.\n\nThese metrics correspond to the\n[*golden signals*](https://sre.google/sre-book/monitoring-distributed-systems/#xref_monitoring_golden-signals)\nrecommended in the Google\n[*Site Reliability Engineering* book](https://sre.google/sre-book/monitoring-distributed-systems/)\nfor monitoring distributed systems.\n\nYou can also view and explore logs for your workloads.\n\nBefore you can use application performance metrics, your application must have\na way to send the metrics to Cloud Monitoring. For information about\nrecommended approaches, see\n[Collect application performance metrics](#app-perf-ingest).\n\nCollect application performance metrics\n---------------------------------------\n\nYou can collect application performance metrics for Google Kubernetes Engine by using\nthe following supported integrations:\n\n- **Cloud Service Mesh**: If you use Cloud Service Mesh, then application performance metrics are collected automatically.\n- **Istio** : If you use [open source Istio](https://istio.io), then we recommend that you [collect the metrics](/stackdriver/docs/managed-prometheus/exporters/istio) by using Google Cloud Managed Service for Prometheus.\n- **GKE Ingress** : When you configure [GKE Ingress for Application Load Balancers](/kubernetes-engine/docs/concepts/ingress), performance metrics are automatically collected for the HTTP/S load balancers that route traffic to your GKE Service and Deployment resources behind GKE Ingress.\n- **NGINX Ingress** : If you are using [NGINX Ingress](https://kubernetes.github.io/ingress-nginx/), then we recommend that you [collect the metrics](/stackdriver/docs/managed-prometheus/exporters/ingress-nginx) by using Google Cloud Managed Service for Prometheus.\n- **Prometheus HTTP and gRPC metrics** : If your application exposes Prometheus HTTP or gRPC metrics, then we recommend that you follow the [HTTP server](/stackdriver/docs/managed-prometheus/exporters/server/http) and [gRPC server](/stackdriver/docs/managed-prometheus/exporters/server/grpc) documents to collect the metrics by using Google Cloud Managed Service for Prometheus.\n\nView application performance metrics\n------------------------------------\n\nAfter the performance data is available for analysis, you can\n[view the metrics](/kubernetes-engine/docs/how-to/view-observability-metrics#app-perf-view)\nfor a Deployment on the application dashboard."]]
