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Halaman ini menjelaskan cara menjalankan workload Arm di Google Kubernetes Engine (GKE).
Ringkasan
Anda dapat menjalankan workload Arm di cluster GKE Autopilot menggunakan class
komputasiPerformance atau Scale-Out,
atau di cluster GKE Standard menggunakan seri mesin C4A
(C4A) atau seri mesin Tau T2A (T2A). Anda dapat menjalankan
image Arm satu arsitektur atau image multi-arsitektur (multi-arch)
yang kompatibel dengan prosesor x86 dan Arm. Untuk mempelajari manfaat Arm, lihat VM Arm di Compute.
Lihat panduan berikut untuk informasi selengkapnya tentang memilih workload yang akan di-deploy di Arm dan menyiapkan workload tersebut untuk deployment:
Memilih workload yang akan dijalankan di Arm: Node C4A menyediakan komputasi berbasis Arm yang secara konsisten mencapai performa tinggi untuk workload berbasis Arm yang paling sensitif terhadap performa. Node T2A cocok untuk
workload yang lebih fleksibel, atau workload yang mengandalkan penskalaan horizontal. Untuk
mempelajari lebih lanjut jenis workload yang berfungsi baik dengan setiap seri
mesin ini, lihat tabel di Kelompok mesin tujuan umum untuk
Compute Engine.
Men-deploy di berbagai arsitektur: Dengan GKE, Anda dapat menggunakan
image multi-arch untuk men-deploy satu manifes image di seluruh node dengan arsitektur yang berbeda, termasuk Arm.
Menyiapkan workload Arm untuk deployment: Setelah Anda memiliki image yang kompatibel dengan Arm, gunakan aturan afinitas
node dan
pemilih node
untuk memastikan workload Anda dijadwalkan ke node dengan jenis arsitektur yang kompatibel.
[[["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,["# Arm workloads on GKE\n\nAutopilot Standard\n\n*** ** * ** ***\n\nThis page explains how you can run Arm workloads on Google Kubernetes Engine (GKE).\n\nOverview\n--------\n\nYou can run Arm workloads in GKE Autopilot clusters\nusing the `Performance` or `Scale-Out` [compute\nclasses](/kubernetes-engine/docs/concepts/autopilot-compute-classes#when-to-use),\nor in GKE Standard\nclusters using the [C4A machine series\n(C4A)](/compute/docs/general-purpose-machines#c4a_series) or [Tau T2A machine\nseries (T2A)](/compute/docs/general-purpose-machines#t2a_machines). You can run\nsingle-architecture Arm images or multi-architecture (multi-arch) images\ncompatible with both x86 and Arm processors. To learn about the benefits of Arm,\nsee [Arm VMs on Compute](/compute/docs/instances/arm-on-compute).\n\nSee the following guides for more information about choosing workloads to deploy on Arm and preparing those\nworkloads for deployment:\n\n- **Choosing workloads to run on Arm** : C4A nodes provide Arm-based compute which achieves consistently high performance for your most performance-sensitive Arm-based workloads. T2A nodes are appropriate for more-flexible workloads, or workloads which rely on horizontal scale-out. To learn more about what types of workloads work well with each of these machine series, see the table in [General-purpose machine family for\n Compute Engine](/compute/docs/general-purpose-machines).\n- **Deploying across architectures** : With GKE, you can use multi-arch images to deploy one image manifest across nodes with different architectures, including Arm.\n - To ensure that your container image is Arm-compatible and can run on your targeted architectures, see [Build multi-architecture images for\n Arm workloads](/kubernetes-engine/docs/how-to/build-multi-arch-for-arm).\n - To follow a tutorial for using multi-arch images to deploy across architectures, see [Migrate x86 application on GKE to\n multi-arch with\n Arm](/kubernetes-engine/docs/tutorials/migrate-x86-to-multi-arch-arm).\n- **Preparing Arm workloads for deployment** : Once you have an Arm-compatible image, use [node\n affinity](https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#node-affinity) rules and [node selectors](https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#nodeselector) to make sure your workload is scheduled to nodes with a compatible architecture type.\n - **Autopilot clusters** : see [Deploy Autopilot\n workloads on Arm\n architecture](/kubernetes-engine/docs/how-to/autopilot-arm-workloads).\n - **Standard clusters** : see [Prepare an Arm workload for\n deployment](/kubernetes-engine/docs/how-to/prepare-arm-workloads-for-deployment).\n\nRequirements and limitations\n----------------------------\n\n- To create a cluster with C4A nodes that uses [Autopilot](/kubernetes-engine/docs/concepts/autopilot-overview)\n mode, [cluster\n autoscaling](/kubernetes-engine/docs/concepts/cluster-autoscaler),\n or [node\n auto-provisioning](/kubernetes-engine/docs/how-to/node-auto-provisioning),\n you must use the following versions or later:\n\n - 1.28.15-gke.1344000\n - 1.29.11-gke.1012000\n - 1.30.7-gke.1136000\n - 1.31.3-gke.1056000\n- To create a Standard cluster with C4A nodes, you must use one of the\n following versions or later:\n\n - 1.28.13-gke.1024000\n - 1.29.8-gke.1057000\n - 1.30.4-gke.1213000\n- Arm nodes are available in Google Cloud locations that support Arm\n architecture. For details, see [Available regions and\n zones](/compute/docs/regions-zones#available).\n\n- You can use [Local\n SSDs](/kubernetes-engine/docs/how-to/persistent-volumes/local-ssd) with C4A\n nodes with the following versions or later:\n\n - 1.29.15-gke.1325000\n - 1.30.12-gke.1033000\n - 1.31.8-gke.1045000\n - 1.32.1-gke.1357000\n- GKE doesn't support the following features with C4A nodes:\n\n - [Confidential GKE Nodes](/kubernetes-engine/docs/how-to/confidential-gke-nodes)\n - [Compact placement](/kubernetes-engine/docs/how-to/compact-placement)\n - [Simultaneous multi-threading (SMT)](/kubernetes-engine/docs/how-to/configure-smt)\n - [Persistent disks](/kubernetes-engine/docs/concepts/persistent-volumes) (use [Hyperdisk](/kubernetes-engine/docs/concepts/hyperdisk) instead, see [Supported disk types for\n C4A](/compute/docs/general-purpose-machines#supported_disk_types_for_c4a))\n - [Nested virtualization](/kubernetes-engine/docs/how-to/nested-virtualization)\n - [GPUs](/kubernetes-engine/docs/concepts/gpus)\n- GKE doesn't support the following features with T2A\n nodes:\n\n - [Confidential GKE Nodes](/kubernetes-engine/docs/how-to/confidential-gke-nodes)\n - [GPUs](/kubernetes-engine/docs/concepts/gpus)\n - [GKE Windows](/kubernetes-engine/docs/concepts/windows-server-gke)\n - [Local SSDs](/kubernetes-engine/docs/how-to/persistent-volumes/local-ssd)\n - [Policy Controller](/anthos-config-management/docs/concepts/policy-controller), [Config Sync](/anthos-config-management/docs/config-sync-overview), and [Config Controller](/anthos-config-management/docs/concepts/config-controller-overview)\n\nWhat's next\n-----------\n\n- [Create clusters and node pools with Arm nodes](/kubernetes-engine/docs/how-to/create-arm-clusters-nodes)\n- [Build multi-architecture images for Arm workloads](/kubernetes-engine/docs/how-to/build-multi-arch-for-arm)\n- [Prepare an Arm workload for deployment](/kubernetes-engine/docs/how-to/prepare-arm-workloads-for-deployment)\n- [Migrate x86 application on GKE to multi-arch with Arm](/kubernetes-engine/docs/tutorials/migrate-x86-to-multi-arch-arm)"]]
