Mantieni tutto organizzato con le raccolte
Salva e classifica i contenuti in base alle tue preferenze.
Autopilot
Standard
Questa pagina spiega come eseguire i workload Arm su Google Kubernetes Engine (GKE).
Panoramica
Puoi eseguire i carichi di lavoro Arm nei cluster GKE Autopilot
utilizzando le Performance o Scale-Outclassi di
calcolo,
oppure nei cluster GKE Standard
utilizzando la serie di macchine C4A
(C4A) o la serie di macchine Tau T2A (T2A). Puoi eseguire
immagini Arm a singola architettura o immagini multi-architettura (multi-arch)
compatibili con processori x86 e Arm. Per scoprire i vantaggi di Arm,
consulta VM Arm su Compute.
Per ulteriori informazioni sulla scelta dei workload da eseguire il deployment su Arm e sulla preparazione di questi workload per il deployment, consulta le seguenti guide:
Scelta dei carichi di lavoro da eseguire su Arm: i nodi C4A forniscono risorse di calcolo basate su Arm
che garantiscono prestazioni elevate e uniformi per i carichi di lavoro basati su Arm
più sensibili alle prestazioni. I nodi T2A sono adatti a carichi di lavoro più flessibili o che si basano sullo scale out orizzontale. Per
scoprire di più sui tipi di workload adatti a ciascuna di queste
serie di macchine, consulta la tabella nella famiglia di macchine per uso generico per
Compute Engine.
Deployment su più architetture: con GKE, puoi utilizzare
immagini multi-architettura per eseguire il deployment di un manifest di immagine su nodi con architetture diverse, inclusa Arm.
Preparazione dei workload Arm per il deployment: una volta che hai un'immagine compatibile con Arm, utilizza le regole di affinità dei nodi e i selettori dei nodi per assicurarti che il workload sia pianificato per i nodi con un tipo di architettura compatibile.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 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)"]]