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Questa pagina spiega come creare e gestire carichi di lavoro stateless all'interno di un cluster Kubernetes air-gap di Google Distributed Cloud (GDC). I carichi di lavoro stateless ti consentono di scalare il deployment dell'applicazione in base alle esigenze del carico di lavoro, il tutto senza dover gestire l'archiviazione permanente in un cluster Kubernetes per archiviare dati o stato dell'applicazione. Questa pagina ti aiuta a iniziare a ottimizzare e regolare in modo efficiente la disponibilità della tua applicazione.
Questa pagina è rivolta agli sviluppatori del gruppo di operatori di applicazioni, che sono
responsabili della creazione dei carichi di lavoro delle applicazioni per la propria organizzazione. Per saperne di più, consulta la documentazione sulle audience per GDC air-gapped.
Prima di iniziare
Per eseguire comandi su un
cluster Kubernetes,
assicurati di disporre delle seguenti risorse:
Individua il nome del cluster Kubernetes o chiedi all'amministratore della piattaforma qual è il nome del cluster.
Accedi e genera
il file kubeconfig per il cluster Kubernetes se non ne hai uno.
Utilizza il percorso kubeconfig del cluster Kubernetes per sostituire
KUBERNETES_CLUSTER_KUBECONFIG in queste istruzioni.
Per ottenere le autorizzazioni necessarie per creare carichi di lavoro stateless, chiedi all'amministratore IAM dell'organizzazione di concederti il ruolo Amministratore spazio dei nomi (namespace-admin) nello spazio dei nomi del progetto.
Crea un deployment
Per creare un deployment, scrivi un manifest Deployment ed esegui
kubectl apply per creare la risorsa. Questo metodo conserva anche gli aggiornamenti apportati
alle risorse live senza unire le modifiche ai file manifest.
Per creare un Deployment dal relativo file manifest, esegui:
kubectl--kubeconfigKUBERNETES_CLUSTER_KUBECONFIG-nNAMESPACE\apply-f-<<EOF
apiVersion:apps/v1
kind:Deployment
metadata:
name:DEPLOYMENT_NAME
spec:
replicas:NUMBER_OF_REPLICASselector:
matchLabels:
run:APP_NAMEtemplate:
metadata:
labels:# The labels given to each pod in the deployment, which are used# to manage all pods in the deployment.run:APP_NAMEspec:# The pod specification, which defines how each pod runs in the deployment.containers:
-name:CONTAINER_NAMEimage:CONTAINER_IMAGE
EOF
Sostituisci quanto segue:
KUBERNETES_CLUSTER_KUBECONFIG: il file kubeconfig per il
cluster Kubernetes in cui stai eseguendo il deployment dei carichi di lavoro dei container.
NAMESPACE: lo spazio dei nomi del progetto in cui eseguire il deployment dei carichi di lavoro dei container.
DEPLOYMENT_NAME: il file kubeconfig per il cluster in cui esegui il deployment dei carichi di lavoro dei container.
APP_NAME: il nome dell'applicazione da eseguire all'interno
del deployment.
NUMBER_OF_REPLICAS: il numero di oggetti Pod replicati gestiti dal deployment.
CONTAINER_NAME: il nome del container.
CONTAINER_IMAGE: il nome dell'immagine container. Devi includere il percorso del registro dei container e la versione dell'immagine, ad esempio REGISTRY_PATH/hello-app:1.0.
[[["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 2025-09-04 UTC."],[[["\u003cp\u003eStateless applications store data with the client, allowing for increased scalability and availability through the use of multiple replicas without needing unique identities.\u003c/p\u003e\n"],["\u003cp\u003eBefore deploying stateless workloads, you need to identify your Kubernetes cluster name, sign in and generate the kubeconfig file, and obtain the Namespace Admin role (\u003ccode\u003enamespace-admin\u003c/code\u003e) from your Organization IAM Admin.\u003c/p\u003e\n"],["\u003cp\u003eDeployments are created by writing a \u003ccode\u003eDeployment\u003c/code\u003e manifest and using \u003ccode\u003ekubectl apply\u003c/code\u003e, which retains updates made to live resources.\u003c/p\u003e\n"],["\u003cp\u003eWhen creating a \u003ccode\u003eDeployment\u003c/code\u003e, you must specify details such as the deployment name, number of replicas, application name, container name, and container image, along with the appropriate kubeconfig file and namespace.\u003c/p\u003e\n"],["\u003cp\u003eYou can use \u003ccode\u003ekubectl apply -f\u003c/code\u003e with either a manifest file or a directory of manifest files to create new resources within your cluster.\u003c/p\u003e\n"]]],[],null,["# Create stateless workloads\n\nThis page explains how to create and manage stateless workloads within a\nGoogle Distributed Cloud (GDC) air-gapped Kubernetes cluster. Stateless workloads let you\nscale your application deployment based on workload demands, all\nwithout having to manage persistent storage in a Kubernetes cluster to store\ndata or application state. This page helps you get started so you can\nefficiently optimize and adjust your application's availability.\n\nThis page is for developers within the application operator group, who are\nresponsible for creating application workloads for their organization. For more\ninformation, see\n[Audiences for GDC air-gapped documentation](/distributed-cloud/hosted/docs/latest/gdch/resources/audiences).\n\nBefore you begin\n----------------\n\nTo run commands against a\n[Kubernetes cluster](/distributed-cloud/hosted/docs/latest/gdch/platform/pa-user/clusters#cluster-architecture),\nmake sure you have the following resources:\n\n1. Locate the Kubernetes cluster name, or ask your Platform Administrator what\n the cluster name is.\n\n2. [Sign in and generate](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/iam/sign-in#zonal-cluster-kubeconfig)\n the kubeconfig file for the Kubernetes cluster if you don't have one.\n\n3. Use the kubeconfig path of the Kubernetes cluster to replace\n \u003cvar translate=\"no\"\u003eKUBERNETES_CLUSTER_KUBECONFIG\u003c/var\u003e in these instructions.\n\nTo get the required permissions to create stateless workloads, ask your\nOrganization IAM Admin to grant you the Namespace Admin role (`namespace-admin`)\nin your project namespace.\n\nCreate a deployment\n-------------------\n\nYou create a deployment by writing a `Deployment` manifest and running\n`kubectl apply` to create the resource. This method also retains updates made to\nlive resources without merging the changes back into the manifest files.\n\nTo create a `Deployment` from its manifest file, run: \n\n kubectl --kubeconfig \u003cvar translate=\"no\"\u003eKUBERNETES_CLUSTER_KUBECONFIG\u003c/var\u003e -n \u003cvar translate=\"no\"\u003eNAMESPACE\u003c/var\u003e \\\n apply -f - \u003c\u003cEOF\n apiVersion: apps/v1\n kind: Deployment\n metadata:\n name: \u003cvar translate=\"no\"\u003eDEPLOYMENT_NAME\u003c/var\u003e\n spec:\n replicas: \u003cvar translate=\"no\"\u003eNUMBER_OF_REPLICAS\u003c/var\u003e\n selector:\n matchLabels:\n run: \u003cvar translate=\"no\"\u003eAPP_NAME\u003c/var\u003e\n template:\n metadata:\n labels: # The labels given to each pod in the deployment, which are used\n # to manage all pods in the deployment.\n run: \u003cvar translate=\"no\"\u003eAPP_NAME\u003c/var\u003e\n spec: # The pod specification, which defines how each pod runs in the deployment.\n containers:\n - name: \u003cvar translate=\"no\"\u003eCONTAINER_NAME\u003c/var\u003e\n image: \u003cvar translate=\"no\"\u003eCONTAINER_IMAGE\u003c/var\u003e\n EOF\n\nReplace the following:\n\n- \u003cvar translate=\"no\"\u003eKUBERNETES_CLUSTER_KUBECONFIG\u003c/var\u003e: the kubeconfig file for the\n Kubernetes cluster to which you're deploying container workloads.\n\n- \u003cvar translate=\"no\"\u003eNAMESPACE\u003c/var\u003e: the project namespace in which to deploy the container workloads.\n\n- \u003cvar translate=\"no\"\u003eDEPLOYMENT_NAME\u003c/var\u003e: the kubeconfig file for the\n cluster to which you're deploying container workloads.\n\n- \u003cvar translate=\"no\"\u003eAPP_NAME\u003c/var\u003e: the name of the application to run within\n the deployment.\n\n- \u003cvar translate=\"no\"\u003eNUMBER_OF_REPLICAS\u003c/var\u003e: the number of replicated `Pod`\n objects that the deployment manages.\n\n- \u003cvar translate=\"no\"\u003eCONTAINER_NAME\u003c/var\u003e: the name of the container.\n\n- \u003cvar translate=\"no\"\u003eCONTAINER_IMAGE\u003c/var\u003e: the name of the container image. You\n must include the container registry path and version of the image, such as\n \u003cvar class=\"readonly\" translate=\"no\"\u003eREGISTRY_PATH\u003c/var\u003e`/hello-app:1.0`.\n\n| **Note:** You can also use `kubectl apply -f `\u003cvar translate=\"no\"\u003eDIRECTORY\u003c/var\u003e to create new objects defined by manifest files stored in a directory.\n\nFor example: \n\n apiVersion: apps/v1\n kind: Deployment\n metadata:\n name: my-app\n spec:\n replicas: 3\n selector:\n matchLabels:\n run: my-app\n template:\n metadata:\n labels:\n run: my-app\n spec:\n containers:\n - name: hello-app\n image: \u003cvar class=\"readonly\" translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-l devsite-syntax-l-Scalar devsite-syntax-l-Scalar-Plain\"\u003eREGISTRY_PATH\u003c/span\u003e\u003c/var\u003e/hello-app:1.0\n\nIf you're deploying GPU workloads to your containers, see\n[Manage GPU container workloads](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/containers/deploy-gpu-container-workloads)\nfor more information."]]