3V0-24.25 VMware Advanced VMware Cloud Foundation 9.0 vSphere Kubernetes Service Free Practice Exam Questions (2026 Updated)

In Kubernetes, the component that actuallycreates and runs workloads on a nodeis thekubelet. The kubelet is the node agent that ensures the containers described by PodSpecs are running on that node. VCF 9.0 maps this concept directly into vSphere Supervisor by describingSphereletas “a kubelet that is ported natively to ESXi and allows the ESXi host to become part of the Kubernetes cluster,” showing that kubelet functionality is responsible for running workloads on worker nodes (ESXi hosts in the Supervisor case).

The other options have different roles:etcdis the control plane data store,API Serveris the front-end for Kubernetes API operations, and theSchedulerdecides placement (which node should run a pod). VCF 9.0 even calls out that “the Kubernetes scheduler… cannot place pods intelligently” without visibility into vCenter inventory—reinforcing that scheduling is about placement decisions, not the act of creating/running the workload on the node.

So, while the scheduler selects where a pod should run, thekubeletis the component responsible for actually instantiating and maintaining the workload on the target node.

VCF 9.0 explains pod fundamentals by describing how Workload Management introducesvSphere Pods, stating a vSphere Pod is “equivalent of a Kubernetes pod” and that it “runs one or more Linux containers.” This directly eliminates optionB, because a pod can includeone or morecontainers (not only one).

The vSphere 9.0 documentation further defines a KubernetesPodas “a group of one or more containerized applications that share such resources as storage and network,” and notes the containers inside a pod are “started, stopped, and replicated as a group.” That definition reflects Kubernetes’ scheduling and lifecycle model: Kubernetes treats the pod as the primary unit it places and manages together, which is why a pod is regarded as thesmallest deployable unitfor running containerized workloads in Kubernetes. OptionsCandDare incorrect because pods are Kubernetes objects (not “managed by Docker” as a smallest entity), and Kubernetes abstracts the underlying runtime/host so pods are not defined as being “deployed directly on the virtual machine” as a characteristic.

VKS cluster lifecycle is managed using adeclarative API: you usekubectl with a YAML fileto specify the desired state of the cluster (for example: “how many nodes,” Kubernetes version, sizing, and storage). After the cluster is created, youupdate the YAMLto update the cluster. This is why the correct operational approach is to modify the cluster manifest (cluster.yaml) rather than deleting and redeploying.

Additionally, VKS uses multiple controller layers, whereCluster APIand theVirtual Machine Serviceare responsible for provisioning and managing the lifecycle of the control plane and worker node VMs that make up the VKS cluster. In other words, when you change the declared state for control plane sizing/replica count in the cluster YAML, the platform reconciles to that new state by adjusting the underlying control plane VMs through the supported controllers, instead of requiring disruptive “tear down and rebuild” operations.

So, editing the cluster.yaml to adjust the control plane replica count is the method that matches the documented VKS declarative operations model and controller-driven reconciliation.

Answer (Correct Order):

Navigate in VCF Operations to Fleet Management → Tasks, select the instance and review Tasks

Check for errors or failed ClusterConfig objects

SSH into the Supervisor Cluster to review logs / attempt manual cleanup if required

Restart the WCP Service

To determinewhya Supervisor upgrade failed, you start where the platform records the most actionable failure context: themanagement-plane task history. The Fleet/Task view surfaces the upgrade workflow steps, timestamps, and the specific operation that failed, which gives you the fastest pointer to the failing phase (precheck, image staging, reconciliation, add-on updates, etc.). Next, you validate the Kubernetes-side reconciliation state by checking forfailed ClusterConfigobjects, because Supervisor enablement/upgrade actions commonly drive configuration via controller reconciliation; a failed ClusterConfig often contains the clearest “reason” and “message” fields that explain what blocked progress (validation errors, dependency issues, unreachable endpoints, incompatible components).

If the management-plane/task view and ClusterConfig status still don’t isolate the root cause, the next escalation is toSSH into the Supervisorto inspect component logs/events and identify low-level failures that may not bubble up cleanly (for example, admission failures, controller crashes, or connectivity/auth issues). Finally,restarting WCPis a remediation step that can clear stuck states, but it’s placed last because it can alter evidence and should not be your first action when you’re still trying to identify the original failure cause.

Configuration Order (in order):

Verify the name of the original VolumeSnapshot object in the Supervisor.

Create a VolumeSnapshotContent object.

Create a VolumeSnapshot object.

Verify that the VolumeSnapshot is marked with ReadyToUse as true.

Apre-provisioned snapshotworkflow means the snapshot already exists at the Supervisor/storage layer, and you are “importing” it into Kubernetes by creating the Kubernetes objects that reference it. That’s why the first step is toidentify/verify the exact snapshot nameas it exists in the Supervisor context—this is the authoritative identifier you must point to when you create Kubernetes snapshot metadata. Next, you create theVolumeSnapshotContentobject, which represents theactual snapshot on the storage backendand includes the handle/reference to that pre-existing snapshot. With the content object in place, you then create theVolumeSnapshotobject, which is theuser-facing Kubernetes object(namespaced) that binds to the pre-provisioned VolumeSnapshotContent (either explicitly or via binding rules). Finally, you validate the outcome by checking that theVolumeSnapshot shows ReadyToUse: true, confirming the binding succeeded and Kubernetes can use the snapshot for restore/clone workflows.

Kubernetes Role-Based Access Control (RBAC) is implemented through theRBAC API group(rbac.authorization.k8s.io) and defines the core authorization primitives used to grant permissions to users, groups, and service accounts. The cluster-scoped objects declared by the RBAC API areClusterRoleandClusterRoleBinding. AClusterRoledefines a set of permissions (verbs such as get/list/watch/create/update/delete) over resources at thecluster scope(including cluster-wide resources and optionally namespaced resources across namespaces). AClusterRoleBindingthenbindsthat ClusterRole to a subject (user/group/serviceaccount), making those permissions effective cluster-wide.

This differs from namespace-scoped RBAC objects (RoleandRoleBinding) which apply only within a single namespace. The other options are incorrect becauseClusterObject/ClusterNodeare not RBAC API objects,ValidatingAdmissionPolicybelongs to the admission control API surface (policy enforcement),ResourceQuotais a namespace resource governance object, andContainer/Deploymentare workload/runtime concepts defined in the core/apps APIs rather than authorization primitives.

The documented behavior of kubectl edit is that it opens the object manifest in a local text editor, and the editor it launches is controlled by environment variables. In the VCF 9.0 documentation (Workload Management / Supervisor operations), the procedure explicitly states: “The kubectl edit command opens the namespace manifest in the text editor defined by your KUBE_EDITOR or the EDITOR environment variable.”

If the administrator’s environment does not have KUBE_EDITOR or EDITOR defined (or they point to an invalid/interactive-less editor in the current session), kubectl edit may not open the expected editor workflow, and the admin may not see the normal confirmation after saving and exiting. Setting KUBE_EDITOR (preferred for kubectl-specific behavior) or EDITOR ensures kubectl launches a known-good editor, allowing the manifest to be modified, saved, and then submitted back to the API server when the editor exits. The same documented requirement also applies to editing other Kubernetes objects (such as a VKS cluster manifest) because the kubectl edit mechanism is identical.

In Kubernetes RBAC, cluster-wide permissions are defined withClusterRoleand granted to a user, group, or service account by creating aClusterRoleBinding. The VCF 9.0 documentation for VKS cluster access describes the RBAC workflow used to grant access: first you “define a Role or ClusterRolefor the user or group,” and then you “create a RoleBinding or ClusterRoleBindingfor the user or group and apply it to the cluster.” This wording reflects the RBAC distinction:RoleBindingis scoped to a namespace, whereasClusterRoleBindingis used when the permissions must apply at thecluster scope(cluster-wide resources and/or across namespaces).

VCF 9.0 further illustrates the purpose of ClusterRoleBinding in a token-auth example: it lists the required objects, including “ClusterRole: This defines the access to the Kubernetes cluster” and “ClusterRoleBinding: This binds the created Service Account with the defined ClusterRole.” That binding step is what grants the subject the cluster-level privileges defined in the ClusterRole, makingClusterRoleBindingthe correct object for permissions to cluster-wide resources.

VCF 9.0 describes Supervisor networking with NSX as a model whereNSX provides network connectivity to Supervisor control plane VMs, services, and workloads, and where the Supervisor can use either the NSX Load Balancer or the Avi Load Balancer. In the NSX + Avi design, the documentation identifies theAvi Load Balancer Controlleras a core infrastructure element: the Controller “interacts with vCenter to automate the load balancing for the VKS clusters,” and is responsible for provisioning and coordinating Service Engines and exposing operational interfaces.

Also, the Supervisor itself is anchored by theSupervisor control plane virtual machines. VCF 9.0 explains you deploy the Supervisor with one or three control plane VMs, and in a three-zone Supervisor the control plane VMs are distributed across zones for high availability.

Finally, because the requirement explicitly calls for a unified networking/security model throughNSX, theNSX Manager virtual machineis foundational to the NSX-based Supervisor design, as shown in the documented architecture and component descriptions for NSX-backed Supervisor deployments.

VCF 9.0 positions VKS clusters as Kubernetes-native environments where platform teams install and manage “standard packages” and add-ons. In VCF Automation’s VKS overview, VMware states that a set of packages is automatically included with a VKS cluster, includingkapp-controllerandsecret-gen controller. These components are part of theCarveltoolchain used for packaging and deploying applications/configuration in a Kubernetes-friendly, declarative way.

In addition, the VCF 9.0 CLI “package” workflows explicitly supportytt overlaysduring package installation/updates (for example, --ytt-overlay-file and --ytt-overlays), which are configuration mechanisms associated with Carvel-based packaging workflows.

Helmis the other widely used Kubernetes package manager for installing and configuring applications through charts and values, and is commonly used by DevOps teams on Kubernetes clusters such as VKS for app deployment and configuration management. By contrast, Fluent Bit is a log shipper, Multus is a CNI multiplexer, and Grafana is a visualization tool—none are package management tools.

VCF 9.0 documentation emphasizes that administrators commonly work withmultiple Kubernetes contexts(Supervisor context, namespace contexts, and workload-cluster contexts), and mustswitch to the correct contextbefore running kubectl commands against a specific target. It explains that when you connect, the CLI generates and appends contexts into the kubeconfig, and you thenswitch between contextsusing the context-management commands (for example, listing contexts and using a specific context).

It further describes the correct pattern for interacting with a VKS workload cluster: obtain or generate theworkload-cluster kubeconfig/context, then run kubectl (such as kubectl get nodes) against that workload cluster context.

In this scenario, the errors appear while attempting cluster operations after a Supervisor update, which strongly indicates kubectl is not pointed at the intended endpoint/context (for example, still using a Supervisor/namespace context or an incorrect kubeconfig entry). Because VCF explicitly calls out context creation andcontext switchingas required steps to target the correct cluster, the most verified cause among the options isbeing in the wrong cluster context.

In VMware Cloud Foundation 9.0 and vSphere Supervisor architectures, the decision to deploy aSingle-Zoneor aMulti-ZoneSupervisor is made at the time ofinitial enablement. A Single-Zone Supervisor is tied to a specific vSphere Cluster. A Multi-Zone Supervisor requires a minimum of three vSphere Zones (each mapped to a cluster) to be defined before the Supervisor is deployed so that the Control Plane VMs can be distributed for high availability.

Currently, there is no supported "in-place" migration path to convert a deployed Single-Zone Supervisor into a Multi-Zone Supervisor by simply adding zones later. If an organization requires the high availability provided by a three-zone architecture, the administrator must decommission the existing Single-Zone Supervisor and then re-enable the Supervisor Service using the Multi-Zone configuration wizard. This design ensures that the underlying Kubernetes Control Plane components are correctly instantiated with the necessary quorum and anti-affinity rules that can only be established during the initial "Workload Management" setup phase.

Amulti-zone Supervisorin VCF 9.0 is designed to deliverplatform resiliency and high availability at the vSphere cluster (zone) failure-domain level. The VCF 9.0 documentation states that a multi-zone Supervisor “leverages three vSphere clusters” (each mapped to a vSphere Zone) and that these zones are used by both “workloads and Supervisor management components to deliver high availability,” exposing “each cluster as an independent, consumable availability zone,” resulting in a “resilient, HA-capable platform.”

This is reinforced in the vSphere Zones guidance: deploying the Supervisor onthree vSphere Zones spreads the control plane VMs across three zones, providing “cluster-level high availability” that protects the Supervisor control plane against asingle cluster-level failure(one control plane VM per management zone).

Because VKS (vSphere Kubernetes Service) runs on Supervisor, distributing Supervisor control plane and workload placement across zones improves overall availability of Supervisor services and Kubernetes consumption in that Supervisor instance.

VCF 9.0 describes backing up workloads on VKS clusters usingVelero(Velero Plugin for vSphere) and shows the backup command pattern scoping backup content bynamespace(for example, velero backup create ... --include-namespaces=my-namespace). This demonstrates thatNamespacesare a primary object type within backup scope (you choose which namespace content is captured). The same section explains that after backup execution,Kubernetes metadata is uploaded to the object store. “Kubernetes metadata” in this context includes standard namespaced resources that represent running workloads and how they are exposed, such asServices(a core Kubernetes API object used to provide stable access to pods).

In addition to namespace scoping, Velero’s selection model commonly includes filtering backed-up Kubernetes objects using selectors (for example, selecting subsets of resources), which aligns with the “objects identified by a label selector” option as an object-selection mechanism within the scope of what Velero captures from Kubernetes APIs (metadata/resources) once the namespace is targeted.

Therefore, the best match to the documented Velero workload-backup model is:Namespace,Service, andlabel-selected objectswithin the included namespace(s).

VCF 9.0 explicitly lists thecomponents that run in a VKS clusterand groups them into areas such as authentication/authorization, storage integration, pod networking, and load balancing. In that list, the documentation names:“Container Storage Interface Plugin”(a paravirtual CSI plug-in that integrates with CNS through the Supervisor),“Container Network Interface Plug-in”(a CNI plugin that provides pod networking), and“Cloud Provider Implementation”(supports creating Kubernetes load balancer services).

These three items map directly to the answer choicesD (Container Storage Interface),F (Container Network Interface), andA (Cloud Provider Implementation). The same VCF 9.0 section also mentions an authentication webhook, but that component is not offered as a selectable option in this question, so the best three matches among the provided choices are the CSI, CNI, and cloud provider implementation entries that the document explicitly states are present inside a VKS cluster.

VCF 9.0 describes VKS as providing self-service, declarative lifecycle management for Kubernetes clusters and explicitly identifiesCluster APIas the mechanism that enables Kubernetes-style lifecycle automation. The documentation states that “The Cluster API provides declarative, Kubernetes-style APIs for cluster creation, configuration, and management,” and that its inputs include resources describing “the virtual machines that make up the cluster” plus “cluster add-ons.” This directly maps to automated lifecycle management: a desired-state YAML is reconciled by controllers that create, update, and maintain the control plane and worker node resources without manual, imperative procedures.

The same VCF 9.0 content also notes VKS exposes “three layers of controllers” for lifecycle management and lists Cluster API as one of those layers, reinforcing that Cluster API is foundational for ongoing cluster operations (create, scale, upgrade, reconcile). Contour is an ingress controller (traffic routing), kubeadm is a Kubernetes bootstrap tool (not the VKS lifecycle controller framework), and Grafana is observability/visualization (not cluster lifecycle).

VCF 9.0 documents that you obtain access to the Supervisor (and the contexts you’re entitled to, which commonly correspond to namespaces and workload clusters) by authenticating withkubectl vsphere login. The procedure “Get and Use the Supervisor Context” explains that after you log in, a Kubernetes configuration context is generated and you can view it in$HOME/.kube/config, which is “commonly called the kubeconfig file.”

The documentation is explicit that running kubectl vsphere login --server= --vsphere-username “creates a configuration file with the JSON Web Token (JWT) to authenticate to the Kubernetes API,” and then lists how to view and switch contexts using kubectl config get-contexts and kubectl config use-context.

This matches optionDprecisely: you don’t “download” kubeconfig from VCF Operations or a Supervisor Services page; instead, you generate/update your kubeconfig locally by logging in withkubectl’s vSphere plugin, which writes the required cluster/user/context details into .kube/config.