3V0-24.25 Advanced VMware Cloud Foundation 9.0 vSphere Kubernetes Service Questions and Answers

A Supervisor upgrade impacts the lifecycle and compatibility of Supervisor Services (including Core Supervisor Services). VMware guidance emphasizes validating compatibility for the components that depend on the Supervisor and remediating any incompatibilities as part of the overall upgrade process. If a Core Supervisor Service remains stuck in“Configuring”after the Supervisor is upgraded, a common and expected cause is that the service version isnot compatiblewith the upgraded Supervisor/vCenter software state. In those cases, the upgrade workflow expects you toidentify and update incompatible Supervisor Servicesto versions that match the new supported software level. Ensuring the vSphere Kubernetes Service is at asupportedversion (for the upgraded Supervisor) aligns with the documented approach: run compatibility checks and thenupdate the versions of incompatible Supervisor Servicesso they can complete reconciliation and reach a healthy state.

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.

Answer (Correct Order):

Select the target cluster in the workload domain.

Open Workload Management and select “Enable Supervisor Cluster”.

Choose cluster networking mode and stack.

Configure the control plane compute, networking, and storage policies.

Configure the workload network configurations.

Review, Validate, and Deploy Supervisor.

You start by selecting theexact vSphere cluster(in the workload domain) that will host the Supervisor, because Supervisor enablement is performedagainst a specific cluster. From there you launch the enablement workflow inWorkload Management(“Enable Supervisor Cluster”). Early in the wizard you must decide thenetworking mode(for example, VDS-based vs NSX-backed) and theIP stack, because those choices drive the remaining configuration screens and what inputs are required. Next you define theSupervisor control plane settings—compute sizing and the core policies the Supervisor will use (including storage policy selections and related defaults). After the control plane foundation is defined, you configure theworkload networkingused by namespaces and Kubernetes workloads (IP ranges, routing/LB integration depending on the selected mode). Finally, youreview/validateall inputs anddeployso the platform can create and configure the Supervisor control plane and supporting components.

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.

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.

When you build Kubernetes-aware policy constructs, “groups” are commonly used to collect objects so you can apply consistent controls (security posture, traffic rules, observability scope, etc.) to a set of endpoints. In VCF 9.0 documentation, the Kubernetes member types that can be used for group-based collection includeKubernetes NodeandKubernetes Serviceas supported member object categories. Nodes represent the worker compute endpoints that run workloads, while Services represent stable networking front-ends for sets of pods (and are often the anchoring object for policy and routing decisions at the Kubernetes layer). Using Node-based grouping helps apply policies to the infrastructure execution points where workloads run, and Service-based grouping helps apply policies consistently to application entry points and east-west communication targets, regardless of pod churn. This combination is especially useful in Kubernetes-centric operational models because it aligns policy scope with both (1) where workloads execute (nodes) and (2) how workloads are exposed and discovered (services).

In VCF 9.0, ingress is described as part ofVKS cluster networking. The documentation’s VKS Cluster Networking table lists“Cluster ingress”and identifies its role asrouting inbound pod traffic. It further clarifies that this function is delivered by athird-party ingress controller, and explicitly namesContouras an example (“you can use any third-party ingress controller, such as Contour”).

That mapping is exactly what optionAdescribes: Contour is deployed to provideingresscapabilities so that inbound requests from outside the cluster can be routed to Kubernetes services and pods according to ingress rules. In other words, Contour is not a storage component (that would align to CSI/CNS/pvCSI), not a node lifecycle manager (that is handled by VKS/Cluster API/VM Service), and not an infrastructure health monitoring tool (that would be metrics/observability tooling). VCF 9.0 positions Contour specifically within theingresspart of the networking feature set, makingAthe correct answer.

VCF 9.0 documentation explicitly indicates thatvCenter upgrades and the Supervisor/cluster (Workload Management) upgrade are distinct, noting that “if you have only upgraded vCenter and not the cluster” then DevOps engineers have reduced permissions until the cluster is upgraded. This supports the stated standard that VKS/Workload Management lifecycle can be treated separately from vCenter. For the private registry requirement, VCF 9.0 provides an operational mechanism to authenticate and pull artifacts from private registries: “Registry secrets allow package and repository consumers to authenticate to and pull images from private registries,” implemented via a standard Kubernetes Secret of type kubernetes.io/dockerconfigjson.

Taken together, the standard implies (1)asynchronoushandling (separate lifecycle from vCenter) and (2)privatesourcing (images pulled from an internal registry with registry secrets). Therefore, selectingAsynchronous Privatebest matches both requirements in a single configuration choice, aligning with the documented separation of upgrades and the documented need to use authenticated access to private registries.

Istio is available in VCF 9.0 as an optional package that can be installed for VKS clusters. The VCF 9.0 documentation explicitly lists “Istio” among the optional packages that “can be optionally installed” for the vSphere Kubernetes Service (VKS). In Kubernetes platforms, Istio is a service mesh that secures and manages service-to-service (east-west) traffic by establishing authenticated and encrypted connections between workloads. The encryption mechanism it provides for inter-service communication ismutual TLS (mTLS), which means both ends (client and server workloads) authenticate each other and negotiate encrypted transport for every service call—meeting the requirement to “encrypt the transport and communications between services.” This is distinct from host-level mechanisms like IPsec/IKEv2 (network-layer) or “AES-256” (an algorithm, not the service-to-service transport model). Enabling Istio Service Mesh is therefore aligned to deliver encrypted, identity-aware service communications across the cluster at the application service layer.

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.

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 VCF 9.0 Workload Management, avSphere Namespaceis the construct that “sets the resource boundaries” for workloads running on a Supervisor, includingCPU, memory, and storage. The documentation explicitly states that a vSphere Namespace “sets the resource boundaries forCPU, memory, storage, and also the number of Kubernetes objects that can run within the namespace.” In the operational procedure “Set Resource Limits to a vSphere Namespace,” VMware further lists the configurable limits as:CPU(“set a limit to the CPU consumption”),Memory(“set a limit to the memory consumption”), andStorage(“set a limit on the storage consumption… per storage policy that is used”).

By contrast,Containersare not a namespace “resource limit” category; VMware documents “Container Defaults” separately (defaults for container CPU/memory requests and limits) rather than a top-level resource limit type. Similarly,Servicesare governed under “Object Limits” (how many Kubernetes objects like Services can exist), which is distinct from resource limits. Therefore, the three resource limitations defined on a vSphere Namespace areCPU, Memory, and Storage.

VCF 9.0 describes a standardized approach to deploying optional capabilities on VKS clusters viastandard packages. In the VCF Automation cloud services overview, VMware listsIstioamong the packages that “can be optionally installed” for VKS. For installing those packages, the VCF CLI provides a dedicatedpackage pluginthat “works on a workload cluster” and exposes explicitinstallworkflows.

The VCF CLI command reference shows the syntax for installing a package:

vcf package install INSTALLED_PACKAGE_NAME --package PACKAGE_NAME --version VERSION (with optional values files and overlays). This is the supported, VCF-aligned way to install standard packages such as Istio onto a VKS workload cluster in a controlled, declarative manner, including tracking reconciliation status and providing configuration via a values file.

Options that rely on ad-hoc downloads (curl) or building tooling (docker build) do not match the documented VCF package-management workflow for VKS standard packages. Therefore, the correct command family isvcf package install.

VCF 9.0 describes a vSphere Namespace as the control point where administrators defineresource boundariesfor workloads, explicitly stating that vSphere administrators can create namespaces and “configure them with specified amount ofmemory, CPU, and storage,” and that you can “set limits forCPU, memory, storage” for a namespace. This directly supports stepAas a day-2 control to keep multi-tenant clusters governed and prevent resource contention across different teams and workload types.

For monitoring and optimization, VCF 9.0 explains that day-2 operations include visibility into utilization and operational metrics for VKS clusters, noting that application teams can use day-2 actions and gain insights intoCPU and memory utilizationand advanced metrics (including contention and availability) for VKS clusters. In addition, VCF 9.0 monitoring guidance for VKS clusters states thatTelegraf and Prometheusmust be installed and configured on each VKS cluster before metrics and object details are sent for monitoring, and that VCF Operations supports metrics collection for Kubernetes objects (namespaces, nodes, pods, containers) via Prometheus. Since the Prometheus stack commonly includes Grafana dashboards for visualization, deployingPrometheus + Grafanamatches the required monitoring/optimization outcome inC.

In Kubernetes terms,non-persistentpod data (for example, transient logs and scratch space) is handled byephemeral storage, meaning the data exists only for the lifetime of the pod/workload and is not meant to survive beyond it. In the VCF Workload Management documentation, this concept is described directly: a pod requiresephemeral storageto store transient Kubernetes objects such as “logs” and “emptyDir volumes,” and this ephemeral (transient) storage “lasts as long as the pod continues to exist,” disappearing when the pod reaches end of life.

While VKS clusters can also consumepersistent storagethrough storage classes and CSI integration for stateful needs, that is specifically for data that must be retained (persistent volumes/claims). The question asks specifically aboutnon-persistentpod data, which aligns with the documented ephemeral/transient storage behavior for pod runtime needs. Therefore, the correct choice isEphemeral storage.