Pass the VMware VCAP-VKS 3V0-24.25 Questions and answers with CertsForce

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= < KUBERNETES-CONTROL-PLANE-IP > --vsphere-username < VCENTER-SSO-USER > “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.

In VMware Cloud Foundation (VCF) 9.0, providing secure, centralized access to Kubernetes clusters is a critical requirement for enterprise compliance. The vSphere Kubernetes Service (VKS) utilizes OpenID Connect (OIDC) as the primary supported protocol for integrating with external identity providers (IdPs). While vCenter Server itself supports SAML 2.0 for administrative access to the vSphere Client, the workload clusters (VKS) specifically leverage OIDC to provide a modern, token-based authentication flow for developers and automated systems.

Through the integration of the Pinniped authentication service within the vSphere Supervisor, administrators can configure VKS clusters to delegate authentication to external providers like Okta, Microsoft Entra ID (formerly Azure AD), or PingFederate. When a developer uses the kubectl vsphere login command, the system facilitates an OIDC flow that issues short-lived identity tokens. This ensures that user identities are managed in a single source of truth rather than locally on each cluster. Although Active Directory (Option D) is a common identity source, it is typically reached via an OIDC provider or integrated into vCenter ' s SSO, which then presents an OIDC interface to the Kubernetes API. VCF 9.0 documentation emphasizes OIDC because of its native compatibility with Kubernetes authentication headers and its ability to handle complex claims and group memberships efficiently within a cloud-native SDDC environment.

In VCF 9.0, cluster autoscaling is delivered as anoptionalcapability that requires installing theCluster Autoscaleras a standard package. The VCF 9.0 materials explicitly call out Cluster Autoscaler as an optionally installed package for vSphere Kubernetes Service, alongside other optional packages (for example, Harbor, Velero, Istio, etc.). The release information further emphasizes that autoscaling features (including newer behaviors such as scaling from/to zero for supported VKr versions) require that “the autoscaler standard package” be installed.

Operationally, installing the autoscaler package provides the controller that watches pending pods and node utilization signals and then drives the required changes in desired worker capacity. After that controller is present, you typically express scaling intent through the cluster’s declarative configuration (for example, worker pool/node pool constraints and limits) so the autoscaler can act within the boundaries you define. Without the autoscaler package, changing replica counts or expecting automatic node growth/shrink will not produce autoscaling behavior because the control loop that performs those actions is missing.

Answer (Correct Order):

Run the install command:velero install … --provider aws --bucket < bucket > … --plugins … --backup-location-config …

Apply BackupStorageLocation YAML.

Apply VolumeSnapshotLocation YAML.

Run test backup:velero backup create test-backup --include-namespaces " myapp1 "

The correct sequence follows Velero’s operational model: install the Velero components first, then define where backups and snapshots are stored, and finally validate with a real backup. In VCF 9.0, the Velero Plugin for vSphere installation command includes parameters for the object-store provider, bucket, and plugin images, which establishes the Velero control plane in the target namespace and prepares it to communicate with an S3-compatible store.

After the installation is in place, you apply theBackupStorageLocationconfiguration so Velero has a durable destination for Kubernetes backup metadata in the object store. This aligns with the VCF 9.0 guidance that backups upload Kubernetes metadata to the object store and require S3-compatible storage for backup/restore workflows.

Next, apply theVolumeSnapshotLocationso Velero knows how and where to create/track volume snapshots for stateful workloads. The VCF 9.0 install example explicitly includes snapshot/backup location configuration parameters, reflecting that both must be set for complete protection.

Finally, run a test backup scoped to the namespace (--include-namespaces=my-namespace) to confirm end-to-end functionality.

Hosts and Clusters

To create avSphere Zone(used as a Supervisor Management Zone and/or Workload Zone), the administrator must start from the vSphere Client inventory wherevCenterand its clusters are managed. That’s why the correct starting point in the “Inventories” toolbar isHosts and Clusters—it is the entry point used to select the vCenter object and the target clusters.

VCF 9.0 documents the zone-creation workflow as:navigate to vCenter, thenSelect Configure, thenselect vSphere Zones, and finally clickAdd New vSphere Zone. After naming the zone, youselect a vSphere cluster to add to the zoneand finish the wizard.

This sequence matches the intent of the hotspot: you must first open the inventory view that exposes vCenter and clusters (Hosts and Clusters), then perform the configuration steps under vCenter to define vSphere Zones. Once created, these zones can later be selected during Supervisor deployment (for multi-zone placement) or assigned to namespaces for workload placement.

Cluster API (CAPI) is a foundational Kubernetes sub-project integrated into VMware Cloud Foundation (VCF) 9.0 via the vSphere Kubernetes Service (VKS) . It is designed to bring declarative, Kubernetes-style APIs to cluster creation, configuration, and management. In a VCF environment, the vSphere Supervisor acts as the " Management Cluster, " utilizing CAPI to automate the entire lifecycle of workload clusters (formerly known as TKG clusters).

Instead of requiring manual infrastructure provisioning, CAPI allows administrators to define the desired state of a Kubernetes cluster—including its version, node count, and underlying hardware resources—using YAML manifests. The vSphere Kubernetes Service then works to reconcile the current state of the infrastructure with this defined desired state. This transition to declarative management is a core component of VCF 9.0, as it enables " Kubernetes-on-Kubernetes " orchestration. This ensures that Day 1 operations (deployment) and Day 2 operations (scaling, patching, and upgrading) are consistent, repeatable, and less prone to human error. While other options describe components like cert-manager (Option A), Container Network Interfaces (Option C), or vulnerability scanners (Option D), only Option B accurately identifies CAPI’s role as the engine for automated, policy-driven cluster lifecycle management within the VMware SDDC stack.

VCF 9.0 design guidance for theSupervisor NSX Load Balancer modelstates that theNSX load balancers run on NSX Edges, and sets explicit sizing requirements at theEdge nodelevel. In the “NSX Load Balancer Design Requirements,” VCF 9.0 requires that theNSX Edge cluster must be deployedbecause “NSX Load Balancers run on NSX Edges.” It further requires that“NSX Edge nodes must be deployed with a minimum of Large form factor”because NSX load balancers havefixed resource allocations on NSX Edge nodes, and the Large form factor is needed to accommodate basic system and workload needs.

This directly ties “deployment size” of the load balancer service capacity to theEdge node form factor(Small/Medium/Large, etc.) rather than the number of pods or the number of clusters. The document also notes that if additional load balancers are required, NSX Edges can bescaled up or out, again reinforcing that sizing is anEdge nodesizing decision.

The problem describes demand spikes where capacity exists, but the application cannot meet demand—this typically indicates the cluster needs toscale out(more nodes/pods) automatically when load increases. In VCF 9.0, VKS supportsCluster Autoscaleras an optional package and specifically calls out improvements: “Cluster Autoscaler supports scaling from zero or to zero… You must have the autoscaler standard package installed.” This directly supports optionA(install cluster autoscaling) as the mechanism to dynamically add capacity during peak events and reduce it afterward, optimizing cost and operations while meeting bursts. A load balancer (including Foundation Load Balancer) helps distribute traffic acrossexistingendpoints, but it does not create new compute capacity when pods are pending due to insufficient nodes. Similarly, installing Contour relates to ingress (routing inbound traffic) and is not, by itself, a capacity scaling solution. Oversubscription is a risky workaround that can degrade performance and does not provide targeted, policy-driven elasticity. Therefore, enablingcluster autoscalingis the correct way to address burst demand when underlying resources are available.

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.