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| Section | Objectives |
|---|---|
| vSphere Kubernetes Service (VKS) | - Cluster lifecycle and operations - Kubernetes cluster deployment in VCF |
| VMware Cloud Foundation Architecture | - Lifecycle management and SDDC Manager concepts - VCF components and architecture design |
| Networking and Storage in VCF | - NSX networking concepts and configuration - vSAN storage integration |
| Operations and Troubleshooting | - Troubleshooting VCF and Kubernetes workloads - Monitoring and performance optimization |
| vSphere Infrastructure | - Compute, storage, and resource management - ESXi and vCenter administration |
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質問 # 29
Which three objects or object types are within the scope of a cluster backup for VMware vSphere Kubernetes Service (VKS)? (Choose three.)
正解：B、C、F
解説：
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).
質問 # 30
An administrator is upgrading an existing VMware vSphere Kubernetes Service (VKS) cluster and receives the following errors:
* kubectl get nodes fails with memcache.go and "server is currently unable to handle the request"
* couldn't get resource list for stats.antrea.tanzu.vmware.com/v1alpha1
* yaml: mapping values are not allowed in this context
The administrator successfully updated the Supervisor, but an attempt to update the VKS cluster failed. Based on the scenario, what is the cause of the problem?
正解：D
解説：
The errors described-specifically the memcache.go failure, the inability to fetch resource lists for Antrea, and the YAML context error-are classic symptoms of aConfiguration Context mismatch. In VCF 9.0, there are two distinct layers of API interaction: theSupervisor Cluster API(used for management tasks like creating clusters) and theGuest Cluster API(used for deploying workloads within the VKS).
When an administrator upgrades a Supervisor, the API endpoint or the available API groups may change. If the administrator attempts to run kubectl commands against a VKS cluster while their kubeconfig context is still pointing to the Supervisor (or vice versa), the client will encounter "mapping values" errors and "unable to handle request" errors because it is sending requests to an endpoint that does not recognize those specific resource definitions (like Antrea stats in the wrong context). To resolve this, the administrator must ensure they have switched to the correct context using kubectl config use-context <cluster-name> after the Supervisor update to ensure the local client is communicating with the correct API server and version of the Kubernetes binaries.
質問 # 31
A Platform Engineer is optimizing resource density for a high-volume batch processing workload. The workload consists of thousands of short-lived tasks that start and stop rapidly. The overhead of reserving memory for a full Guest OS for each task is a concern.
Review the following resource profile for a single task instance:
Task Runtime: < 2 minutes
CPU: High bursts
Memory: 512 MB
OS Dependency: Generic Linux userspace
Why are vSphere Pods the architecturally superior choice over TKG cluster nodes for this specific scenario? (Select all that apply.)
正解：A、C、D
質問 # 32
A Cloud Administrator is architecting a vSphere with Tanzu environment. They must decide on the appropriate Load Balancer topology to support a requirement for fully isolated network segments for different tenants (Namespaces), ensuring no shared routing infrastructure between tenants.
Review the following available Load Balancer integration options:
A: HAProxy with Frontend Network topology
B: NSX Advanced Load Balancer (Avi) with Default Gateway topology
C: NSX Load Balancer (integrated)
D: HAProxy with Basic topology
Which of these options satisfy the requirement for tenant network isolation? (Select all that apply.)
正解：A、C
質問 # 33
What Kubernetes component is responsible for workload creation?
正解：D
解説：
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.
質問 # 34
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