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Difficulty: Very hardDeploying and Managing Google Kubernetes Engine (GKE) Clusters and Workloads

An organization is deploying infrastructure on Google Kubernetes Engine (GKE) in region us-central1 to support two distinct applications. The first application consists of fault-tolerant, stateless batch-processing jobs that can tolerate node interruptions. The second application is a legacy security monitoring daemon that requires direct access to host kernel modules and privileged Linux capabilities on the underlying nodes. Additionally, an administrator needs to configure their local workstation to manage workloads on this new cluster named 'analytics-cluster' using kubectl. Which TWO actions or configuration choices should the administrator implement to meet these requirements?

  1. Deploy a GKE Standard cluster containing a dedicated Spot VM node pool for the stateless batch jobs, while hosting the security daemon on nodes with privileged execution enabled.Answer
  2. Execute `gcloud container clusters get-credentials analytics-cluster --region us-central1` on the workstation to fetch cluster endpoint and authentication details into kubeconfig.Answer
  3. C
    Execute `gcloud config set container/cluster analytics-cluster` on the workstation to authorize local kubectl commands against the GKE control plane.
  4. D
    Deploy a GKE Autopilot cluster using Spot pod resources to host both the stateless batch workloads and the host-kernel monitoring security daemon.

Answer

The correct choices are deploying a GKE Standard cluster with a Spot VM node pool for fault-tolerant jobs and privileged node support, and executing `gcloud container clusters get-credentials analytics-cluster --region us-central1` to configure workstation authentication for kubectl.
Deploying a GKE Standard cluster with a Spot VM node pool satisfies both requirements: Spot VMs minimize costs for stateless, fault-tolerant batch jobs, while Standard mode permits running privileged pods that access underlying node kernel modules. Running `gcloud container clusters get-credentials` correctly populates the local kubeconfig file with the cluster endpoint and authentication tokens required for kubectl operation.

Step-by-Step Solution

1
Evaluate workload architectural requirements against GKE cluster modes.
Identified that the host-kernel security daemon requires GKE Standard mode because GKE Autopilot blocks privileged pods and custom host kernel access.
GKE Autopilot is fully managed and enforces strict security boundaries that prohibit elevated node permissions.
2
Select compute optimization strategies for stateless batch processing.
Configured a Spot VM node pool within the GKE Standard cluster.
Spot VMs provide significant cost discounts suitable for fault-tolerant batch workloads that can handle node preemptions.
3
Determine the proper workstation command to configure kubectl cluster credentials.
Identified `gcloud container clusters get-credentials analytics-cluster --region us-central1` as the correct credential retrieval method.
This command retrieves cluster certificate authority data and auth tokens, updating the local kubeconfig file so kubectl can communicate with the cluster master.

Key Concept

GKE Cluster Modes & Workstation Kubeconfig Management
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Topics

Deploying and Managing Google Kubernetes Engine (GKE) Clusters and Workloads