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Difficulty: MediumPlanning and Assessing Cloud Compute Solutions

An enterprise DevOps team is planning compute resources on Google Cloud for two distinct application components. Component 1 consists of a specialized network proxy service that requires custom Linux kernel module modifications. Component 2 consists of multiple stateless REST API microservices packaged in standard Docker containers, where the team wants to eliminate cluster node management overhead. Which compute architecture should the team select to fulfill these requirements?

  1. Deploy Component 1 on Compute Engine virtual machine instances and Component 2 on Google Kubernetes Engine (GKE) Autopilot clusters.Answer
  2. B
    Deploy Component 1 on Google Kubernetes Engine (GKE) Autopilot clusters and Component 2 on Compute Engine virtual machine instances.
  3. C
    Deploy Component 1 on Cloud Functions and Component 2 on Cloud Run.
  4. D
    Deploy both Component 1 and Component 2 on Cloud Run using custom container images.

Answer

Deploy Component 1 on Compute Engine virtual machine instances and Component 2 on Google Kubernetes Engine (GKE) Autopilot clusters.
Compute Engine provides full access to the underlying virtual machine operating system, allowing administrators to load custom kernel modules. GKE Autopilot manages cluster infrastructure and node scaling automatically, eliminating node management overhead for standard containerized microservices.

Step-by-Step Solution

1
Analyze OS and kernel customization requirements for Component 1.
Identify that custom Linux kernel modifications require full infrastructure control provided by Compute Engine VMs, as managed container platforms prohibit host kernel changes.
Managed services like GKE Autopilot, Cloud Run, and Cloud Functions abstract away the underlying host OS and kernel.
2
Analyze operational overhead requirements for Component 2.
Select GKE Autopilot for standard containerized microservices to eliminate node provisioning, auto-scaling, and OS patch management.
GKE Autopilot handles node management automatically, aligning with the goal of reducing operational maintenance.

Key Concept

Selecting GCP Compute Services Based on OS Customization Needs and Operational Overhead
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Topics

Planning and Assessing Cloud Compute Solutions

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