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Zorluk: ZorPlanning and Assessing Cloud Compute Solutions

An online gaming company is designing its Google Cloud compute architecture for two core backend services with distinct requirements:

1. Service A: A stateless containerized microservice that handles incoming REST API player requests, experiences unpredictable traffic spikes, and requires zero cluster node administration with the ability to scale to zero instances.
2. Service B: A legacy physics engine that requires custom Linux kernel patches and direct root access to the host virtual machine operating system.

Which TWO compute strategies should the cloud engineer choose to meet these requirements with optimal operational efficiency? (Select TWO)

  1. Deploy Service A on Cloud Run to leverage fully managed serverless container execution with automatic scaling to zero.Cevap
  2. Deploy Service B on Compute Engine Virtual Machines to support direct access to the host OS and custom kernel module installations.Cevap
  3. C
    Deploy Service A on Cloud Functions to host the full multi-container REST API application framework.
  4. D
    Deploy Service B on Google Kubernetes Engine (GKE) Autopilot clusters to automate custom Linux kernel configuration on underlying nodes.
  5. E
    Deploy Service B on Spot Compute Engine Virtual Machines to permanently retain custom kernel settings while guaranteeing fault tolerance.

Cevap

Deploy Service A on Cloud Run and deploy Service B on Compute Engine Virtual Machines.
Cloud Run provides serverless container management for stateless HTTP services with zero node overhead and scale-to-zero capabilities. Compute Engine virtual machines provide Infrastructure-as-a-Service access, allowing arbitrary OS-level customization and custom Linux kernel patches.

Adım Adım Çözüm

1
Analyze Service A requirements
Service A requires running a stateless container, zero node management, handling unpredictable HTTP traffic, and scaling to zero.
Cloud Run provides serverless container execution that scales down to zero instances when idle and abstracts away infrastructure management completely.
2
Analyze Service B requirements
Service B requires custom OS kernel patches and direct root level access to the underlying virtual machine OS.
Compute Engine VMs offer complete control over the guest OS kernel and system configuration, which managed container platforms restrict.
3
Evaluate and reject invalid options
Cloud Functions is unsuitable for complex container microservices; GKE Autopilot prevents custom node kernel modifications; Spot VMs are intended for fault-tolerant workloads due to preemption.
Matching workload constraints precisely prevents operational failure and unexpected architectural limitations.

Anahtar Kavram

Selecting GCP Compute Services Based on Workload Constraints and OS Requirements
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Planning and Assessing Cloud Compute Solutions

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