Google Associate Cloud Engineer exam dumps

Google Associate Cloud Engineer practice question 65 of 375

Associate Cloud Engineer. Free level, Google Cloud. Free question with the correct answer and a full explanation.

Google Associate Cloud Engineer Question 65

Single answerGoogle Cloud Platform

You are tasked with setting up a cost-effective, scalable system for a batch processing job that runs intermittently and can handle interruptions. Which configuration would be most appropriate for this scenario in Google Cloud Platform?

  1. A

    Use preemptible VM instances with a custom machine type optimized for the workload.

  2. B

    Use standard on-demand VM instances with a custom machine type optimized for the workload.

  3. C

    Use preemptible VM instances with a standard machine type.

  4. D

    Use standard on-demand VM instances with a standard machine type.

Show answer and explanation

Correct answer: A

Explanation

For batch processing jobs that are intermittent and can tolerate interruptions, preemptible VM instances provide a cost-effective solution due to their lower pricing compared to on-demand instances. Coupling them with a custom machine type ensures that the resource allocation is tailored to the workload, maximizing performance while still keeping costs low.

  • A. Correct.

    Preemptible VM instances are cost-effective and ideal for workloads that can handle interruptions. Custom machine types allow you to optimize resources for the specific needs of your job, ensuring efficient performance.

  • B. Incorrect.

    Standard on-demand VMs offer reliability but at a higher cost, which is not necessary for a batch processing job that can tolerate interruptions.

  • C. Incorrect.

    While preemptible VMs are cost-effective, using a standard machine type might not optimize resource usage for your specific workload, potentially leading to inefficiencies.

  • D. Incorrect.

    Standard on-demand VMs with standard machine types are the least cost-effective option and may not be optimized for your specific workload requirements.

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