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Cloud Digital Leader Fundamental Cloud Concepts Practice Question

A company wants to run a batch job that processes large files (up to 100 TB each) using a custom Linux executable. The job runs once a month and takes about 12 hours. They want to minimise cost. Which compute option should they choose?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Compute Engine with preemptible VMs

Compute Engine Preemptible VMs offer deep discounts (up to 60-90% off) and are suitable for fault-tolerant batch jobs. Preemptible VMs can be terminated at any time, but since the job can be restarted, it's cost-effective. Persistent disks are required for data. Cloud Run has a timeout limit of 60 minutes. GKE with Spot VMs is also an option but adds overhead. Standard Compute Engine is more expensive.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Compute Engine with preemptible VMs

    Why this is correct

    Preemptible VMs are a cost-effective choice for fault-tolerant batch jobs because they are priced up to 80% lower than standard VMs and can run for up to 24 hours, which fits the job's duration. The key requirement is that the batch job must handle preemption events gracefully—using checkpoints, retries, or restarting from the last saved state—which ensures uninterrupted processing of large files despite possible interruptions. Given the explicit tolerance for interruptions, preemptible VMs reduce cost without compromising completion, making them the optimal compute service for this use case.

  • Compute Engine with standard VMs

    Why it's wrong here

    Standard VMs are more expensive than preemptible VMs and do not get preempted, but they provide no additional benefit for a batch job that is already fault-tolerant and designed to handle interruptions. Paying full price for guaranteed capacity is wasteful here because the workload does not require the higher reliability or predictable availability that standard VMs offer. For large-file batch processing where cost is a consideration, choosing standard VMs would unnecessarily inflate the bill without improving throughput or correctness, making them a less optimal choice.

  • Cloud Run

    Why it's wrong here

    Cloud Run is a serverless compute platform that executes containers in response to HTTP requests or events, but it imposes a maximum request timeout of 60 minutes, which is insufficient for a batch job that runs for 12 hours. Additionally, Cloud Run is designed for short-lived, stateless, or event-driven workloads, not for long-running batch processing that may need persistent disk state or the ability to resume from interruptions. The platform's automatic scaling and timeout limits make it unsuitable for processing very large files that require hours of continuous compute time.

  • App Engine Flexible Environment

    Why it's wrong here

    App Engine Flexible Environment is a platform-as-a-service (PaaS) designed primarily for hosting web applications and RESTful services, not for running batch jobs that process very large files. It lacks the explicit fault-tolerance mechanisms and cost models that preemptible VMs offer, and its scaling and request handling are optimized for user-facing traffic rather than long-running data processing tasks. While App Engine Flexible can run custom containers, it is not the intended or most efficient service for a 12-hour batch workload, making it a poor fit compared to Compute Engine with preemptible VMs.

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