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?
⚠ Common exam trap
The trap is overlooking preemptible VMs because of the assumption that batch jobs require guaranteed availability, when in fact the cost savings and tolerance for interruption make them the best choice for this scenario.
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
For a monthly batch job processing large files (up to 100 TB) with a custom Linux executable, preemptible VMs on Compute Engine offer the lowest cost. Preemptible VMs are significantly cheaper than standard VMs and are suitable for batch jobs that can tolerate interruptions, as the job can be restarted if preempted. Since the job runs once a month for about 12 hours, the cost savings outweigh the risk of preemption.
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.
Go deeper
Related to this question
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Compute Options on Google Cloud
Key term
Compute Engine
Compute Engine is Google Cloud's Infrastructure-as-a-Service (IaaS) offering that lets you create and run virtual machines on Google's infrastructure.
Key term
Batch
Batch is a cloud computing service that runs large numbers of computing jobs as a group, or batch, without needing to manage individual servers.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This GCDL practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCDL exam.