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Google PCA Practice Question: A company runs batch processing jobs nightly that…
A company runs batch processing jobs nightly that can tolerate interruptions. They want to minimize compute costs for these jobs. Which Compute Engine machine type and provisioning model is most cost-effective?
⚠ Common exam trap
PCA often tests the difference between committed use discounts (for steady-state) and preemptible/spot VMs (for interruptible); candidates may incorrectly choose CUDs for batch jobs.
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
✓
Preemptible VMs with custom machine types
Preemptible VMs are up to 80% cheaper than standard VMs and are ideal for fault-tolerant, interruptible batch jobs. Custom machine types allow tailoring CPU and memory to the workload, avoiding over-provisioning and further reducing cost.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
E2 custom VMs with sole-tenant nodes
Why it's wrong here
Sole-tenant nodes are for licensing or compliance, not cost savings.
- ✗
N2 standard VMs with committed use discounts
Why it's wrong here
Committed use discounts require 1-3 year commitments, less flexible for nightly jobs.
- ✓
Preemptible VMs with custom machine types
Why this is correct
Preemptible VMs suit interruptible batch workloads because they cost substantially less than standard instances, and Google forcibly stops them after 24 hours. Custom machine types let you match vCPU and memory precisely to the job, avoiding waste from oversized predefined shapes. Together they satisfy the stem's dual constraints: tolerance of interruptions and minimised compute cost.
- ✗
GPU-accelerated VMs
Why it's wrong here
GPUs are costly and unnecessary for general batch processing.
Go deeper
Related to this question
Learn chapter
Google Kubernetes Engine (GKE)
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.
Key term
Machine type
A machine type defines the virtual hardware resources (vCPU, memory, and sometimes GPU) assigned to a virtual machine instance in a cloud computing environment.
About these practice questions
This PCA question is part of Courseiva's 807-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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 PCA 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 PCA exam.