Google Cloud Associate Cloud Engineer 2025 — 50 Practice Questions Verified
Series:
CrashCourses Professional Study Series
Author:
Dr Z. Moomba, MBChB, MRCPsych | BethelWellness Ltd
Exam Target:
Google Cloud ACE
Year:
2025/2026
Format:
50 Questions with Verified Answers and Rationales
>
Author's Note:
This document is an original work produced for the CrashCourses Professional Study Series.
Clinical questions and professional scenarios were composed by Dr Z. Moomba based on current
exam objectives, published guidelines, and evidence-based sources (2024–2025). All patient
names, ages, and case details are fictional. Any resemblance to existing published Q&A banks is
coincidental. For personal study use only — not for reproduction or redistribution.
PART 1: CORE PRINCIPLES & FOUNDATIONS
1.
A pharmaceutical company is running massive biochemical simulations. These workloads are
highly fault-tolerant and can handle unexpected termination without compromising the overall job.
They need to minimize infrastructure spend as much as possible. Which Compute Engine
configuration should they adopt?
A. Provision E2 standard instances on an on-demand basis.
B. Utilize Spot VMs.
C. Deploy legacy Preemptible VMs to gain sustained use discounts.
D. Choose C3 compute-optimized VMs with committed use contracts.
Answer: B
,Lead:
Spot VMs provide the steepest discounts (up to 91% off standard rates) for batch, stateless, or
fault-tolerant workloads that can gracefully handle instance preemption.
Discriminator:
The prompt specifically highlights the need to "minimize infrastructure spend" for tasks that "can
handle unexpected termination." Spot instances are uniquely designed for exactly this profile.
Distractor:
Legacy Preemptible VMs (Option C) are older technology and critically, do not qualify for
sustained use discounts, making the premise of the option factually incorrect.
Examiner Insight:
Unlike older Preemptible VMs that forcefully terminate after 24 hours, Spot VMs have no maximum
runtime restriction, making them superior for long-running resilient workloads. [Google Cloud
Compute Docs 2025]
2.
A national vaccination booking system runs on a Managed Instance Group (MIG). During public
health announcements, traffic surges drastically. You want the MIG to dynamically scale out by
adding more VM instances whenever average CPU usage breaches 80%. What is the correct
configuration?
A. Set up a Cloud Monitoring alert that triggers a Cloud Function to spin up instances.
B. Deploy a stateful MIG configured with aggressive autohealing checks.
C. Attach an autoscaler to the MIG configured with a CPU utilization metric.
D. Route traffic through an unmanaged instance group linked to an application load balancer.
Answer: C
Rationale:
Lead:
Autoscalers seamlessly add or remove VM instances from a Managed Instance Group based on
defined metrics, such as CPU utilization or HTTP load balancing capacity.
Discriminator:
The scenario requires automatic instance addition specifically when "CPU usage breaches 80%."
A native autoscaler attached to the MIG handles this exact requirement out-of-the-box.
,Distractor:
Option A describes a highly fragile, custom-built workaround. Native autoscaling is infinitely more
reliable and requires no custom code maintenance.
High-Yield Point:
Always define an initialization period (cooldown) for your autoscaler so it doesn't prematurely
launch unnecessary instances while newly created VMs are still booting. [Google Cloud
Architecture Framework 2025]
3.
A maternity ward application requires a fully managed relational database to handle sensitive
patient admission records with strict ACID transactional consistency. Data must remain entirely
within the UK (`europe-west2`) and be highly available across zones. Which GCP service is
optimal?
A. Cloud Spanner
B. Cloud SQL for PostgreSQL
C. Cloud Bigtable
D. Firestore
Answer: B
Rationale:
Lead:
Cloud SQL provides fully managed, regional relational database services (PostgreSQL, MySQL,
SQL Server) that inherently support strict ACID transactions and High Availability (HA)
configurations.
Discriminator:
The combination of "relational," "strict transactional consistency," and "highly available across
zones" within a single region strongly points to Cloud SQL.
Distractor:
Cloud Spanner (Option A) also offers relational consistency but is engineered for massive, global
horizontal scaling. It is overkill and cost-prohibitive for a localized, single-region maternity ward
application.
Clinical Pearl:
, Configuring High Availability (HA) in Cloud SQL automatically provisions a standby instance in a
different zone within the same region, ensuring minimal downtime during hardware failures.
[Google Cloud Database Specs 2025]
4.
An orthopedic imaging center securely stores DEXA bone density scans in Cloud Storage. These
files are accessed heavily during the first 45 days for diagnostic review but are rarely touched
afterward. Compliance dictates a 7-year retention period. Which storage lifecycle approach is the
most cost-efficient?
A. Retain in Standard storage for 45 days, then transition to Coldline storage.
B. Retain in Standard storage for 45 days, then transition directly to Archive storage.
C. Retain in Nearline storage for the full 7 years.
D. Retain in Standard storage for 45 days, then transition to Nearline storage, followed by Archive
at year 5.
Answer: A
Rationale:
Lead:
Coldline storage is optimized for data accessed at most once every 90 days, providing an
excellent balance of low at-rest storage costs and manageable retrieval fees for infrequent
access.
Discriminator:
The initial 45-day heavy access period demands Standard storage. Following this, the data is
"rarely touched" but retained for compliance, making Coldline the perfect long-term, cost-
effective repository.
Distractor:
Transitioning directly to Archive (Option B) is risky; Archive is for data accessed less than once a
year. If a patient requires follow-up scans and old data is pulled, Archive retrieval costs are
significantly higher than Coldline.
Key Principle:
Cloud Storage lifecycle rules calculate the age of an object based on its creation timestamp, not
the date it was last accessed or modified. [Google Cloud Storage Lifecycle Docs 2025]
Series:
CrashCourses Professional Study Series
Author:
Dr Z. Moomba, MBChB, MRCPsych | BethelWellness Ltd
Exam Target:
Google Cloud ACE
Year:
2025/2026
Format:
50 Questions with Verified Answers and Rationales
>
Author's Note:
This document is an original work produced for the CrashCourses Professional Study Series.
Clinical questions and professional scenarios were composed by Dr Z. Moomba based on current
exam objectives, published guidelines, and evidence-based sources (2024–2025). All patient
names, ages, and case details are fictional. Any resemblance to existing published Q&A banks is
coincidental. For personal study use only — not for reproduction or redistribution.
PART 1: CORE PRINCIPLES & FOUNDATIONS
1.
A pharmaceutical company is running massive biochemical simulations. These workloads are
highly fault-tolerant and can handle unexpected termination without compromising the overall job.
They need to minimize infrastructure spend as much as possible. Which Compute Engine
configuration should they adopt?
A. Provision E2 standard instances on an on-demand basis.
B. Utilize Spot VMs.
C. Deploy legacy Preemptible VMs to gain sustained use discounts.
D. Choose C3 compute-optimized VMs with committed use contracts.
Answer: B
,Lead:
Spot VMs provide the steepest discounts (up to 91% off standard rates) for batch, stateless, or
fault-tolerant workloads that can gracefully handle instance preemption.
Discriminator:
The prompt specifically highlights the need to "minimize infrastructure spend" for tasks that "can
handle unexpected termination." Spot instances are uniquely designed for exactly this profile.
Distractor:
Legacy Preemptible VMs (Option C) are older technology and critically, do not qualify for
sustained use discounts, making the premise of the option factually incorrect.
Examiner Insight:
Unlike older Preemptible VMs that forcefully terminate after 24 hours, Spot VMs have no maximum
runtime restriction, making them superior for long-running resilient workloads. [Google Cloud
Compute Docs 2025]
2.
A national vaccination booking system runs on a Managed Instance Group (MIG). During public
health announcements, traffic surges drastically. You want the MIG to dynamically scale out by
adding more VM instances whenever average CPU usage breaches 80%. What is the correct
configuration?
A. Set up a Cloud Monitoring alert that triggers a Cloud Function to spin up instances.
B. Deploy a stateful MIG configured with aggressive autohealing checks.
C. Attach an autoscaler to the MIG configured with a CPU utilization metric.
D. Route traffic through an unmanaged instance group linked to an application load balancer.
Answer: C
Rationale:
Lead:
Autoscalers seamlessly add or remove VM instances from a Managed Instance Group based on
defined metrics, such as CPU utilization or HTTP load balancing capacity.
Discriminator:
The scenario requires automatic instance addition specifically when "CPU usage breaches 80%."
A native autoscaler attached to the MIG handles this exact requirement out-of-the-box.
,Distractor:
Option A describes a highly fragile, custom-built workaround. Native autoscaling is infinitely more
reliable and requires no custom code maintenance.
High-Yield Point:
Always define an initialization period (cooldown) for your autoscaler so it doesn't prematurely
launch unnecessary instances while newly created VMs are still booting. [Google Cloud
Architecture Framework 2025]
3.
A maternity ward application requires a fully managed relational database to handle sensitive
patient admission records with strict ACID transactional consistency. Data must remain entirely
within the UK (`europe-west2`) and be highly available across zones. Which GCP service is
optimal?
A. Cloud Spanner
B. Cloud SQL for PostgreSQL
C. Cloud Bigtable
D. Firestore
Answer: B
Rationale:
Lead:
Cloud SQL provides fully managed, regional relational database services (PostgreSQL, MySQL,
SQL Server) that inherently support strict ACID transactions and High Availability (HA)
configurations.
Discriminator:
The combination of "relational," "strict transactional consistency," and "highly available across
zones" within a single region strongly points to Cloud SQL.
Distractor:
Cloud Spanner (Option A) also offers relational consistency but is engineered for massive, global
horizontal scaling. It is overkill and cost-prohibitive for a localized, single-region maternity ward
application.
Clinical Pearl:
, Configuring High Availability (HA) in Cloud SQL automatically provisions a standby instance in a
different zone within the same region, ensuring minimal downtime during hardware failures.
[Google Cloud Database Specs 2025]
4.
An orthopedic imaging center securely stores DEXA bone density scans in Cloud Storage. These
files are accessed heavily during the first 45 days for diagnostic review but are rarely touched
afterward. Compliance dictates a 7-year retention period. Which storage lifecycle approach is the
most cost-efficient?
A. Retain in Standard storage for 45 days, then transition to Coldline storage.
B. Retain in Standard storage for 45 days, then transition directly to Archive storage.
C. Retain in Nearline storage for the full 7 years.
D. Retain in Standard storage for 45 days, then transition to Nearline storage, followed by Archive
at year 5.
Answer: A
Rationale:
Lead:
Coldline storage is optimized for data accessed at most once every 90 days, providing an
excellent balance of low at-rest storage costs and manageable retrieval fees for infrequent
access.
Discriminator:
The initial 45-day heavy access period demands Standard storage. Following this, the data is
"rarely touched" but retained for compliance, making Coldline the perfect long-term, cost-
effective repository.
Distractor:
Transitioning directly to Archive (Option B) is risky; Archive is for data accessed less than once a
year. If a patient requires follow-up scans and old data is pulled, Archive retrieval costs are
significantly higher than Coldline.
Key Principle:
Cloud Storage lifecycle rules calculate the age of an object based on its creation timestamp, not
the date it was last accessed or modified. [Google Cloud Storage Lifecycle Docs 2025]
