- A
Move the transcoding pipeline to Cloud Functions to automatically scale without VM management
Why wrong: Cloud Functions does not support GPU accelerators required for transcoding.
- B
Increase the memory of all instances to 64 GB and manually select GPU types with more memory
Why wrong: This may fix memory but increases costs further and does not address dynamic needs.
- C
Switch all instances to preemptible VMs to reduce cost, and increase the number of retry attempts for failed jobs
Why wrong: Preemptible VMs are cheaper but can be terminated anytime, likely increasing failures.
- D
Use a managed instance group with custom autoscaling based on CPU/memory utilization and implement a queue-based scaling metric
Autoscaling ensures right-sized instances are used, reducing failures and costs.
Cloud Digital Leader Fundamental cloud concepts Practice Question
This GCDL practice question tests your understanding of fundamental cloud concepts. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A media streaming company runs its video transcoding pipeline on Google Cloud. The pipeline uses Compute Engine instances with GPU accelerators to process videos. The instances are started and stopped by a custom scheduler based on a Cloud Pub/Sub queue of new video uploads. Recently, the team noticed that transcoding jobs are failing intermittently with 'Out of memory' errors on some instances, and the overall cost has increased by 30% over the past month. The operations team reports that the same job configurations used to succeed before. The pipeline does not use any managed instance groups or autoscaling; each job provisions its own instance manually via a script. The company wants to reduce failures and costs. Which course of action should they take?
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
Use a managed instance group with custom autoscaling based on CPU/memory utilization and implement a queue-based scaling metric
Option D is correct because using a managed instance group (MIG) with custom autoscaling based on CPU/memory utilization and a queue-based scaling metric (e.g., Cloud Pub/Sub queue depth) addresses both the intermittent 'Out of memory' errors and the cost increase. The MIG automatically provisions and terminates instances based on actual workload, preventing resource over-provisioning (which drives cost) and under-provisioning (which causes OOM failures). This eliminates the manual, static instance provisioning that cannot adapt to varying job resource requirements.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Move the transcoding pipeline to Cloud Functions to automatically scale without VM management
Why it's wrong here
Cloud Functions does not support GPU accelerators required for transcoding.
- ✗
Increase the memory of all instances to 64 GB and manually select GPU types with more memory
Why it's wrong here
This may fix memory but increases costs further and does not address dynamic needs.
- ✗
Switch all instances to preemptible VMs to reduce cost, and increase the number of retry attempts for failed jobs
Why it's wrong here
Preemptible VMs are cheaper but can be terminated anytime, likely increasing failures.
- ✓
Use a managed instance group with custom autoscaling based on CPU/memory utilization and implement a queue-based scaling metric
Why this is correct
Autoscaling ensures right-sized instances are used, reducing failures and costs.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume increasing resources (Option B) or using cheaper VMs (Option C) will solve the problem, but Cisco tests the understanding that intermittent failures in a batch processing pipeline are often due to lack of dynamic scaling, not static resource sizing or cost alone.
Detailed technical explanation
How to think about this question
Under the hood, a managed instance group with custom autoscaling can use a 'queue depth' metric from Cloud Pub/Sub (e.g., the number of outstanding messages) to scale the number of instances. This ensures that instances are created only when there are pending jobs and terminated when idle, directly correlating resource allocation with demand. The OOM errors likely occur because the manual script provisions instances with a fixed machine type (e.g., n1-standard-4 with 15 GB RAM) that is insufficient for larger video files; autoscaling can also use instance templates with different machine types or allow per-instance configuration based on job metadata.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Fundamental cloud concepts — study guide chapter
Learn the concepts, then practise the questions
- →
Fundamental cloud concepts practice questions
Targeted practice on this topic area only
- →
All GCDL questions
507 questions across all exam domains
- →
Google Cloud Digital Leader study guide
Full concept coverage aligned to exam objectives
- →
GCDL practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related GCDL practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Why cloud technology is transforming business practice questions
Practise GCDL questions linked to Why cloud technology is transforming business.
Fundamental cloud concepts practice questions
Practise GCDL questions linked to Fundamental cloud concepts.
Google Cloud products, services, and solutions practice questions
Practise GCDL questions linked to Google Cloud products, services, and solutions.
Scaling with Google Cloud operations practice questions
Practise GCDL questions linked to Scaling with Google Cloud operations.
Trust and security with Google Cloud practice questions
Practise GCDL questions linked to Trust and security with Google Cloud.
GCDL fundamentals practice questions
Practise GCDL questions linked to GCDL fundamentals.
GCDL scenario practice questions
Practise GCDL questions linked to GCDL scenario.
GCDL troubleshooting practice questions
Practise GCDL questions linked to GCDL troubleshooting.
Practice this exam
Start a free GCDL practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this GCDL question test?
Fundamental cloud concepts — This question tests Fundamental cloud concepts — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use a managed instance group with custom autoscaling based on CPU/memory utilization and implement a queue-based scaling metric — Option D is correct because using a managed instance group (MIG) with custom autoscaling based on CPU/memory utilization and a queue-based scaling metric (e.g., Cloud Pub/Sub queue depth) addresses both the intermittent 'Out of memory' errors and the cost increase. The MIG automatically provisions and terminates instances based on actual workload, preventing resource over-provisioning (which drives cost) and under-provisioning (which causes OOM failures). This eliminates the manual, static instance provisioning that cannot adapt to varying job resource requirements.
What should I do if I get this GCDL question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jun 25, 2026
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.