Question 492 of 500
Planning and configuring a cloud solutionhardMultiple ChoiceObjective-mapped

Quick Answer

The answer is a managed instance group with autoscaling combined with scheduled scaling pre-warming before Black Friday. This architecture is correct because it uses autoscaling to keep costs low during normal periods by scaling down to minimal instances, while scheduled scaling proactively adds capacity before the traffic spike to avoid cold-start latency, ensuring the 20x surge is handled seamlessly without manual intervention. On the Google Associate Cloud Engineer exam, this scenario tests your understanding of how to pair autoscaler metrics with scheduled-based scaling, a common trap being that simple autoscaling alone reacts too slowly to sudden spikes, leading to dropped requests. The key insight is that prewarming bridges the gap between reactive scaling and predictable demand. Memory tip: think “react for normal, schedule for the storm” — autoscaling handles the day-to-day, but prewarming is your Black Friday insurance.

Google ACE Planning and configuring a cloud solution Practice Question

This ACE practice question tests your understanding of planning and configuring a cloud solution. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.

An e-commerce platform sees a 20x traffic spike every Black Friday. The rest of the year traffic is low and stable. The team wants to minimize costs during normal periods while handling the annual peak without manual intervention. Which architecture achieves this?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

  • Clue: "minimum / minimize"

    Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

Question 1hardmultiple choice
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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

Managed instance group with autoscaling + scheduled scaling pre-warming before Black Friday

Option B is correct because it combines managed instance group autoscaling for normal low-cost operation with scheduled scaling to pre-warm capacity before the Black Friday spike, ensuring seamless handling of the 20x traffic surge without manual intervention. This approach uses the 'autoscaler' and 'scheduled scaling' features in Google Cloud to dynamically adjust resources based on load, while pre-warming prevents cold-start latency during the peak.

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.

  • Pre-provision 20x capacity year-round to guarantee Black Friday performance

    Why it's wrong here

    Permanent over-provisioning wastes ~19x the resources for 364 days per year — prohibitively expensive.

  • Managed instance group with autoscaling + scheduled scaling pre-warming before Black Friday

    Why this is correct

    MIG autoscaling handles demand-based scale-out automatically. Scheduled scaling policies can pre-warm additional capacity hours before the known Black Friday spike — combining reactive and proactive scaling.

    Clue confirmation

    The clue word "minimum / minimize" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Deploy on Cloud SQL — it scales compute automatically for traffic spikes

    Why it's wrong here

    Cloud SQL doesn't automatically scale compute for web traffic — it's a database service. Compute scaling is for application servers, not databases.

  • Add 20 manual VMs on Black Friday and delete them afterward each year

    Why it's wrong here

    Manual scaling requires human intervention and is error-prone. Autoscaling with scheduled policies automates this without annual manual effort.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the misconception that database services like Cloud SQL can automatically scale compute for traffic spikes, but in reality, Cloud SQL requires manual vertical scaling or read replicas and does not handle web-tier traffic spikes natively.

Detailed technical explanation

How to think about this question

Managed instance groups with autoscaling use metrics like CPU utilization, HTTP load balancing serving capacity, or Stackdriver custom metrics to scale instances; scheduled scaling allows defining a 'cool-down' period and a target size before the event to avoid the lag of autoscaling from zero. Under the hood, the autoscaler calculates desired size based on the maximum of all metric signals, and pre-warming ensures the load balancer has time to distribute traffic to new instances, preventing request queuing or timeouts during the initial spike.

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.

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FAQ

Questions learners often ask

What does this ACE question test?

Planning and configuring a cloud solution — This question tests Planning and configuring a cloud solution — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Managed instance group with autoscaling + scheduled scaling pre-warming before Black Friday — Option B is correct because it combines managed instance group autoscaling for normal low-cost operation with scheduled scaling to pre-warm capacity before the Black Friday spike, ensuring seamless handling of the 20x traffic surge without manual intervention. This approach uses the 'autoscaler' and 'scheduled scaling' features in Google Cloud to dynamically adjust resources based on load, while pre-warming prevents cold-start latency during the peak.

What should I do if I get this ACE question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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