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Scaling with Google Cloud operationseasyMultiple ChoiceObjective-mapped

Cloud Digital Leader Scaling with Google Cloud operations Practice Question

This GCDL practice question tests your understanding of scaling with google cloud operations. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 startup has deployed a Node.js application on Cloud Run. They are seeing a higher-than-expected bill for Cloud Run usage. The application is accessed by users worldwide, and traffic patterns show occasional spikes. They want to reduce costs while maintaining performance. They currently have no concurrency management and use the default Cloud Run settings. What should they do first?

Clue words in this question

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

  • Clue: "first"

    Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.

Question 1easymultiple 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

Set a maximum number of concurrent requests per container instance to reduce over-provisioning.

Option C is correct because Cloud Run bills for CPU time during request processing, and the default setting allows unlimited concurrent requests per container instance. By setting a maximum concurrency, you prevent a single instance from being overwhelmed during traffic spikes, which reduces the number of instances needed and avoids over-provisioning. This directly lowers costs while maintaining performance by ensuring each instance handles only its optimal load.

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.

  • Implement a caching layer with Cloud CDN.

    Why it's wrong here

    Caching can reduce requests but does not address the root cause of over-provisioning instances; it is a secondary optimization.

  • Move the application to Compute Engine with a smaller machine type.

    Why it's wrong here

    Migrating to VMs introduces management overhead and may not be cheaper if the application scales dynamically.

  • Set a maximum number of concurrent requests per container instance to reduce over-provisioning.

    Why this is correct

    Increasing concurrency allows a single instance to handle multiple requests, reducing the number of instances needed and lowering costs.

    Clue confirmation

    The clue word "first" in the question point toward this answer.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Reduce the container memory limit to the minimum required.

    Why it's wrong here

    Reducing memory may cause out-of-memory errors if the application needs more, and does not directly reduce instance count.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates confuse reducing memory limits (Option D) with concurrency management, but memory reduction does not control the number of simultaneous requests hitting an instance, which is the root cause of over-provisioning in serverless billing.

Detailed technical explanation

How to think about this question

Cloud Run's default concurrency is 80 requests per container instance, but if the application is CPU-bound or has long request durations, this can lead to resource contention and excessive instance scaling. Setting a lower concurrency (e.g., 1 or 10) forces Cloud Run to spawn more instances to handle spikes, but each instance uses less CPU and memory, often reducing total cost because Cloud Run bills per vCPU-second and GB-second only during request processing. In practice, tuning concurrency based on application profiling (e.g., using Cloud Monitoring metrics like container CPU utilization) is critical to balance cost and latency.

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 GCDL question test?

Scaling with Google Cloud operations — This question tests Scaling with Google Cloud operations — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Set a maximum number of concurrent requests per container instance to reduce over-provisioning. — Option C is correct because Cloud Run bills for CPU time during request processing, and the default setting allows unlimited concurrent requests per container instance. By setting a maximum concurrency, you prevent a single instance from being overwhelmed during traffic spikes, which reduces the number of instances needed and avoids over-provisioning. This directly lowers costs while maintaining performance by ensuring each instance handles only its optimal load.

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.

Are there clue words in this question I should notice?

Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 25, 2026

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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.