PCDOE Managing Google Cloud costs Practice Question
This PCDOE practice question tests your understanding of managing google cloud costs. 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.
A DevOps team is analyzing Google Cloud costs and notices that spending on BigQuery has increased significantly. They want to reduce costs without impacting ongoing analytical workloads. Which TWO actions should they take? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set custom cost controls like query quotas and maximum bytes billed per query.
Option C is correct because BigQuery allows you to set custom cost controls such as query quotas (e.g., concurrent queries per project) and maximum bytes billed per query. These controls cap resource usage at the query level, preventing runaway costs while still allowing analytical workloads to run within defined limits. This directly addresses cost spikes without blocking ongoing operations.
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.
✗
Switch to on-demand pricing to pay only for queries run.
Why it's wrong here
On-demand may be more expensive for high-volume workloads; flat-rate is better.
✗
Enable column-level security to restrict access to sensitive data.
Why it's wrong here
This is a security measure, not directly cost-saving.
✓
Set custom cost controls like query quotas and maximum bytes billed per query.
Why this is correct
Limits prevent expensive queries from running unbounded.
Related concept
Read the scenario before looking for a memorised answer.
✗
Delete unused datasets to reduce storage costs.
Why it's wrong here
Deleting datasets removes data and may impact analytics; better to archive old data.
✓
Implement flat-rate pricing with reservations for consistent workloads.
Why this is correct
Flat-rate pricing caps costs for predictable usage, avoiding per-query charges.
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 confuse storage cost reduction (Option D) with the primary driver of BigQuery cost spikes, which is almost always query compute (bytes processed), not storage, and they may overlook that flat-rate pricing (Option E) is a valid cost-reduction strategy for consistent workloads.
Detailed technical explanation
How to think about this question
BigQuery pricing separates storage and analysis (query) costs. Query costs are based on the number of bytes processed; setting a maximum bytes billed per query (e.g., via the `maximum_bytes_billed` parameter in the API or console) prevents a single query from processing an unexpectedly large amount of data. Flat-rate pricing with reservations (Option E) provides predictable costs for consistent workloads by purchasing dedicated slots, which can be more economical than on-demand when usage is steady. Combining custom cost controls with reservations allows teams to cap per-query spend while benefiting from bulk pricing.
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.
Managing Google Cloud costs — This question tests Managing Google Cloud costs — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set custom cost controls like query quotas and maximum bytes billed per query. — Option C is correct because BigQuery allows you to set custom cost controls such as query quotas (e.g., concurrent queries per project) and maximum bytes billed per query. These controls cap resource usage at the query level, preventing runaway costs while still allowing analytical workloads to run within defined limits. This directly addresses cost spikes without blocking ongoing operations.
What should I do if I get this PCDOE 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.
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Question Discussion
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