- A
Higher SLOs are always more expensive to achieve and the company cannot afford cloud infrastructure that provides 99.99% availability
Why wrong: Google Cloud infrastructure itself is highly available — 99.99% is achievable but requires architectural effort (multi-zone, failover, redundancy). The argument is about whether the effort is proportionate to the value, not cloud infrastructure cost.
- B
For a non-critical internal tool, 99.99% reliability requires disproportionate engineering investment (redundancy, 24/7 on-call, chaos testing) compared to its business value; 99.5% matches the actual reliability need while preserving engineering capacity for higher-value work
This is the SRE argument. Reliability is not free — achieving 99.99% requires architectural complexity, 24/7 on-call readiness, and ongoing reliability engineering. For an internal tool, this investment would consume engineering time that could build features users value more. The SLO should match what the business actually needs, not maximize reliability for its own sake.
- C
Google Cloud cannot provide 99.99% availability for any service, so the SLO must be kept lower
Why wrong: Google Cloud's managed services do achieve 99.99%+ availability. The argument against 99.99% for this tool is about engineering investment proportionality, not platform capability limits.
- D
The team should set 99.5% now and plan to increase it to 99.99% next quarter when the tool becomes more popular
Why wrong: While SLOs can be revisited, this doesn't address the stakeholder's argument. The SRE's response should articulate why 99.5% is appropriate now based on the tool's business criticality, not promise future escalation.
Quick Answer
The answer is that the SRE team should keep the 99.5% target because for a non-critical internal tool, pursuing 99.99% reliability demands disproportionate engineering investment—such as redundant infrastructure, 24/7 on-call rotations, and chaos testing—that far outweighs the marginal business value gained. This directly applies the SRE principle of aligning SLO target justification with actual business need, where error budgets and cost-benefit analysis dictate that engineering capacity is preserved for higher-value work rather than over-engineering a low-priority system. On the Google Cloud Digital Leader exam, this scenario tests your understanding of how SRE prioritizes reliability investment based on criticality; a common trap is assuming higher numbers are always better, but the exam emphasizes that SLOs must match the tool’s role in the business. Remember the memory tip: “Non-critical tools get non-critical SLOs—99.5% is plenty, 99.99% is just expensive.”
Cloud Digital Leader Scaling with Google Cloud operations Practice Question
This GCDL practice question tests your understanding of scaling with google cloud operations. 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 company's SRE team sets an SLO of 99.5% monthly availability for a non-critical internal tool. A business stakeholder argues the target should be 99.99%. The SRE team pushes back. Which SRE argument best supports keeping the 99.5% target?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
For a non-critical internal tool, 99.99% reliability requires disproportionate engineering investment (redundancy, 24/7 on-call, chaos testing) compared to its business value; 99.5% matches the actual reliability need while preserving engineering capacity for higher-value work
Option B correctly applies the SRE principle of aligning SLOs with business value. For a non-critical internal tool, the cost of achieving 99.99% availability—including redundant infrastructure, 24/7 on-call rotations, and chaos engineering—far exceeds the marginal benefit over 99.5%. This preserves engineering capacity for higher-value work, which is a core tenet of Google's SRE approach to error budgets and cost-benefit analysis.
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.
- ✗
Higher SLOs are always more expensive to achieve and the company cannot afford cloud infrastructure that provides 99.99% availability
Why it's wrong here
Google Cloud infrastructure itself is highly available — 99.99% is achievable but requires architectural effort (multi-zone, failover, redundancy). The argument is about whether the effort is proportionate to the value, not cloud infrastructure cost.
- ✓
For a non-critical internal tool, 99.99% reliability requires disproportionate engineering investment (redundancy, 24/7 on-call, chaos testing) compared to its business value; 99.5% matches the actual reliability need while preserving engineering capacity for higher-value work
Why this is correct
This is the SRE argument. Reliability is not free — achieving 99.99% requires architectural complexity, 24/7 on-call readiness, and ongoing reliability engineering. For an internal tool, this investment would consume engineering time that could build features users value more. The SLO should match what the business actually needs, not maximize reliability for its own sake.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Google Cloud cannot provide 99.99% availability for any service, so the SLO must be kept lower
Why it's wrong here
Google Cloud's managed services do achieve 99.99%+ availability. The argument against 99.99% for this tool is about engineering investment proportionality, not platform capability limits.
- ✗
The team should set 99.5% now and plan to increase it to 99.99% next quarter when the tool becomes more popular
Why it's wrong here
While SLOs can be revisited, this doesn't address the stakeholder's argument. The SRE's response should articulate why 99.5% is appropriate now based on the tool's business criticality, not promise future escalation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that higher SLOs are always better or that cloud providers universally guarantee high availability, when the correct SRE approach is to set SLOs based on the actual user experience and business impact, not arbitrary targets.
Detailed technical explanation
How to think about this question
Error budgets are calculated as 1 - SLO; for a 99.5% monthly SLO, the error budget allows 0.5% downtime (about 3.6 hours per month), while 99.99% allows only 4.3 minutes. The engineering investment to reduce downtime from 3.6 hours to 4.3 minutes often requires multi-region active-active deployments, automated failover, and 24/7 incident response, which is justified only for customer-facing or revenue-critical services. Google's SRE literature explicitly warns against setting SLOs tighter than necessary, as it wastes resources and increases burnout.
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: For a non-critical internal tool, 99.99% reliability requires disproportionate engineering investment (redundancy, 24/7 on-call, chaos testing) compared to its business value; 99.5% matches the actual reliability need while preserving engineering capacity for higher-value work — Option B correctly applies the SRE principle of aligning SLOs with business value. For a non-critical internal tool, the cost of achieving 99.99% availability—including redundant infrastructure, 24/7 on-call rotations, and chaos engineering—far exceeds the marginal benefit over 99.5%. This preserves engineering capacity for higher-value work, which is a core tenet of Google's SRE approach to error budgets and cost-benefit analysis.
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: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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
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.
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