Cloud Digital Leader Scaling with Google Cloud operations Practice Question
A company's SRE team is debating whether to automate a frequently performed manual operational task. The automation would take 4 weeks of engineering time to build. The manual task takes 30 minutes per occurrence and happens approximately 20 times per month. Using the SRE concept of 'toil,' how should the team approach this decision?
⚠ Common exam trap
The GCDL exam often tests the misconception that automation decisions require detailed financial cost analysis (like salary data) rather than the SRE principle of prioritizing toil elimination for long-term reliability gains, leading candidates to pick Option D or A.
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
✓
Build the automation: eliminating toil permanently is a core SRE principle, and the 4-week investment pays back within approximately 16 months while freeing engineers for higher-value reliability work indefinitely
Automating toil aligns with the core SRE principle of eliminating repetitive, manual work to free engineers for higher-value reliability tasks. The 4-week build cost is justified: 20 occurrences/month × 0.5 hours = 10 hours/month, so the payback period is 4 weeks × 40 hours/week ÷ 10 hours/month = 16 months, after which the team gains indefinite time savings. This decision does not require exact salary data, as the primary goal is reducing toil, not purely cost optimization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Do not automate — the manual task is only 10 hours per month and the 4-week build cost is too high to justify
Why it's wrong here
SRE philosophy strongly favors eliminating toil through automation. 10 hours/month of toil is significant, and the automation investment pays back within ~16 months and then provides permanent relief. The long-term value far exceeds the short-term cost.
- ✓
Build the automation: eliminating toil permanently is a core SRE principle, and the 4-week investment pays back within approximately 16 months while freeing engineers for higher-value reliability work indefinitely
Why this is correct
This is the SRE-aligned answer. Toil elimination is a core SRE value. The math: 10 hours/month saved, 160 hours invested → 16 month payback. But the more important point is that automation eliminates the toil permanently and scales with service growth, while manual toil grows proportionally. SREs should invest in eliminating toil even with moderate payback periods.
- ✗
Hire an additional junior engineer to perform the manual task more efficiently instead of automating
Why it's wrong here
Hiring more people to do toil is the opposite of SRE philosophy. It scales costs proportionally with growth and doesn't address the root cause. SRE explicitly avoids 'throwing people at the problem' when automation is feasible.
- ✗
The team cannot make this decision without knowing the exact annual salary cost of the engineers who perform the manual task
Why it's wrong here
This option incorrectly assumes the automation decision hinges on a precise cost model. SRE principles explicitly direct teams to eliminate automatable toil regardless of the exact dollar cost of the engineers performing it, because toil consumes time that should be spent on higher-value reliability engineering. The 10 hours/month manual effort is permanent recurring work that scales with service growth, while the 160-hour automation investment is a one-time capital cost with an approximately 16-month payback; once built, it requires no ongoing salary allocation. Even if the precise salary were known, it would only reinforce the decision, because the opportunity cost of toil extends beyond wages to include slower feature delivery, increased human error, and higher on-call burden.
Go deeper
Related to this question
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BigQuery and Data Analytics
Key term
Reliability
Reliability is the measure of a system's ability to consistently perform its intended functions without failure over a specified period of time under stated conditions.
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.