Cloud Digital Leader Scaling with Google Cloud operations Practice Question
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?
⚠ Common exam trap
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.
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
Ly 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.
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
The premise that achieving 99.99% requires unaffordable cloud infrastructure mislocates the cost: Google Cloud's zonal and managed services already carry 99.99% availability, for example multi-zone Compute Engine and regional managed services. What raises cost is the engineering investment to design, operate, and automate failover, not the platform's own uptime. Even if higher reliability is more expensive, the reason to reject 99.99% here is that the internal tool's low business impact does not justify that price, not that the company cannot pay it.
- ✓
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.
- ✗
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 service-level agreements contradict the claim that no service can provide 99.99%; for instance, Cloud Storage states 99.99% uptime and regional managed offerings can exceed that without custom engineering. The limitation that might prevent 99.99% for this internal tool is not platform capability but the combined availability of the application, dependencies, and operational processes. A service can achieve 99.99% only if the entire stack and runbook are designed for that target, so a platform cap is a common misconception.
- ✗
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
Deferring the SLO target to next quarter based on speculative popularity ignores the error-budget principle: the current business value of an internal tool should determine the reliability target today. An SLO is a metric of what users need, not a roadmap milestone; frequently changing targets also undermines data-driven review and can mask reliability regressions. The SRE should justify 99.5% by current usage criticality, not promise an arbitrary future increase.
Go deeper
Related to this question
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Benefits of Google Cloud
Key term
SLO
A Service Level Objective is a measurable target for a specific aspect of a service's performance or reliability that a team commits to meeting over a defined period.
Key term
Availability
Availability is the measure of how often a system or service is operational and accessible when needed, typically expressed as a percentage of uptime.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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