DevOps-SRE Exam Dumps : Site Reliability Engineering (SRE) Foundation v1.2

Comprehensive and Detailed Explanation From Exact Extract:

SRE defines toil as “manual, repetitive, automatable, tactical work tied to running a service” (SRE Book – Eliminating Toil). Repetitive outages are specifically noted as a form of operational toil. The SRE Book and SRE Workbook emphasize adopting automation, intelligent tooling, and machine-learning–assisted systems to reduce toil and decrease Mean Time to Repair (MTTR) and Mean Time to Restore Service (MTRS). The books state: “Reducing MTTR directly increases system reliability more effectively than attempting to eliminate all failures.” (SRE Book – Chapter: Managing Incidents).

AI and advanced automation help detect issues faster, classify patterns, trigger automated remediation, and reduce human intervention—delivering reliability gains through faster repair rather than perfect uptime.

Option A is the only option aligned with SRE’s reliability philosophy.

Options B and C incorrectly suggest increasing MTTR/MTRS.

Option D refers to “perfect MTRS,” which is impossible and contradicts SRE’s acceptance of failure.

Thus, A is correct.

Comprehensive and Detailed Explanation From Exact Extract:

Error budgets are a fundamental SRE mechanism for balancing reliability and innovation. The SRE book states: “The error budget directly governs the rate of change: as long as the service stays within budget, development velocity can remain high.” (SRE Book – Chapter: Service Level Objectives). This means teams can push changes aggressively as long as the allowed amount of unreliability has not been consumed.

The error budget acts as a safety threshold. When reliability dips and the error budget is consumed, SRE enforces a change freeze to restore stability. Google explains: “If the error budget is spent, releases are halted and efforts focus on improving reliability.” Feature velocity is not arbitrarily slowed—it is governed solely by the remaining error budget.

Option A best expresses this: when the error budget is high, teams can safely accelerate feature delivery.

Option D incorrectly suggests rushing, which contradicts controlled release practices.

Option B misinterprets error budgets as a percentage-based throttling system.

Option C incorrectly implies that innovation stops entirely only when empty.

Thus, A is the correct interpretation according to official SRE principles.

Comprehensive and Detailed Explanation From Exact Extract:

The future growth envelope refers to the anticipated growth trajectory of a service, including expected load, user demand, data volume, and performance requirements. Planning for this growth is essential to ensuring that a service can scale reliably without violating SLOs.

The Site Reliability Engineering Book, in discussions on capacity planning, states:

“A key element of capacity planning is estimating future demand so that systems can scale to meet user needs without sacrificing reliability.”

The SRE Workbook reinforces this concept:

“Understanding expected growth enables teams to design systems that scale and remain reliable as usage increases.”

Having the growth envelope defined enables:

Proper capacity planning

Avoiding resource exhaustion

Ensuring scalability before it becomes a reliability problem

Designing architectures that can handle future load

Why the other options are incorrect:

A Signed artifacts relate to supply chain security, not scaling.

C SLO/SLI reviews do not require growth envelope analysis.

D Error budgets relate to reliability thresholds, not capacity forecasting.

Thus, B is the correct answer.