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

Comprehensive and Detailed Explanation From Exact Extract:

When a team exceeds its error budget, SRE practice requires applying error budget policies that restrict feature releases and shift focus toward reliability improvement. The idea is to prevent further degradation of user experience and ensure the service meets the agreed reliability targets.

The Site Reliability Engineering Book, Chapter “Service Level Objectives,” states:

“If the service exceeds its error budget, all new feature launches or risky changes are halted until reliability returns to acceptable levels. Engineering work should be directed toward addressing the causes of the budget overrun.”

This aligns with option A, which describes a reliability-focused response during sprint planning. Limiting sprint planning to post-mortem action items and reliability improvements is a direct application of error budget policies.

Additional guidance from the SRE Workbook:

“Error budget burn should directly influence decision-making. When the budget is exhausted, the team must focus on remediation work rather than new features.”

Why the other options are incorrect:

B Reviewing the error budget’s realism can be done periodically, but it is not the immediate consequence of a breach.

C Extending the error budget invalidates its purpose and is discouraged.

D Ignoring the error budget contradicts the entire SRE model and Google’s official guidance.

Therefore, A is the only correct answer.

Comprehensive and Detailed Explanation From Exact Extract:

SRE emphasizes decision-making based on measured data, not intuition. The SRE Book explains: “Monitoring and SLOs provide an objective basis for decision-making, replacing guesswork with quantifiable data.” (SRE Book – SLOs & Monitoring). Data enables SRE teams to understand system behavior, validate assumptions, detect anomalies, and prioritize engineering work. The primary benefit is not merely collecting data, but analyzing and interpreting it to support decisions grounded in facts rather than opinion.

Option A accurately reflects this principle: data analysis and interpretation enable fact-based decisions, which is the core justification for SRE’s reliance on SLIs and observability signals.

Option B overstates by claiming data alone is always sufficient.

Option C refers to data mining, which is not a core SRE concept.

Option D is partially true but narrower than the SRE philosophy of data-driven operations.

Thus, A is the most accurate SRE-aligned answer.

Comprehensive and Detailed Explanation From Exact Extract:

The SRE Book clearly states: “A target of 100% availability is neither realistic nor economically viable at scale.” Complex distributed systems inherently experience failures, network issues, hardware faults, and dependency outages. SRE emphasizes embracing this reality through error budgets, which assume some failure and allow engineering resources to be used efficiently.

The primary reason not to set 100% availability is that it is impossible to achieve reliably and leads to wasted engineering effort. SRE states: “Chasing perfect reliability leads to dramatically increasing costs with diminishing returns.”

Option A captures this rationale precisely.

Options B, C, and D are secondary or incorrect interpretations and do not come directly from SRE principles.

Thus, A is the correct SRE-aligned answer.