Free and Premium PeopleCert DevOps-SRE Dumps Questions Answers

Comprehensive and Detailed Explanation From Exact Extract:

The term “wisdom of production” refers to the insights gained from real systems running under actual production conditions. Only production environments exhibit real user behavior, real workloads, true performance characteristics, and authentic failure modes. This concept is rooted in the SRE philosophy that production is the ultimate source of truth for understanding system behavior.

From the SRE Workbook, Chapter “Monitoring”:

“Only production provides the full truth about how a system behaves under real workloads. Production is the ultimate source of wisdom about the system.”

This makes clear that wisdom gained from production is indispensable. Testing and staging environments cannot reproduce all real-world variables, usage patterns, and failure pathways.

Why the other options are incorrect:

A describes engineering approaches but does not define “wisdom of production.”

C is incorrect because staging environments do not provide production wisdom.

D relates to automation strategy, not production insights.

Thus, the accurate meaning of the term is B — The wisdom gained from something running in production.

Comprehensive and Detailed Explanation From Exact Extract:

Anti-fragility focuses on an organization’s ability to respond, adapt, learn, and recover from incidents. The most useful metrics relate to incident detection, response, reliability, and recovery. Deployment frequency, while important in DevOps and DORA metrics, does not directly measure anti-fragility.

From the SRE Workbook, Incident Response section:

“Improving antifragility requires better detection, better recovery mechanisms, and clear reliability goals.”

Key metrics relevant to anti-fragility:

MTTD (Mean Time To Detect) — quicker detection improves resilience

MTTR/RPO — recoverability measures

SLOs — define acceptable reliability thresholds and guide learning

Deployment frequency primarily measures delivery velocity, not resilience.

The Site Reliability Engineering Book emphasizes:

“Antifragility is improved by learning from incidents and strengthening recovery mechanisms rather than by increasing release cadence.”

Why other options are correct for anti-fragility:

A. Mean Time To Detect — critical for detecting failures quickly

B. SLOs — define boundaries for reliability and failure tolerance

D. Recovery Point Objective — measures potential loss during failures

Thus, C is the least useful metric for improving antifragility.

Comprehensive and Detailed Explanation From Exact Extract:

The SRE Book defines the Four Golden Signals of monitoring as Latency, Traffic, Errors, and Saturation. Specifically, it describes “Errors” as: “the rate of requests that fail, whether explicitly, implicitly, or by policy.” (SRE Book – Chapter: Monitoring Distributed Systems). This includes HTTP 5xx responses, timeouts, and requests served but not meeting success criteria.

This definition matches option B exactly.

Option A describes latency, not errors.

Option C describes traffic.

Option D describes saturation (resource usage).

Therefore, B is the correct and SRE-accurate description of the golden signal for errors.

Comprehensive and Detailed Explanation From Exact Extract:

Achieving high availability in SRE practice is driven by accurate measurement of what matters and fast detection and correction of issues. According to Google’s Site Reliability Engineering Book, measurement of critical user-facing signals is foundational: “SLIs must capture the aspects of the service that are most critical to users and must be measured with high accuracy.” (SRE Book – Chapter: Service Level Objectives). Without measuring the critical aspects of a service—latency, errors, availability, and quality—teams cannot make informed decisions or detect degradation effectively.

The SRE book also emphasizes reducing MTTR (Mean Time to Repair) and tightening the feedback loop between detection and correction. Google states: “Reducing the time between detection and mitigation is one of the most effective levers for improving availability.” (SRE Book – Chapters on Incident Response & Monitoring). Rapid identification and resolution directly improve a system’s availability and resilience.

Option D (1 and 4) is the only choice that correctly reflects SRE principles.

Measuring critical aspects → essential for correct SLO/SLI alignment

Maintaining a short interval between detection and correction → drives higher availability

Options including staff performance measurement or generic development relationships are not mentioned as availability-driving factors in the SRE literature.

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.

Comprehensive and Detailed Explanation From Exact Extract:

Fixed error budgets are preferred in SRE because they encourage smaller, safer, and more predictable releases, which inherently reduces risk. A fixed budget forces the team to consistently evaluate how much reliability they can afford to trade for delivery speed each month or quarter.

From the Site Reliability Engineering Book, Chapter “Service Level Objectives”:

“Error budgets allow teams to make controlled decisions about the risk they take on. A fixed budget naturally encourages teams to release in smaller batches, which reduces the overall risk and impact of a failure.”

Similarly, the SRE Workbook states:

“When teams work within a fixed error budget, they tend to push changes in smaller increments to avoid burning the budget too quickly.”

Why the other options are incorrect:

A Fixed budgets reduce toil by reducing firefighting, not increase it.

C Fixed budgets can be exceeded; this is not a reason they are beneficial.

D Error budgets do not predict outages; they measure tolerated unreliability.

Thus, the correct and SRE-supported answer is B.

Comprehensive and Detailed Explanation From Exact Extract:

Simplicity is a core SRE design principle. Google states: “Small, frequent, automated changes reduce risk and improve system stability.” (SRE Book – Release Engineering). Automating continuous, small deployments creates a simple and repeatable pipeline that increases agility while maintaining reliability. This approach aligns with both DevOps and SRE practices: reducing deployment complexity, lowering blast radius, and supporting rapid iteration.

Option B best reflects this philosophy: automated, continuous small deployments provide simplicity, stability, and agility simultaneously.

Option A improves process clarity but does not directly affect agility.

Option C is beneficial but broader and not specific to simplicity.

Option D focuses on control rather than agility.

Thus, B is correct.

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 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.

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:

Embracing failure—through practices such as blameless postmortems, chaos engineering, and proactive detection—enables organizations to improve their incident response performance. This directly improves:

MTTD (Mean Time to Detect)

MTTR (Mean Time to Recover)

The Site Reliability Engineering Book, chapter “Postmortem Culture,” states:

“By examining failures without blame and learning from them, organizations improve their ability to detect issues faster and recover more quickly.”

Similarly, in the SRE Workbook, section on incident response:

“Learning from incidents is essential to reducing time to detection and time to mitigation.”

Why the other options are incorrect:

A MTBSI (Mean Time Between System Incidents) is influenced by architecture and testing, not directly by embracing failure.

B These are DORA metrics — important, but not primarily tied to failure-embracing practices.

C Too vague and not a standard SRE metric pair.

Thus, D is the correct answer.

Comprehensive and Detailed Explanation From Exact Extract:

SRE defines effective monitoring as comprehensive observability across all layers of a system, including latency, traffic, errors, saturation, dependencies, and infrastructure. The SRE Book states: “Monitoring must offer insight across all system components, enabling teams to rapidly detect and diagnose issues.” (SRE Book – Monitoring Distributed Systems). Observability instrumentation (logs, metrics, traces) provides the necessary depth for reliable digital experience monitoring.

Option B captures this exactly: broad observability across all components and layers.

Option A rejects modern observability practices—contradicting SRE guidance.

Option C is too narrow (network-only).

Option D focuses only on advanced technologies, not comprehensive coverage.

Thus, B is the best answer.

Comprehensive and Detailed Explanation From Exact Extract:

Google defines SRE as “what happens when you ask a software engineer to design an operations function.” (SRE Book – Introduction). The core engineering approach in SRE focuses on:

Eliminating toil

Building scalable systems

Applying software engineering to operational challenges

Learning from previous solutions and patterns

The SRE Book emphasizes: “SREs focus on designing and engineering solutions that reduce manual operations and scale service delivery.” (Chapter: Eliminating Toil). This aligns directly with Option B: designing a solution to eliminate toil and scale service delivery, informed by prior successful engineering patterns.

Option A focuses only on automating a single tuning activity—not holistic engineering.

Option C describes deployment, not engineering approach to operations.

Option D is about incident response, not engineering strategy.

Thus, B is the best representation of SRE’s engineering approach.

Comprehensive and Detailed Explanation From Exact Extract:

Traditional IT escalation paths—before modern SRE practices—were generally based on hierarchical or functional structures. The SRE Workbook explains that SRE aims to “replace rigid hierarchical escalation paths with structured incident roles and clear authority during incidents.” (SRE Workbook – Incident Management). These older models include:

Hierarchical escalation: issues are escalated to higher managerial or senior technical tiers.

Functional escalation: issues are escalated across functional lines depending on expertise (network team, DBAs, sysadmins, etc.).

Both models are referenced throughout reliability engineering literature as “traditional escalation paths,” which SRE incident management explicitly avoids by instead using role-based escalation (IC, Communications Lead, Ops Lead, etc.).

Options 3 and 4 (Cyclical and Logical) are not recognized escalation patterns in ITSM or SRE literature.

Thus, the answer is A (1 and 2).

Comprehensive and Detailed Explanation From Exact Extract:

Customer Reliability Engineering (CRE) is described in Google's SRE literature as an extension of SRE practices outward to customers who run workloads on cloud platforms. The SRE Book and the SRE Workbook state: “CRE is the practice of sharing SRE principles with customers, working closely with their operations teams, and establishing shared responsibility for reliability.” (SRE Workbook – Chapter: Customer Reliability Engineering). A CRE team collaborates directly with customer engineering and operations teams to identify reliability risks, review architectures, and co-manage SLOs, but does not redesign cloud services or build new features.

Option D matches the exact intention: CRE integrates with the customer’s operations team to share reliability responsibilities, applying SRE methods to customer systems and ensuring both customer and provider work jointly on reliability goals.

Option A is incorrect—CRE does not redesign cloud services.

Option B misinterprets CRE as improving the provider’s internal systems.

Option C incorrectly focuses on feature shipping; CRE is about reliability guidance, not feature delivery.

Thus, D is the correct and SRE-authentic answer.

Comprehensive and Detailed Explanation From Exact Extract:

A Service Level Indicator (SLI) is a measurement of some aspect of reliability (e.g., latency, availability, quality). One of its defining characteristics is that it must be measured over a specific time window. Without a time horizon, the SLI has no actionable meaning.

From the Site Reliability Engineering Book, Chapter “Service Level Indicators”:

“An SLI is a quantitative measure of some aspect of the level of service that is provided. SLIs are evaluated over a specific period of time in order to understand reliability as experienced by the user.”

The SRE Workbook further states:

“Every SLI must define a measurement window. Without a time horizon, the indicator cannot be used to calculate SLO compliance.”

Why the other options are incorrect:

A SLIs do not need to appear in an SLA; SLAs are external contracts, SLOs/SLIs are internal engineering tools.

B SLIs may include client-side, server-side, or network metrics depending on what reflects user experience.

D SLI agreement is not defined by SRE vs. Agile teams; it is defined by business and user need.

Thus, the correct answer is C.

Comprehensive and Detailed Explanation From Exact Extract:

The primary difference between SRE and DevOps lies in their implementation focus and origins, though they share similar objectives. According to Google’s official SRE documentation:

“SRE can be seen as a specific implementation of DevOps with some idiosyncratic extensions.”

— Site Reliability Engineering Book, Chapter: What is Site Reliability Engineering?

While DevOps is a broad cultural and organizational philosophy aimed at closing the gap between development and operations through collaboration and automation, SRE provides a concrete, engineering-driven approach to achieving those goals — particularly through practices like error budgets, SLIs/SLOs, toil reduction, and incident response.

SRE focuses heavily on the post-production lifecycle — including reliability, monitoring, capacity planning, and incident response — whereas DevOps includes these concerns but emphasizes the entire software delivery lifecycle. Hence, Option A is the correct and most accurate answer.

Options B and C are incorrect:

B wrongly implies a division of roles (DevOps = developers, SRE = infrastructure), which is not how these frameworks operate.

C misrepresents SRE — it does not build silos but instead emphasizes shared responsibility and transparency in production systems.

D is incorrect because, while aligned, SRE and DevOps are not identical.

Comprehensive and Detailed Explanation From Exact Extract:

In a safety culture, SRE emphasizes psychological safety so engineers can work effectively in production without fear of blame. However, safety never removes accountability. Engineers must take responsibility for their actions, decisions, and assumptions, particularly during incidents.

The Site Reliability Engineering Book, Chapter “Postmortem Culture,” states:

“Blamelessness does not eliminate accountability. Individuals must still explain the context, assumptions, and reasoning behind their decisions so that the organization can learn.”

Google stresses that:

Engineers must feel safe to act and report issues

Engineers must remain responsible and accountable

Accountability enables learning, not punishment

Why other options are incorrect:

A Sharing incidents on social media violates confidentiality

C Blameless postmortems are required, not skipped

D Avoiding on-call is contrary to SRE responsibilities

Thus, B is correct.

Comprehensive and Detailed Explanation From Exact Extract:

SLIs must measure user experience, and sometimes server-side metrics alone do not show the full picture. Client-side data may reveal issues such as:

Slow networks

Browser rendering delays

Mobile device limitations

CDN performance issues

Last-mile latency

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

“Server-side metrics do not always fully capture the user experience. In many cases, client-side measurements are required to understand the actual reliability delivered to users.”

The SRE Workbook reinforces:

“Some SLIs require client instrumentation because user-visible performance problems may not be observable from backend systems alone.”

Why the other options are incorrect:

B SLA negotiation has nothing to do with SLI selection.

C Automation engineering is unrelated to client-side measurement needs.

D Achievability of SLOs does not determine whether client-side data is needed; accuracy of user-experience measurement does.

Thus, the correct answer is A.

Comprehensive and Detailed Explanation From Exact Extract:

Burning the error budget to zero — strategically, not accidentally — helps ensure the correct balance between release velocity and system stability, which is the fundamental purpose of error budgets. Error budgets exist to encourage a healthy level of risk-taking up to the point where user experience is not impacted.

From the Site Reliability Engineering Book, SLO chapter:

“Error budgets provide a mechanism for balancing innovation and reliability by allowing measured risk-taking while ensuring user expectations are met.”

The SRE Workbook adds:

“Teams should aim to use their full error budget. Not using it implies missed opportunities to deliver features or improvements.”

This means that strategically burning the error budget to zero ensures:

Teams are shipping value at maximum safe velocity

Reliability goals are still respected

Risk is managed and intentional

Why other options are incorrect:

B Capacity measurement is unrelated to error budget consumption.

C Error budgets should not be continually revised unless business needs change.

D Conversations with partners may occur, but this is not the primary benefit.

Thus, the correct answer is A.

Comprehensive and Detailed Explanation From Exact Extract:

High turnover in IT operations roles is often driven by a combination of factors, not just one. The Google SRE Book, Chapter “Eliminating Toil,” outlines that excessive toil, unpredictable work, and overload contribute to burnout and churn:

“Excessive operational workload and interrupt-driven work lead to burnout and high attrition among engineering and operational staff.”

The SRE Workbook adds:

“Teams overwhelmed with toil struggle to innovate, automate, or develop new skills, creating frustration and increasing turnover.”

Each option listed represents a recognized driver of burnout in SRE and operations environments:

Overload and disruptive work patterns are known contributors to burnout.

Lack of time for skills development demotivates engineers and prevents career growth.

Backlog-driven cultures force teams into reactive rather than proactive work.

The combination of these factors matches common causes of attrition in operations teams. Therefore, all of the above is the correct answer.

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:

Application Performance Management (APM) refers to a set of tools and practices used to monitor and manage the performance, behavior, and availability of software applications. Although APM is not defined exclusively in the Google SRE Book, it is described within the broader context of monitoring and observability.

In the SRE Workbook, under Monitoring:

“Application monitoring tools provide insights into the performance, latency, availability, and behavior of applications to help engineering teams maintain reliability.”

Industry-standard APM frameworks (including Google Cloud Operations Suite, formerly Stackdriver) define APM as:

“The monitoring and management of application performance and availability.”

Why the other options are incorrect:

A describes telemetry, not APM.

C describes system monitoring (infrastructure), not application performance monitoring.

D refers to communication of metrics, not the monitoring of application performance.

Therefore, B is the correct definition.

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.