Testing, Quality & Reliability Topics
Quality assurance, testing methodologies, test automation, and reliability engineering. Includes QA frameworks, accessibility testing, quality metrics, and incident response from a reliability/engineering perspective. Covers testing strategies, risk-based testing, test case development, UAT, and quality transformations. Excludes operational incident management at scale (see 'Enterprise Operations & Incident Management').
Service Reliability and Technical Debt
Covers principles and practices for ensuring system reliability while balancing feature delivery and long term code health. Candidates should understand reliability targets and how to express them, such as uptime goals like 99.9 percent or 99.99 percent, and how to define and measure service level indicators and service level objectives. Explain the concept of error budgets, how to allocate and consume them, and how they drive decisions about releases versus reliability work. Include monitoring and observability strategies for detecting and diagnosing reliability issues, incident response and postmortem practices, and metrics to track system health. Discuss identification and categorization of technical debt, methods to prioritize paying down debt versus shipping new features, cost of delay and business impact communication, and processes for tracking and reducing technical debt over time. Show how you would collaborate with product managers, engineering teams, and stakeholders to trade off feature velocity and stability, set policies for error budget usage, and create roadmaps that include reliability improvements.
Reliability, SLO, and Error Budget Implications
Understand how architectural decisions affect reliability. For example, using a single database vs. replicated databases, synchronous vs. asynchronous processing. Discuss SLOs (e.g., 99.9% uptime) and what that means architecturally. Understand error budgets and how they influence rollout strategies or feature prioritization.
Reliability and Operational Excellence
Covers design and operational practices for building and running reliable software systems and for achieving operational maturity. Topics include defining, measuring, and using Service Level Objectives, Service Level Indicators, and Service Level Agreements; establishing error budget policies and reliability governance; measuring incident impact and using error budgets to prioritize work. Also includes architectural and operational techniques such as redundancy, failover, graceful degradation, disaster recovery, capacity planning, resilience patterns, and technical debt management to improve availability at scale. Operational practices covered include observability, monitoring, alerting, runbooks, incident response and post incident analysis, release gating, and reliability driven prioritization. Proactive resilience practices such as fault injection and chaos engineering, as well as trade offs between reliability, cost, and development velocity and scaling reliability practices across teams and organizations, are included to capture both hands on and senior level discussions.
Engineering Quality and Standards
Covers the practices, processes, leadership actions, and cultural changes used to ensure high technical quality, reliable delivery, and continuous improvement across engineering organizations. Topics include establishing and evolving technical standards and best practices, code quality and maintainability, testing strategies from unit to end to end, static analysis and linters, code review policies and culture, continuous integration and continuous delivery pipelines, deployment and release hygiene, monitoring and observability, operational run books and reliability practices, incident management and postmortem learning, architectural and design guidelines for maintainability, documentation, and security and compliance practices. Also includes governance and adoption: how to define standards, roll them out across distributed teams, measure effectiveness with quality metrics, quality gates, objectives and key results, and key performance indicators, balance feature velocity with technical debt, and enforce accountability through metrics, audits, corrective actions, and decision frameworks. Candidates should be prepared to describe concrete processes, tooling, automation, trade offs they considered, examples where they raised standards or reduced defects, how they measured impact, and how they sustained improvements while aligning quality with business goals.
Service Level Objectives and Error Budgets
Comprehensive coverage of Service Level Indicators, Service Level Objectives, Service Level Agreements, and error budgets, covering both conceptual foundations and practical operationalization. Candidates should be able to define each construct, explain how to select and instrument meaningful indicators such as availability, latency percentiles, throughput, and error rate, and choose appropriate measurement windows and targets. Expect to compute error budgets from objective targets, convert objective percentages into allowed downtime or error time over observation windows, calculate burn and burn rate, and describe how error budget policies gate releases, influence rollback and mitigation decisions, and drive prioritization between feature work and reliability work. Topics include monitoring and alerting design aligned to objectives, distinguishing noisy symptomatic alerts from objective driven alerts, dashboarding and real time tracking, observability and instrumentation considerations, progressive delivery patterns such as canary deployments and feature flags to protect an error budget, and on call and incident response practices including blameless post incident review and SLO adjustments. At senior levels be prepared to discuss trade offs between reliability and velocity, aligning infrastructure investment with objective targets, governance and policy across multiple teams and dependent services, handling seasonality and edge cases, and metrics design to avoid gaming or misinterpretation while translating objectives into actionable runbooks and organizational policies.