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').
On Call Operations and Reliability Engineering
Evaluate practices for sustainable on call operations and reliability engineering. Key areas include defining and measuring service level objectives and service level agreements, using error budget concepts to prioritize work, designing alerting and paging policies to reduce noise and fatigue, building and maintaining runbooks and on call playbooks, conducting blameless postmortems, automating repetitive operational tasks to reduce toil, and continuously improving reliability through capacity planning and redundancy. Candidates should demonstrate familiarity with incident roles, escalation paths, and how on call learnings translate into long term engineering changes.
Observability Fundamentals and Alerting
Core principles and practical techniques for observability including the three pillars of metrics logs and traces and how they complement each other for debugging and monitoring. Topics include instrumentation best practices structured logging and log aggregation, trace propagation and correlation identifiers, trace sampling and sampling strategies, metric types and cardinality tradeoffs, telemetry pipelines for collection storage and querying, time series databases and retention strategies, designing meaningful alerts and tuning alert signals to avoid alert fatigue, dashboard and visualization design for different audiences, integration of alerts with runbooks and escalation procedures, and common tools and standards such as OpenTelemetry and Jaeger. Interviewers assess the ability to choose what to instrument, design actionable alerting and escalation policies, define service level indicators and service level objectives, and use observability data for root cause analysis and reliability improvement.
Your QA Background and Experience Summary
Craft a clear, concise summary (2-3 minutes) of your QA experience covering: types of applications you've tested (web, mobile, etc.), testing methodologies you've used (manual, some automation), key tools you're familiar with (test management tools, bug tracking systems), and one notable achievement (e.g., 'I identified a critical data loss bug during regression testing that prevented a production outage').
Service Level Objectives and Reliability Metrics
Defining and operating to measurable reliability targets. Topics include selecting service level indicators that reflect user experience, defining service level objectives and translating them into service level agreements where required, calculating and monitoring error budgets, common reliability metrics such as uptime mean time between failures and mean time to recovery, aligning alerting and escalation thresholds to objectives, and using post incident analysis to close gaps. Candidates should be able to propose indicators for concrete services and explain how to measure and improve them.
Automation Testing and Validation
Covers testing and validation practices specifically for automation artifacts and automated workflows. Topics include validating automated solutions before production deployment, version control and code review for automation code and infrastructure definitions, monitoring automation jobs and handling failures gracefully, documenting automation for team learning, and managing technical debt in automation. Also covers the distinctions and trade offs between automation and manual testing, when to automate versus when to perform exploratory or manual testing, and strategies for continuously improving existing automation suites and identifying new opportunities for automation.
Quality and Reliability Focus
Describe your philosophy and concrete practices for building reliable, maintainable infrastructure. Topics include designing for fault tolerance and redundancy, defining service level objectives and service level agreements, establishing observability and alerting, automated testing and validation for changes, safe deployment patterns, incident detection and response, post incident analysis and continuous improvement, and strategies for managing technical debt while delivering business outcomes. Provide examples where prioritizing reliability improved long term operational cost or customer experience.
Attention to Detail and Quality
Covers the candidate's ability to perform careful, accurate, and consistent work while ensuring high quality outcomes and reliable completion of tasks. Includes detecting and correcting typographical errors, inconsistent terminology, mismatched cross references, and conflicting provisions; maintaining precise records and timestamps; preserving chain of custody in forensics; and preventing small errors that can cause large downstream consequences. Encompasses personal systems and team practices for quality control such as checklists, peer review, audits, standardized documentation, and automated or manual validation steps. Also covers follow through and reliability: tracking multiple deadlines and deliverables, ensuring commitments are completed thoroughly, escalating unresolved issues, and verifying that fixes and process changes are implemented. Interviewers assess concrete examples where attention to detail prevented problems, methods used to maintain accuracy under pressure, how the candidate balances speed with precision, and how they build processes that sustain consistent quality over time.
Observability for Reliability and Capacity Planning
Using observability to design for reliability, handle failure modes, and plan capacity. Topics include golden signals and reliability metrics, SLOs and error budgets, failure mode analysis, graceful degradation and resiliency patterns, circuit breakers, timeouts and bulkheads, forecasting capacity needs, and how monitoring informs scaling and resource planning. Discusses tradeoffs for operating at scale, cost controls on telemetry, alert fatigue mitigation, and strategies for cascading failure prevention and recovery.
Systematic Troubleshooting and Debugging
Covers structured methods for diagnosing and resolving software defects and technical problems at the code and system level. Candidates should demonstrate methodical debugging practices such as reading and reasoning about code, tracing execution paths, reproducing issues, collecting and interpreting logs metrics and error messages, forming and testing hypotheses, and iterating toward root cause. Topic includes use of diagnostic tools and commands, isolation strategies, instrumentation and logging best practices, regression testing and validation, trade offs between quick fixes and long term robust solutions, rollback and safe testing approaches, and clear documentation of investigative steps and outcomes.