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').
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').
Testing Strategy and Test Pyramid Approach
Understand test pyramid (unit, integration, E2E), testing types (functional, performance, security, usability, compliance), optimal ratios, and how to balance coverage vs. effort. Know when to prioritize manual vs. automated testing and justify decisions based on risk and ROI.
SLIs, SLOs, SLAs Definition and Implementation
Understanding Service Level Indicators (SLIs - what you measure), Service Level Objectives (SLOs - targets you set), and Service Level Agreements (SLAs - commitments to customers). At senior level, design SLOs that align with business requirements and user expectations. Choose meaningful SLIs like availability, latency, error rate. Understand how SLOs drive reliability decisions, allocation of engineering effort, and error budgets. Design monitoring to track SLI achievement. Address multi-tiered SLOs for different service tiers or customer segments.
Metrics Analysis and Monitoring Fundamentals
Fundamental concepts for metrics, basic monitoring, and interpreting telemetry. Includes types of metrics to track (system, application, business), metric collection and aggregation basics, common analysis frameworks and methods such as RED and USE, metric cardinality and retention tradeoffs, anomaly detection approaches, and how to read dashboards and alerts to triage issues. Emphasis is on the practical skills to analyze signals and correlate metrics with logs and traces.
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.
Platform Reliability and Operational Excellence
Ensuring that deployment platforms are reliable, observable, and maintainable while minimizing operational cost. Coverage includes defining service level indicators and service level objectives, monitoring and alerting strategies, dashboards and health signals, incident runbooks and automation, capacity planning and headroom, safe upgrade and rollout strategies such as canary and blue green style techniques, resilience testing and chaos engineering, toil reduction and automation prioritization, continuous improvement processes, and measuring the operational impact of platform work. Candidates should be able to describe how they instrument platform health and how they reduce operational burden while preserving safety and velocity.
Logging and Observability
Cover how to use logs, metrics, and traces to detect and diagnose system problems and to measure system health. Topics include structured logging best practices, centralized log aggregation and querying, time series metrics and alerting, dashboard design, correlating events across services, sampling and retention strategies, and turning telemetry into actionable incident detection and performance insights.
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.