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').
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.
Edge Case Handling and Debugging
Covers the systematic identification, analysis, and mitigation of edge cases and failures across code and user flows. Topics include methodically enumerating boundary conditions and unusual inputs such as empty inputs, single elements, large inputs, duplicates, negative numbers, integer overflow, circular structures, and null values; writing defensive code with input validation, null checks, and guard clauses; designing and handling error states including network timeouts, permission denials, and form validation failures; creating clear actionable error messages and informative empty states for users; methodical debugging techniques to trace logic errors, reproduce failing cases, and fix root causes; and testing strategies to validate robustness before submission. Also includes communicating edge case reasoning to interviewers and demonstrating a structured troubleshooting process.
Testability and Testing Practices
Emphasizes designing code for testability and applying disciplined testing practices to ensure correctness and reduce regressions. Topics include writing modular code with clear seams for injection and mocking, unit tests and integration tests, test driven development, use of test doubles and mocking frameworks, distinguishing meaningful test coverage from superficial metrics, test independence and isolation, organizing and naming tests, test data management, reducing flakiness and enabling reliable parallel execution, scaling test frameworks and reporting, and integrating tests into continuous integration pipelines. Interviewers will probe how candidates make code testable, design meaningful test cases for edge conditions, and automate testing in the delivery flow.
Testing Debugging and Instrumentation
Testing strategies and observability practices for software and hardware systems, including embedded contexts. Topics include unit testing, integration testing, hardware in the loop testing, test harnesses, test automation, and trade offs when testing resource constrained systems. Instrumentation covers logging design, metrics, tracing, telemetry, and debug interfaces that make systems observable in development and production. Debugging techniques include use of debuggers, serial logging, signal capture, oscilloscope traces, remote debugging, and structured troubleshooting workflows. Discuss design decisions that balance visibility against performance and safety requirements, how to make systems testable and instrumented from the start, and how to interpret instrumentation to localize faults and validate fixes.
Advanced Debugging and Root Cause Analysis
Systematic approaches to complex debugging scenarios: intermittent failures, race conditions, environment-dependent issues, infrastructure problems. Using logs, metrics, and instrumentation effectively. Differentiating between automation issues, environment issues, and application defects. Experience with advanced debugging tools and techniques.
Site Reliability Engineering Fundamentals
Covers foundational site reliability engineering concepts that interviewers expect all candidates to understand. Topics include Service Level Objectives and Service Level Indicators and how they relate to availability targets and measurable system health, the notion of error budgets and trade offs between velocity and reliability, incident management including detection, escalation, on call rotations, and blameless postmortems, the importance of monitoring and observability for alerting and root cause analysis, basic deployment and rollback strategies, and an automation mindset to reduce toil. Candidates should be able to explain these ideas at a conceptual level, discuss how they influence decision making, and reference common practices used to improve reliability.
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.
Edge Case Identification and Testing
Focuses on systematically finding, reasoning about, and testing edge and corner cases to ensure the correctness and robustness of algorithms and code. Candidates should demonstrate how they clarify ambiguous requirements, enumerate problematic inputs such as empty or null values, single element and duplicate scenarios, negative and out of range values, off by one and boundary conditions, integer overflow and underflow, and very large inputs and scaling limits. Emphasize test driven thinking by mentally testing examples while coding, writing two to three concrete test cases before or after implementation, and creating unit and integration tests that exercise boundary conditions. Cover advanced test approaches when relevant such as property based testing and fuzz testing, techniques for reproducing and debugging edge case failures, and how optimizations or algorithmic changes preserve correctness. Interviewers look for a structured method to enumerate cases, prioritize based on likelihood and severity, and clearly communicate assumptions and test coverage.
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.