Performance & Stability Interview Questions

Combine unit, integration, and E2E tests based on risk. Puppeteer excels at certain layers—explain what you automate with it for Performance & Stability and what you still verify manually or in staging.

Prefer data-testid, roles, or accessible labels over brittle CSS paths. Stable selectors reduce flaky tests when UI changes and make Performance & Stability suites maintainable across refactors.

Eliminate arbitrary sleeps, wait for explicit conditions, isolate test data, and run tests in parallel only when independent. Retry only as a last resort—fix root causes of Performance & Stability instability.

Reports should show pass/fail, duration, screenshots or traces on failure, and trends over time. Tie Performance & Stability scenarios to user journeys or requirements so stakeholders trust the signal.

Run tests on pull requests, cache dependencies, parallelize jobs, and fail builds on regressions. Store artifacts (videos, logs) for debugging failed Performance & Stability cases without reproducing locally.

Mock external APIs for speed and determinism; use real services in integration environments for fidelity. Document the trade-off and keep Performance & Stability tests fast enough for developer workflow.

Many unit tests, fewer integration tests, minimal E2E. Place Performance & Stability tests at the layer where they give maximum confidence per maintenance cost—avoid duplicating the same scenario at every layer.

Use the official Puppeteer docs for Performance & Stability, language or framework references, and reputable community guides. Bookmark release notes and migration guides when upgrading versions, since Performance & Stability behavior can change between releases.

Copying snippets without understanding why Performance & Stability works leads to fragile code. Beginners often skip error handling, tests, or edge cases. Slow down, trace execution step by step, and validate assumptions with small experiments.

Start with the problem Performance & Stability solves, show a minimal working example, and list the team conventions around it. Point them at official docs and one trusted internal example rather than random snippets.

Performance & Stability shows up often in production Puppeteer work—misunderstanding it leads to bugs, performance issues, or security gaps. Interviewers want clear explanations plus practical judgment.

Describe scaffolding a feature, configuring defaults, or validating input where Performance & Stability is required. Call out what goes wrong if the team skips conventions around it.

Read the official overview, run a minimal sandbox, learn key terms and common errors, then expand with a small project. Hands-on practice beats memorizing Performance & Stability definitions.

Follow team conventions, split concerns into testable units, handle edge cases, and document assumptions. Review similar modules in the codebase, add observability, and ship incrementally with feature flags if Performance & Stability is risky.

Map the Performance & Stability attack surface (injection, broken auth, data exposure, DoS). Layer defenses—validation, rate limits, least privilege, encryption, and regular audits.

Measure first, then improve the hottest Performance & Stability paths with batching, connection pooling, async I/O, better algorithms, or sharding. Re-check p95/p99 after each change and skip micro-tweaks without clear gains.

Use expand/contract or strangler patterns, dual-write/dual-read where needed, feature flags, and rollback plans. Validate parity with shadow traffic before decommissioning the old Performance & Stability path.

State whether Performance & Stability needs strong consistency or can tolerate eventual consistency. Discuss partitions, quorum, conflict resolution, and user-visible anomalies during failures.

Pick availability and latency indicators, set achievable objectives, watch burn rate, and decide when reliability work outranks features. Tie those budgets to release decisions for Performance & Stability.

Define clear ownership boundaries for Performance & Stability, failure domains, caching, and observability. Plan capacity, multi-region needs if relevant, and explicit trade-offs between consistency, latency, and cost.