Software Development Lifecycle and Tradeoffs Questions

Covers fundamental software development lifecycle concepts and the technical tradeoffs made during product development. Topics include the lifecycle phases of requirements gathering and analysis, design, implementation and development, testing, deployment, and maintenance, and awareness of different lifecycle models such as waterfall, agile and scrum, and iterative development. Also covers practical engineering techniques and tradeoffs such as feature flags, split testing, blue green deployments, canary releases, technical debt, and how decisions affect velocity quality and maintainability. Emphasis is on understanding how individual engineering work fits into the broader process and how to reason about tradeoffs between speed cost scalability and code quality.

EasyTechnical

0 practiced

Describe the minimal stages and responsibilities of a CI/CD pipeline for a microservice team that deploys to production frequently. Include build, unit test, integration test, artifact publish, deployment to an environment, smoke tests, and rollback. For each stage mention one gating mechanism (e.g., test thresholds, manual approval) that protects production quality.

HardTechnical

0 practiced

As a senior engineer you recommend delaying a high-profile release by two weeks to address discovered reliability and quality issues. Describe how you would present this decision to product and executive stakeholders: quantify the risks and benefits, propose mitigations and a revised timeline, communicate customer impact and contingency plans, and maintain team morale while meeting business goals.

HardTechnical

0 practiced

Propose how to integrate chaos engineering experiments into the release pipeline. Specify which experiments are appropriate for staging versus production, how to schedule experiments relative to deployments, how to limit blast radius and customer impact, and how to automatically correlate experiment results with SLOs to drive remediation or delayed rollouts.

MediumTechnical

0 practiced

Write a GitHub Actions workflow (YAML) that, on push to main: builds a Docker image, runs unit tests, pushes the image to a Docker registry with an 'rc' tag if tests pass, deploys that image to a staging Kubernetes cluster, runs smoke tests in staging, and then requires a manual approval step before deploying to production. Assume secrets DOCKER_USER, DOCKER_PASS, and KUBE_CONFIG are provided. Provide the key parts of the YAML (jobs, steps, conditions) and explain the artifact tagging strategy.

HardTechnical

0 practiced

Design a distributed tracing and sampling strategy for a polyglot microservices environment so tracing remains useful across releases while controlling storage costs. Cover context propagation standards, global vs per-service sampling rates, adaptive sampling for errors, trace retention policy, and how tracing signals should tie into release gate decisions.

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