DevOps & Release Engineering Topics
CI/CD pipeline design, build automation, deployment strategies, release management, artifact repositories, version control integration, and continuous delivery practices. Covers infrastructure automation for delivery workflows, release gates and approvals, multi-service orchestration, rollback strategies, and GitOps approaches. Distinct from Cloud & Infrastructure by focusing specifically on delivery automation and release processes rather than infrastructure platforms.
Software Development Lifecycle and Tradeoffs
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.
Production Deployments and Operations
Covers the end to end practices and trade offs involved in releasing, running, and operating software in production environments. Topics include deployment strategies such as blue green deployment, canary releases, and rolling updates, and how each approach affects reliability, rollback complexity, recovery time, and release velocity. Includes feature flagging and release gating to separate deployment from feature exposure. Addresses continuous integration and continuous deployment pipeline design, automated testing and validation in pipelines, artifact management, environment promotion, and release automation. Covers infrastructure as code and environment provisioning, containerization fundamentals including container images and runtimes, container registries, and orchestration fundamentals such as scheduling, health checks, autoscaling, service discovery, and the role of Kubernetes for scheduling and orchestration. Discusses database migration patterns for large data sets, strategies for online schema changes, and safe rollback techniques. Explores monitoring and observability including metrics, logs, and traces, distributed tracing and error tracking, performance monitoring, instrumentation strategies, and how to design systems for effective troubleshooting. Includes alerting strategy and runbook design, on call and incident response processes, postmortem practice, and how to set meaningful service level objectives and service level indicators to balance reliability and velocity. Covers scalability and high availability patterns, multi region deployment trade offs, cost versus reliability considerations, operational complexity versus operational velocity trade offs, security and compliance concerns in production, and debugging and troubleshooting practices for distributed systems with partial information. Candidates should be able to justify trade offs, explain when a simple deployment model is preferable to a more complex architecture, and give concrete examples of operational choices and their impact.
Deployment and Release Strategies
Covers end to end practices, automation, and architectural choices for delivering software safely and frequently. Candidates should understand and be able to compare deployment and upgrade approaches such as blue green deployment, canary releases, rolling updates, recreate deployments, shadow traffic and shadow deployments, and database migration techniques that avoid downtime. This topic includes progressive delivery and feature management practices such as feature flagging, staged rollouts by user cohort or region, staged traffic ramp up, and progressive delivery platforms. Candidates should be able to explain safety controls and verification gates including health checks, automated validation gates, smoke testing and staging verification, automated rollback criteria, and emergency rollback procedures. They should understand zero downtime patterns, rollback complexity and mechanisms, capacity and resource requirements, latency and consistency trade offs, and techniques to reduce blast radius and deployment risk. The topic also covers release engineering and operational practices such as release orchestration across environments, deployment automation and pipelines, continuous integration and continuous delivery practices, approvals and release management processes, incident response and communication during releases, chaos testing to validate resilience, and observability and monitoring to detect regressions and measure release health. Candidates should be able to describe metrics to measure deployment velocity and reliability such as deployment frequency, mean time to recovery, and change failure rate, and explain how to design frameworks, automation, and operational processes to enable frequent safe deployments at scale.
Continuous Integration and Delivery Pipeline Testing
Designing and operating automated test execution within continuous integration and continuous delivery pipelines. Candidates should demonstrate practical experience integrating unit tests, integration tests, end to end tests, and smoke tests into pipeline stages and selecting which tests run at various points in the pipeline. Key areas include test triggers and scheduling, selective and incremental test execution based on code changes, test parallelization and sharding to reduce wall clock time, test prioritization and risk based selection, management of compute resources for test runners, artifact and log handling, failure detection and triage, automatic reruns and quarantine strategies for flaky tests, and reporting and dashboards for visibility. Candidates should also be able to discuss gating deployments based on quality gates, feedback loops to developers, trade offs between test coverage and pipeline execution time, strategies for improving test reliability and mitigating flakiness, scaling test infrastructure with ephemeral runners and autoscaling, cost optimization for test execution, environment and test data provisioning strategies, and how testing supports shift left practices and faster safe delivery. Practical familiarity with pipeline tooling such as Jenkins, GitHub Actions, GitLab continuous integration, or cloud pipeline services and their features for parallel execution, artifact management, and gating is expected.
Continuous Integration and Delivery Pipelines
Design and implement continuous integration and continuous delivery pipelines that reliably build, test, validate, and deploy applications and infrastructure. Topics include pipeline as code practices, defining stages and triggers for builds and tests, automated testing strategies across unit, integration, smoke, and end to end tests, gating and environment promotion, branching and release strategies, artifact management and versioning, and deployment patterns such as rolling updates, blue green deployments, and canary releases. Candidates should be able to design rollback and recovery procedures, integrate infrastructure provisioning into pipelines, select and configure pipeline tooling such as Jenkins, GitHub Actions, GitLab CI, Azure Pipelines, or cloud vendor pipeline services, and reason about observability and reporting for pipeline health and test execution. Practical considerations include environment parity, pipeline security, secrets handling, pipeline as code best practices, and trade offs between speed and safety.
Feature Flagging and Rollout Strategy
Managing product evolution and cross platform launches using feature flags experiments and controlled rollouts. Topics include server side versus client side flag evaluation, experiment design and measurement, cohort targeting, canary and gradual rollouts, kill switches and rollback patterns, synchronization of flags across platforms for consistent user experience, monitoring rollout health and metrics, and operational practices to remove stale flags and migrate flags into permanent code paths.
Deployment Risk Management & Rollback Strategy
Discuss strategies for managing deployment risk: canary deployments (detect issues in subset), feature flags (quick disable without rollback), smoke testing post-deployment. Understand rollback procedures: full rollback (restore previous version), partial rollback (revert specific services). Know how to handle complications like database schema changes that can't simply rollback.