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.
Python Scripting for Infrastructure Automation
Applied Python skills for building reusable, production grade automation for infrastructure and operations. Topics include designing modular automation code and libraries, using relevant third party libraries for systems administration and remote management, invoking and controlling subprocesses, interacting with application programming interfaces and cloud platform endpoints, robust error handling and structured logging, automated testing of scripts and modules, packaging and distributing tools for reuse, secure credential management, integration with configuration management and orchestration tooling, and designing multi step workflows and idempotent operations. Candidates should demonstrate experience with writing maintainable automation, reasoning about failure modes, and selecting appropriate abstractions and libraries for operational tasks.
Release Engineering and Change Management
Design and operate deployment and release processes that minimize user impact while enabling rapid change. Topics include deployment strategies such as blue green, canary, and rolling updates, feature flagging and progressive delivery, rollback and remediation strategies, database schema migration techniques that avoid downtime, release gating, approval workflows and auditability, disaster recovery and rollback planning, and instrumentation for release observability and post deployment validation. Candidates should also understand change management practices, incident response during releases, minimizing change windows, and cross team coordination between engineering, product, and operations to manage release risk and stakeholder communication.
Automation and Scripting
Covers practical and architectural skills for writing production safe automation and operational scripts as well as building reusable automation systems. Topics include designing idempotent automation, safe retries, robust error handling, structured logging and observability, argument parsing and command line interface design, configuration management, and secure credential handling. Emphasis on testing and validation of scripts and automation code, packaging, documentation, deployment, and maintainability so automation can be operated by other team members. Includes integration with schedulers such as cron and systemd timers, continuous integration and continuous delivery pipelines, orchestration and configuration management systems, and common operational patterns such as log processing, backups, polling, multi step orchestration, provisioning, configuration changes, and routine maintenance. Also assesses language selection and trade offs among Python, Go, Bash and other tooling, concurrency and performance considerations, and at senior levels the design and architecture of reusable automation frameworks and strategies for scaling automation to reduce toil.
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.
Configuration Management and Operational Rigor
Practices and processes for managing system and network configurations with operational discipline. Topics include version control for configurations, secure configuration backups, automated testing of configuration changes, rollback and recovery mechanisms, detecting and remediating configuration drift, documentation and runbook development, change windows and impact assessment, stakeholder communication for changes, and balancing operational rigor with deployment velocity. Interviewers may probe tooling, automation strategies, validation and testing approaches, and how the candidate ensures repeatability, auditability, and safe change promotion across environments.
Container Image Management and Registry
Focuses on the lifecycle of container images from build to runtime. Includes building reproducible images, multi stage builds, tagging strategies and semantic versioning, minimizing image size and attack surface, running as non root, and use of minimal base images. Covers pushing to and pulling from registries including public and private registries, authentication and access control, registry lifecycle policies, image caching and garbage collection, image signing and provenance, vulnerability scanning and remediation processes, integration with CI CD pipelines, and operational considerations such as storage costs, replication and geo distribution, and registry high availability.
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.
Pipeline Integration and Infrastructure Automation
Integrate pipelines with container orchestration and infrastructure automation to enable repeatable and reliable deployments. Topics include pipeline triggers and hooks, container image build and registry strategies, environment promotion and image tagging strategies, integrating infrastructure as code into pipeline workflows, interacting with orchestration platforms such as Kubernetes for deploying services, and managing multiple environments and pipeline dependencies. Also cover secrets and configuration management in pipelines, deployment automation patterns, health checks and rollout validation, and operational practices such as deployment observability and collaboration between developers and platform teams.
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.