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.
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.
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.
Test Environment and Data Management
Practices and strategies for provisioning, configuring, operating, and maintaining test environments and the test data they rely on to enable reliable, repeatable, and scalable testing across development and delivery pipelines. Topics include environment tiering and parity with production; reproducible declarative provisioning using infrastructure as code; containerization and virtualization; ephemeral, persistent, feature, and shared environment patterns; orchestration and dependency management for services, networks, and databases; configuration and secret management; dependency and version control; and techniques to prevent environment drift. For test data the scope includes synthetic data generation, anonymization and data masking, database snapshots and seeding, data isolation and cleanup for parallel runs, handling stateful systems, data versioning and migration, and strategies to scale test data. Also covers service virtualization and test doubles for unavailable dependencies, automation of environment lifecycle including creation and teardown, resource allocation and cost management for ephemeral resources, observability and logging for troubleshooting environment related failures, access controls and data privacy, integration with continuous integration and continuous delivery pipelines, and coordination with platform and operations teams.
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.
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.
Test Pipeline Orchestration and Gating
Automated orchestration of CI/CD test pipelines: staged test suites (smoke/integration/acceptance), test dependency gating, conditional/change-impact test execution, and integration of test orchestration with deployment pipelines.
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.
Kubernetes Deployment and Gitops
Focuses on implementing safe deployment patterns specifically in Kubernetes and on GitOps practices for declarative, version controlled operations. Topics include Kubernetes native rollout models such as rolling updates, canary releases, and blue green deployments; pod lifecycle considerations, readiness and liveness probes, resource limits, and health checks; implementing automated continuous deployment pipelines that target Kubernetes clusters; and GitOps principles including declarative manifests, version control as the source of truth, automated reconciliation, and observable drift management. Candidates should also know common GitOps tools such as Argo CD and Flux, manifest management approaches like Helm and Kustomize, and operational concerns such as rollback procedures, security and access controls, and integration with monitoring.