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.
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.
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.
CI/CD Pipeline Concepts and Workflow
Conceptual understanding of how CI/CD pipelines work: continuous integration (running tests automatically on code commits), continuous deployment/delivery (automatically deploying to environments), pipeline stages (build, test, deploy), and tools that orchestrate these processes. Understand the benefits of CI/CD: faster feedback, reduced manual errors, faster release cycles.
Gitops and Infrastructure Governance at Scale
Applying Git based workflows and governance to infrastructure management across teams and clusters. Candidates should understand the Gitops principle of using Git as the source of truth, automated reconciliation controllers, pull request driven infrastructure changes, continuous delivery controllers, audit trails and immutable change histories, policy as code and guardrails to enforce compliance, role based access controls and secret management, multi cluster reconciliation and drift detection, self service platform patterns that preserve developer velocity, and trade offs between automation, governance, and security when operating infrastructure at scale.
Version Control for Infrastructure Code
Understand Git fundamentals applied to infrastructure - branching strategies, pull requests, code reviews for infrastructure changes. Know how infrastructure code differs from application code. Discuss infrastructure change management - how you'd safely deploy changes, rollback if needed. Understand the risks of infrastructure changes and how to mitigate them. Know about infrastructure documentation alongside code - README files, architecture diagrams, variable explanations. Practice discussing a git workflow for collaborative infrastructure development.
Software Installation and Deployment
Covers the end to end practices for installing, configuring, deploying, and maintaining application software across environments. Topics include installation procedures for complex applications, dependency management, package management, configuration file handling and templating, applying patches and updates, version control for releases, rolling and blue green deployments, deployment verification and testing, troubleshooting installation and runtime failures, compatibility and architecture considerations, and use of configuration management and deployment automation tools. Also includes best practices for managing software lifecycles, handling conflicts and version skew, and ensuring repeatable, auditable deployments across multiple operating systems and stacks.