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.
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.
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 Orchestration and Cloud Platforms
Design deployment architecture and orchestration for applications and infrastructure on cloud platforms. Topics include containerization and container orchestration systems, how orchestration and platform services affect deployment strategy, operational considerations for scaling and reliability, integration of monitoring and logging, and decision criteria for when orchestration adds value. Candidates should be able to describe deployment models for monoliths and microservices, patterns for scaling and resilience, and cloud native considerations such as managed services, auto scaling policies, and environment separation.
Deployment and Operations Fundamentals
Describe the end to end process for getting code from development into production and the operational practices that support it. Topics include version control and branching strategies automated build and test pipelines artifact promotion continuous integration and continuous delivery deployment strategies such as blue green and canary deployments feature flagging rollback procedures infrastructure as code containerization and orchestration secrets management and how deployment practices interact with monitoring and incident response. Candidates should be ready to discuss real examples and lessons learned from deployments and rollbacks.
Backend Infrastructure and Deployment
Covers designing, building, and operating the platform and deployment pipelines for backend services. Topics include cloud architecture with providers such as Amazon Web Services and Google Cloud Platform, containerization with Docker, orchestration with Kubernetes, continuous integration and continuous delivery pipelines, infrastructure as code for reproducible environments, deployment strategies such as rolling updates, blue green deployments and canary releases, autoscaling and load balancing, service mesh considerations, networking and security at the infrastructure layer, secrets and configuration management, cost optimization, and observability at the platform level. Candidates should describe trade offs and practical experience operating production infrastructure.