Cloud & Infrastructure Topics
Cloud platform services, infrastructure architecture, Infrastructure as Code, environment provisioning, and infrastructure operations. Covers cloud service selection, infrastructure provisioning patterns, container orchestration (Kubernetes), multi-cloud and hybrid architectures, infrastructure cost optimization, and cloud platform operations. For CI/CD pipeline and deployment automation, see DevOps & Release Engineering. For cloud security implementation, see Security Engineering & Operations. For data infrastructure design, see Data Engineering & Analytics Infrastructure.
Containerization and Virtualization Trade Offs
Examines trade offs between containers and virtual machines and the complexity of orchestrated environments. Topics include hypervisor and virtual machine basics, container isolation and resource models, performance and overhead comparisons, security and attack surface differences, when to prefer virtual machines versus containers, single container versus orchestrated multi container setups, operational complexity versus benefits, and criteria for selecting the appropriate platform at different scales.
Scalability and Systems Resource Management
Design and operational practices for managing compute and platform resources as systems scale. Covers autoscaling, resource pooling, orchestration, cost trade offs between always on versus on demand provisioning, and architectural choices that affect resource utilization and performance. Candidates should be prepared to discuss capacity planning for infrastructure, metrics and alerts for autoscaling, and cost versus performance decisions for high availability systems.
Cloud Infrastructure Knowledge (AWS/GCP/Azure)
Have working knowledge of at least one major cloud platform: common services (EC2/Compute Engine, RDS/Cloud SQL, S3/Cloud Storage, Load Balancers, VPCs, networking), typical failure modes, and how to troubleshoot within that platform. Understand concepts like availability zones, regions, and cross-region failover.
Cloud Migration Strategy and Cutover
Plan end to end migration using common patterns such as rehost replatform refactor and repurchase and map those choices to workload characteristics. Define sequencing and phase gates plan pilot migrations and develop detailed cutover playbooks that include data replication validation reconciliation and rollback triggers. Address zero downtime techniques such as parallel running incremental synchronization canary deployments and feature gates plus testing strategies metrics to detect regressions and run books for rollback and post cutover verification.
Kubernetes and Container Orchestration Fundamentals
Core knowledge of container orchestration with a focus on Kubernetes fundamentals and everyday operations. Candidates should understand the role of orchestration and why it is used at scale, and be familiar with core Kubernetes objects including pods as the smallest deployable unit, deployments and replica management, replica sets, services for inter pod communication and service discovery, config maps and secrets for configuration and secret management, and the basic lifecycle of containerized applications. Coverage includes deployment and scaling workflows, rolling update and rollout strategies including rollbacks, common deployment patterns such as blue green and canary, and basic health checks and probe concepts. Practical operational skills include common kubectl commands for deploying, inspecting, scaling and debugging applications, reading pod logs and events, describing resources, port forwarding, and diagnosing common failure modes. Candidates should also understand high level trade offs between using managed cloud provider Kubernetes services and operating self managed clusters including operational overhead, upgrades, cost, and reliability considerations. The scope focuses on fundamentals and day to day operations and excludes advanced cluster administration topics such as custom operators, admission controllers, control plane internals, and deep platform level configuration.
Infrastructure as Code Design and Modularity
Deep expertise with Terraform, CloudFormation, or Pulumi at scale. Module design patterns, code organization across monorepos vs polyrepos, state management strategies, remote backends, workspaces, and dependency management. Version control strategies for infrastructure, handling breaking changes, and managing IaC across teams. DRY principles and reducing repetition across infrastructure definitions.
Infrastructure Automation and Provisioning
Covers designing, implementing, and operating automated infrastructure provisioning and configuration using Infrastructure as Code practices and complementary automation patterns. Candidates should be able to select and author declarative infrastructure definitions with tools such as Terraform, CloudFormation, and Azure Resource Manager templates, and discuss configuration management tools such as Ansible, Puppet, or Chef. Core skills include modular and reusable code organization for multiple environments, variable and output management, remote state management and locking, idempotency and atomicity of operations, and version control integration for infrastructure artifacts. Candidates should understand testing and validation practices including linting, plan or dry run validation, unit and integration testing of infrastructure changes, and drift detection and remediation. The topic includes strategies for safe changes and rollbacks, change coordination, error handling and recovery, and deployment patterns such as canary and blue green where applicable. It also encompasses automation and orchestration patterns, immutable infrastructure and self healing practices, autoscaling and scaling policies, automated patching and updates, secrets handling patterns using secret managers, and integrating observability and monitoring into automated workflows. Finally, candidates should be able to reason about trade offs between imperative and declarative approaches, scaling Infrastructure as Code across large projects and teams, and security and compliance considerations for automated provisioning.
Cloud Platform Experience
Personal account of hands on experience using public cloud providers and the concrete results delivered. Candidates should describe specific services and patterns they used for compute, storage, networking, managed databases, serverless and eventing, and explain their role in architecture decisions, deployments, automation and infrastructure as code practices, continuous integration and continuous delivery pipelines, container orchestration, scaling and performance tuning, monitoring and incident response, and cost management. Interviewees should quantify outcomes when possible with metrics such as latency reduction, cost savings, availability improvements or deployment frequency and note any formal training or certifications. This topic evaluates depth of practical experience, ownership, and the ability to operate and improve cloud systems in production.
Infrastructure as Code and Configuration Management
Infrastructure as Code and Configuration Management covers designing, implementing, and operating infrastructure defined as code and the practices that keep that infrastructure consistent and auditable. Topics include Infrastructure as Code principles and patterns, declarative versus imperative approaches, idempotency, state management, module and template design for reusable infrastructure, version control integration, testing and validation of infrastructure code, drift detection and remediation, safe rollout and rollback strategies, policy as code and Git operations for infrastructure, and how to scan and remediate infrastructure misconfigurations. This topic also encompasses integration points with system configuration tools and considerations for managing secrets and secure defaults within infrastructure definitions.