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.
Cloud Integration and Hybrid Network Architecture
Designing connectivity and integration between on premise infrastructure and public cloud environments, including hybrid and multi cloud topologies. Topics include dedicated interconnect options and internet based connectivity, routing and network topology trade offs, virtual private networks and software defined wide area networks, network virtualization, security boundary and identity considerations across environments, latency and throughput implications, cost trade offs for interconnects, and operational practices for managing hybrid infrastructure and multi cloud complexity.
Platform Architecture for Organizational Scale
Designing internal platforms and infrastructure to support large engineering organizations and evolving teams. Topics include developer experience and self service platform design, deployment platforms that enable safe frequent releases for hundreds of engineers, platform automation and observability patterns that provide cross service visibility, governance and operational policies, service onboarding and lifecycle, and how to evolve platform capabilities as headcount and service count grows. Candidates should discuss trade offs between centralized platform services and team autonomy, metrics for platform health, and approaches to encourage adoption while minimizing operational friction.
Understanding the Company's Infrastructure Context
Research the company's public infrastructure information (engineering blog, tech talks, published case studies, job description). Understand what systems they operate at scale, what problems they likely face, and what your role would contribute to.
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.
AWS Well-Architected Framework Principles
Principles and guidelines from the AWS Well-Architected Framework for designing, building, and operating robust, secure, efficient, and cost-optimized systems on AWS. Covers the five pillars—Operational Excellence, Security, Reliability, Performance Efficiency, and Cost Optimization—and related architecture decisions, patterns, and best practices.
Cloud Architecture Fundamentals
Fundamental concepts and design patterns for cloud based systems and services. Topics include core service categories such as compute, storage, networking and databases, virtual machines and containers, serverless computing, managed services, and infrastructure as code. Understand deployment and service models including infrastructure as a service, platform as a service, and software as a service. Evaluate architectural patterns including monolithic, microservices, and serverless approaches, and how they influence scalability, availability, reliability, performance, security, and cost. For more senior roles include distributed systems concepts, consistency and partitioning models, trade off analysis, fault isolation, observability and operational practices in cloud native design.
Containerization and Orchestration Fundamentals
Practical understanding of container technology and orchestration platforms. Topics include container image creation and registries, container runtime basics, core orchestration concepts such as pods, services, deployments, replicas, stateful sets, persistent storage, configuration management, service discovery and networking, scaling and autoscaling, rolling updates and rollbacks, self healing, resource management, and common deployment patterns. Emphasis is on how containers and orchestrators change deployment and operations practices and on at least one major platform such as Kubernetes or a cloud managed service.
Networking, VPC, and Connectivity
Deep understanding of AWS VPC architecture including subnets (public and private), route tables, Network Address Translation (NAT), internet gateways, and VPC endpoints. Knowledge of security groups and network ACLs. Understanding of VPN and AWS Direct Connect for hybrid connectivity. DNS and Route 53 routing policies.
Cloud Platform Fundamentals
Comprehensive understanding of core public cloud services and the primary trade offs when selecting among them across major providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Candidates should know compute options including virtual machines, managed compute, containers and serverless functions; storage types including object, block and file storage and lifecycle and archival strategies; managed database offerings for relational, non relational, and data warehouse workloads; networking fundamentals including virtual private networks, subnets, routing, load balancing, content delivery networks, and private connectivity; messaging and integration services such as message queues and event streaming; identity and access management and secrets management; monitoring, logging, and observability; autoscaling, elasticity, high availability, and basic disaster recovery patterns; and cost and pricing considerations. The topic also covers the trade offs between managed services and self managed infrastructure in terms of consistency, latency, cost, operational overhead, and durability, and the ability to map common workload requirements to the right service categories.