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 Strategy and Migration Planning
Fundamentals and planning practices for adopting cloud computing and migrating workloads to cloud environments. Coverage includes understanding cloud delivery models such as Infrastructure as a Service, Platform as a Service, and Software as a Service, and hybrid deployment options. Candidates should be able to evaluate migration strategies including lift and shift, refactor, replatform, and rebuild, and assess trade offs across cost, performance, security, compliance, and organizational readiness. Planning topics include workload assessment, suitability analysis, vendor evaluation for examples like Amazon Web Services, Microsoft Azure, and Google Cloud Platform, migration sequencing and runbooks, data migration and networking considerations, identity and access patterns, testing and rollback strategies, monitoring and observability, cost optimization and governance, and stakeholder and change management during migration.
Enterprise Cloud Architecture and Migration Strategy
Focuses on enterprise scale cloud architecture and migration planning, including multi cloud and hybrid cloud strategies, governance, cost optimization, compliance, security, and disaster recovery. Covers cloud migration patterns such as lift and shift, refactoring, replatforming, and full rearchitecting, plus data migration strategies, cutover and rollback plans, network and identity architecture, and workload placement decisions. Candidates should demonstrate understanding of differences between major cloud providers such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure, and describe how to evaluate provider strengths, select migration approaches, and design resilient, cost effective enterprise cloud solutions.
Technology and Digital Capability Evaluation
Assessing technology options and digital capabilities with a clear link to business outcomes. Evaluation considerations include scalability, reliability, security, maintainability, total cost of ownership, vendor lock in, integration complexity, data maturity, developer productivity, and operational overhead. Effective evaluation uses criteria such as proof of concept, prototype metrics, costed trade offs, organizational ability to operate and maintain the solution, and measurable success definitions tied to business objectives. Candidates should articulate frameworks and processes used to choose build versus buy decisions and how technical choices were validated before wide rollout.
Technology and Platform Selection
Evaluation and justification of technologies services and platforms used to implement systems across the stack. Candidates should be able to select compute options including virtual machines containers and serverless platforms as well as orchestration and workflow engines messaging systems batch and streaming processing engines object and block storage data warehouses and other data platforms. The topic encompasses comparing managed services and self managed deployments cloud versus on premise hosting and choosing frameworks runtimes and overall stacks based on workload characteristics. Assessment focuses on weighing trade offs across cost operational overhead reliability latency and throughput scaling characteristics vendor lock in development velocity team familiarity and learning curve maturity and community support security and compliance and monitoring and debugging complexity. Candidates should demonstrate how system requirements map to service capabilities justify build versus buy decisions and managed service choices design proof of concept experiments and outline migration and rollout planning while making pragmatic choices that balance performance cost and operational risk.
Cloud Architecture and Design Patterns
Designing and evaluating cloud native architectures and common architecture patterns, with attention to service capabilities, limits, and operational and security implications. Topics include compute scaling models for virtual instances, managed compute, serverless functions and container orchestration; storage choice, object storage classes, lifecycle policies and caching strategies; managed relational database architectures with high availability patterns such as multiple availability zone deployments and read replicas; trade offs of serverless approaches including cold start and invocation limits; different load balancing approaches for application level and network level traffic; networking and identity boundary design including virtual networks, subnetting, routing, security groups and access control patterns; backup, recovery and disaster recovery planning; deployment patterns such as blue green and canary releases; scalability strategies, performance and latency considerations; vendor lock in, portability and total cost of ownership trade offs; and operational practices for monitoring, limits management and incident response. Candidates should be able to translate requirements into architecture decisions, justify trade offs, and design for resilience, scalability, performance, security and cost.
Infrastructure Modernization and Cloud Adoption
Covers the end to end process of modernizing an organization infrastructure and adopting public and private cloud platforms. Interviewers assess experience managing traditional data centers and virtualization platforms including capacity planning, power and cooling considerations, hardware refresh cycles, and operational excellence practices. It also includes planning and executing migrations and hybrid architectures, choosing between infrastructure as a service, platform as a service, and software as a service, and selecting cloud native patterns such as containerization, microservices, and serverless where appropriate. Candidates should be able to describe strategy development for organizations with legacy and new systems, cost and risk trade offs, security and compliance impacts, networking and connectivity for hybrid setups, data migration approaches, rollback and cutover techniques, and how infrastructure as code and automation practices support a modernization roadmap.