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.
Technical Stack and Infrastructure
Addresses the technology stack and platform infrastructure choices that support a product. Topics include cloud architecture, deployment platforms, service and data layer design, observability and monitoring, scalability and performance considerations, tooling for build and release, and assessing technical debt or modernization needs in the stack. Also covers evaluation of BI tools, ETL platforms, and how infrastructure choices affect team velocity and operational cost.
GCP Core Services and Architecture Basics
Core Google Cloud Platform services and architecture concepts, including Compute Engine, Kubernetes Engine (GKE), App Engine, Cloud Functions, Cloud Run, Cloud Storage, BigQuery, Pub/Sub, Cloud SQL/Spanner, and IAM. Covers foundational cloud architecture topics such as projects and resource organization, VPC networking (regions, zones, subnets), identity and access management, security considerations, and scalable design patterns for cloud-native applications on GCP.
Microsoft Product and Azure Fundamentals
Practical knowledge of Microsoft enterprise offerings and core Azure services, and the ability to map those products to customer scenarios. Candidates should understand when to recommend Azure compute database and networking services versus platform services when Microsoft 365 Dynamics 365 or Power Platform are more appropriate and how to articulate trade offs for scalability security compliance and cost. Topics include Azure infrastructure and platform services virtual machines app services managed databases storage networking identity and governance considerations migration patterns and common integration approaches with on premise systems.
Microsoft Products and Ecosystem
Knowledge of Microsoft's enterprise product suite and how the pieces fit together as part of a broader technology stack. Covers Office 365 and Microsoft 365 (Teams, SharePoint, Exchange), Dynamics 365, the Power Platform (Power Apps, Power Automate, Power BI), and core Azure services, along with common integration patterns between them: identity and access management (Azure AD / Entra ID, single sign-on), data flows across products, typical enterprise deployment topologies, licensing and bundling models, and security and compliance considerations. Candidates should be able to explain how these products interoperate, when a Microsoft-native service is the right fit versus a third-party alternative, and the practical tradeoffs involved in enterprise adoption, rollout, and migration.
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.
Vendor Selection and Technology Evaluation
Approach for evaluating vendors, tools, and technology options before committing to them. Topics include defining requirements and success criteria, creating structured evaluation and scoring criteria, running proof of concept or pilot exercises, benchmarking performance and scalability, assessing total cost of ownership and ongoing operational burden, reviewing service level agreements and support/contract terms, examining vendor roadmaps and interoperability with existing systems, and planning for migration paths and vendor lock in mitigation. Applies to any technology or service selection decision (infrastructure and network hardware, cloud platforms, data and software tooling, security products, SaaS vendors, and similar), not just one domain.