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 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.
Multi Cloud Architecture and Trade Offs
Covers architecture patterns, operational considerations, and trade offs when designing systems that span two or more public cloud providers. Includes comparing compute, storage, networking, database, identity, and managed service equivalents across AWS, Microsoft Azure, and Google Cloud Platform; criteria for choosing managed platform services versus infrastructure virtual machines; containerization and orchestration trade offs; strategies to minimize vendor lock in such as abstraction layers, multi provisioned pipelines, and data portability; cost and service level trade offs including egress and billing implications; cross cloud networking and connectivity patterns; security, compliance, and identity implications across providers; implications for monitoring, logging, deployment automation, and operational run books. Candidates should be able to justify provider choices, explain the operational overhead of multi cloud, and propose realistic migration or hybrid strategies.
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.
Network Architecture and Topology
Design of network topologies and segmentation for scale and reliability. Covers data center and backbone topologies such as spine leaf, hub and spoke, full and partial mesh, WAN options including MPLS and SD WAN, redundancy and failover strategies, segmentation and micro segmentation for security, and design considerations for global and regional network growth and performance.
Terraform Fundamentals
Foundational knowledge of HashiCorp Terraform and infrastructure as code practices. Topics include the HashiCorp configuration language, providers and resources, variables and outputs, data sources, module design and code organization, state file concepts and state management including local and remote backends, handling sensitive data and secrets, common interpolation and conditional patterns, and writing reusable modules for multi tier applications networking and databases. Candidates should understand best practices for state locking remote state storage and how to structure Terraform for collaboration and safe deployments.