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.
Observability and Monitoring Architecture
Building visibility into infrastructure and services: metrics, logs, and traces, dashboards and alerting, SLIs/SLOs, and the design of an observability stack. Covers instrumenting systems for actionable signal, reducing alert noise, and diagnosing production issues from telemetry. Infrastructure-wide observability, distinct from network-specific monitoring.
Infrastructure as Code and Automation
Defining, provisioning, and automating infrastructure programmatically. Covers declarative IaC with Terraform and comparable tools like CloudFormation (resource and provider model, state management and remote backends, module design and reuse, workspaces, drift detection, and safe plan/apply workflows), plus the broader automation discipline: provisioning pipelines, golden-image and machine-image building, scripting glue, self-service platforms, and end-to-end environment stand-up. The authoring, lifecycle, and automation of infrastructure code that reduces manual toil across provisioning workflows.
Kubernetes Architecture, Operations, and Troubleshooting
How Kubernetes works, how to run it, and how to debug it. Covers control-plane and node components, the scheduler and API server, cluster design, high availability and multi-cluster topologies, and platform-level operations; the workload primitives (pods, deployments, services, controllers), cluster upgrades, and designing Kubernetes as an internal platform; and the operational depth inside a cluster including pod and service networking, ingress and the CNI model, service mesh, persistent volumes and storage classes, resource requests and limits, and systematically diagnosing scheduling, networking, and storage failures. The full architecture-through-day-two-operations span of Kubernetes.
AWS Core Services and Architecture
Amazon Web Services' core service catalog and how the pieces compose into a working system: EC2, Lambda, S3, VPC, IAM, RDS, and the managed-service ecosystem. Covers service selection within AWS, common reference architectures, the AWS Well-Architected Framework pillars, and operational patterns specific to the platform. For provider-agnostic compute or storage trade-offs, see the cross-cloud entries.
Containerization and Docker Fundamentals
Packaging applications into containers: images and layers, Dockerfiles, registries, image optimization and security, container networking and storage, and the container runtime model. Covers how containers differ from virtual machines, image build and management, and the fundamentals that underpin any orchestration platform. The container primitive before orchestration.
Cloud Compute Options and Trade-offs
Choosing among compute abstractions independent of provider: virtual machines, containers, managed container services, serverless functions, and bare metal. Covers the cost, control, cold-start, scaling, and operational trade-offs of each model; how to pick an instance family or hardware accelerator (general-purpose, compute-optimized, memory-optimized, GPU, TPU) and a purchasing model (on-demand, reserved, spot); and how workload characteristics (latency, statefulness, burstiness) drive the decision. Managed-versus-self-managed reasoning lives here.
Cloud Cost Optimization and FinOps
Controlling and optimizing cloud spend: cost modeling and forecasting, rightsizing, reserved capacity and savings plans, autoscaling for cost, tagging and chargeback, and the FinOps operating model. Covers building the business justification for infrastructure spend and continuously driving efficiency at scale without sacrificing reliability. Cost as a first-class architectural concern.