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 Networking and VPC Design
Designing networks inside a cloud provider: VPC/VNet topology, subnets, route tables, gateways, peering, private connectivity, and cloud load balancers. Covers segmentation, security groups and network ACLs, connectivity to on-premises, and how cloud network design differs from traditional data-center networking. Sits between the platform entries and the physical-networking entries.
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.
Networking Fundamentals and Protocols
The core model of how networks move data: the OSI and TCP/IP layers, the Internet Protocol suite, transport protocols (TCP versus UDP), encapsulation, and TCP behavior including congestion control. Covers the protocol foundations every networking and infrastructure discussion builds on, from link layer through transport. The conceptual bedrock beneath addressing, routing, and switching.
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.
Google Cloud Platform Services and Architecture
Google Cloud Platform's core services and architecture: Compute Engine, Cloud Run, GKE, Cloud Storage, VPC, and BigQuery-adjacent managed services. Covers GCP service selection, networking and IAM specifics, and reference patterns for building on the platform. For provider-agnostic compute, storage, or networking concepts, see the cross-cloud entries.
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.
Infrastructure Scaling, Capacity Planning, and High Availability
Making infrastructure grow and stay up: horizontal and vertical scaling, autoscaling, load balancing, capacity planning and forecasting, and high-availability and redundancy design. Covers sizing systems for demand, distributing load, and eliminating single points of failure so services remain available as they scale. The reliability-and-growth discipline.
Cloud Service and Deployment Models
The foundational service models (IaaS, PaaS, SaaS, FaaS) and deployment models (public, private, hybrid, community cloud) and when each is appropriate. Covers the shared-responsibility boundary, on-demand elasticity, the core value proposition of cloud versus on-premises, and how service-model choice shifts operational ownership. The conceptual entry point before any provider-specific or architectural depth.
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.