Automate the software delivery lifecycle — continuous integration, continuous delivery/deployment, pipeline stages, and best practices.

Master container fundamentals — images, containers, Dockerfile best practices, multi-stage builds, and container networking.

Deploy, scale, and manage containerized applications with Kubernetes — pods, deployments, services, ingress, and cluster architecture.

Manage cloud infrastructure declaratively — Terraform state, providers, modules, and best practices for infrastructure reproducibility.

The operational lifecycle of secrets — Vault, KMS, SOPS, dynamic vs static, rotation, dynamic secret generation, and the fail state of `.env` files in production.

Build observable systems — metrics, logs, traces, alerting, and the three pillars of observability in production environments.

A vendor-neutral tour of cloud computing — compute, storage, networking, serverless, managed services, and the cost/operability trade-offs of each abstraction.

Run services you can trust in production — SLI/SLO/error budgets, alerting and paging, incident response, blameless postmortems, and the discipline of reliability engineering.

What happens after the artefact ships — release strategies that contain blast radius, progressive delivery, feature-flag-driven decoupling, and the rollback that you wish you never need.

Treating cloud spend as an engineering concern — unit economics, tagging strategy, right-sizing, committed use, spot/preemptible, and the multi-region cost trade-offs every platform team owns.

SRE's sister discipline — fault injection, ChaosMesh, Gremlin, game days, blast-radius doubling, and the hypothesis-driven practice of breaking things on purpose.