Containers, orchestration, cloud infrastructure, and the practices that keep production reliable.
Create a reproducible local Kubernetes cluster with kind, load development images safely, expose services, test multiple nodes, and clean up.
Why Terraform's state file is the actual source of truth behind every plan and apply, and how drift, locking, and idempotency all follow from that design.
How vulnerability scanners actually inspect container image layers, how to read a scan report, and the practices that reduce real supply-chain risk.
How pod-to-pod networking, Services, and kube-proxy's packet rewriting fit together to make Kubernetes' flat network model actually work.
The two-phase filter-and-score process the Kubernetes scheduler uses to decide which node a pod lands on, and how to influence it.
How multi-stage builds, distroless bases, secret-safe caching, non-root execution, and layer inspection produce smaller, auditable runtime images.
At PyCon on March 15, 2013, dotCloud co-founder Solomon Hykes introduced Docker to the world, ahead of the company's later pivot to focus on it entirely.
On October 29, 2013, dotCloud announced it was scaling back its original PaaS business and renaming the company entirely around its container tooling.
Kubernetes 1.0 arrived in July 2015 as Google placed the project with the newly launched CNCF, anchoring a vendor-neutral ecosystem.
How the three pillars of observability complement each other, and why having all three matters more than maximizing any single one.