What to expect
Go from container basics to a production-shaped Kubernetes cluster over five hands-on days: architecture, workloads, networking, storage, troubleshooting, and observability, all running on your own kind cluster.
Kubernetes
Kubernetes Foundations
Go from container basics to a production-shaped Kubernetes cluster: architecture, workloads, networking, storage, troubleshooting, and observability - all on your own kind cluster.
- Duration
- 5 days
- Level
- Beginner to Intermediate
- Format
- On-site
- Price
- On request
What to know before
Who it's for
- Engineers and platform teams starting from Docker/container basics who need a solid, production-shaped foundation in Kubernetes before specializing further.
- Teams with some ad hoc Kubernetes exposure who want the gaps in their mental model - scheduling, storage, troubleshooting, observability - closed systematically.
- Each participant works on their own VM with VS Code preinstalled, running a multi-node kind cluster on Docker with Cilium as the CNI - no cloud account needed to attend.
You'll learn to
- Bootstrap and operate a multi-node kind cluster: architecture, kubectl fluency, namespaces, and context management.
- Design and deploy production-shaped workloads: Deployments, StatefulSets, DaemonSets, Jobs, scheduling, and rolling updates.
- Wire up services, networking, config, storage, and RBAC, then troubleshoot and observe a cluster using metrics, logs, and traces you built yourself.
Agenda
Day 1
- Kubernetes architecture: control plane, kubelet, kube-proxy, and etcd
- Container runtime basics and bootstrapping a multi-node kind cluster
- kubectl fundamentals, namespaces, and context management
Day 2
- Workloads: Pods, Deployments, ReplicaSets, StatefulSets, DaemonSets, and Jobs/CronJobs
- Scheduling: affinity/anti-affinity, taints and tolerations, resource requests and limits
- Rolling updates and rollbacks
Day 3
- Services and networking: ClusterIP, NodePort, and Ingress on kind
- DNS, ConfigMaps, Secrets, and environment injection
- Liveness, readiness, and startup probes
Day 4
- Storage: PersistentVolumes, PersistentVolumeClaims, and StorageClasses via local-path-provisioner
- Multi-container pod patterns: init containers and sidecars
- Systematic troubleshooting: triaging pod, node, and network failures from events and logs
- Introductory RBAC: Roles, RoleBindings, and ServiceAccounts
Day 5
- Metrics with Prometheus and Grafana dashboards tied to user-facing symptoms
- Centralized logging and structured logging practices
- Distributed tracing with OpenTelemetry
- Incident-response drill using only the observability stack built that morning
The MVJ Method
Lots of practical, hands-on teaching. Theory shows up only when you need it to unblock the next exercise.
Mostly hands-on. Most of the session is spent building real labs and real pipelines, not watching slides.
Your own cluster, not a shared sandbox. Every participant runs a real multi-node kind cluster on their own VM, so what gets built in the room is what ships on Monday.
Small enough that everyone drives. Groups of 4-12, so every attendee gets keyboard time.
You keep the runbook. Labs, scripts, and reference material go home with your team as the start of your own documentation, not a one-off slide deck.
Request this training
Tell us a bit about your team and we'll get back to you to schedule Kubernetes Foundations.
Manuel Vogel-Johnson
Principal Engineer
“Most Kubernetes training stops at 'it works on my sandbox.' We spend two full days on storage, troubleshooting, and observability because that's where teams actually get stuck in production, not on day one.”
Kubernetes Foundations
Go from container basics to a production-shaped Kubernetes cluster: architecture, workloads, networking, storage, troubleshooting, and observability - all on your own kind cluster.
- Duration
- 5 days
- Format
- On-site
- Level
- Beginner to Intermediate
- Price
- On request
Learning goals
- Bootstrap and operate a multi-node kind cluster: architecture, kubectl fluency, namespaces, and context management.
- Design and deploy production-shaped workloads: Deployments, StatefulSets, DaemonSets, Jobs, scheduling, and rolling updates.
- Wire up services, networking, config, storage, and RBAC, then troubleshoot and observe a cluster using metrics, logs, and traces you built yourself.
FAQs
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