Build a practical Kubernetes foundation in a ready-to-use v1.35.5 cluster. The course uses six learning cycles: each guided lab explains a core workflow, and a focused challenge immediately asks you to apply it with less scaffolding.
Across 12 activities, you will progress from reading cluster state to declaring workloads, debugging failures, connecting applications, scaling replicas, and managing releases. The emphasis is on understanding desired state and verifying what Kubernetes controllers actually produce.
What You Will Learn
By completing this course, you will be able to:
- Confirm the active
kubectlcontext, Kubernetes version, node health, namespaces, and system workloads. - Write YAML manifests for Pods and Deployments and relate labels, ReplicaSets, and controllers to desired state.
- Diagnose unhealthy workloads with status,
describe, events, logs, and container inspection, then repair the saved manifest. - Expose applications with ClusterIP and NodePort Services and trace selectors, EndpointSlices, and cluster DNS.
- Create a two-tier in-cluster web stack with separate Deployments and stable Service identities.
- Scale a Deployment manually and observe Pods, Service backends, and request distribution converge.
- Perform rolling image updates, inspect revisions and ReplicaSets, recover a failed release, and keep live and saved state consistent.
Who This Course Is For
This course is for complete Kubernetes beginners, container users taking their first orchestration steps, and developers who want to understand everyday application operations before studying cluster administration. The guided-lab and challenge pairs suit learners who want explanation followed by immediate independent practice.
Prerequisites: No prior Kubernetes experience is required. Basic Linux terminal skills, familiarity with containers, and the ability to read simple YAML are helpful, but the guided labs introduce the Kubernetes objects and commands used in the challenges.
Learning environment: All 12 activities run in provided Ubuntu 22.04 terminal environments with a preconfigured single-node labex-v135 cluster running Kubernetes v1.35.5. The cluster starts for each activity, so you do not install Kubernetes or connect an external cloud account; startup can take a few minutes.
Frequently Asked Questions
How are the guided labs and challenges organized?
There are six guided labs and six challenges. Each challenge follows a related lab on cluster inspection, deployment, debugging, Services, scaling, or releases, letting you repeat the workflow with fewer command-by-command instructions.
Do I need my own Kubernetes cluster or Docker registry?
No. A local minikube-based cluster and pinned container images are prepared in the LabEx environment. You work entirely in the supplied terminal without creating cloud infrastructure or pushing images to an external registry.
What Kubernetes topics are intentionally outside the course?
The course focuses on stateless Pods, Deployments, Services, manual scaling, troubleshooting, and rolling releases. Persistent storage, Ingress, security policy, observability platforms, automatic scaling, and multi-node administration are not covered.
How does this differ from “30 Days of Kubernetes”?
This is a guided Beginner course that teaches the core application workflow before testing it in short challenges. “30 Days of Kubernetes” is an Intermediate collection of 30 independent CKA-, CKAD-, and CKS-style tasks covering deeper administration, repair, storage, networking, and security.
