Course Introduction

My name is Mumshad Mannambeth, and I’ll be your instructor. Kubernetes is the de facto platform for hosting production-grade applications. As companies adopt cloud-native architectures, demand for engineers with Kubernetes skills is rising. This lesson builds a strong foundation by starting with containers and then progressing into core Kubernetes concepts and real-world troubleshooting. We emphasize hands-on practice. You will solve Kubernetes coding challenges in a live browser-accessible Kubernetes environment. You don’t need a powerful laptop or a cloud account — the course provides access to real clusters from your browser.

You get browser-accessible, hands-on environments that run real Kubernetes clusters. This lets you practice commands and debugging without installing or paying for cloud resources.

What you’ll learn in this module

Container basics and running multiple containers locally
Mapping containers and volumes for simple app topologies
Reading and editing static pod manifests (control plane components)
Common control-plane troubleshooting workflows using kubectl
Practical debugging techniques you can use in production clusters

Example: running multiple containers locally

Run example application containers (detached):

# Run sample application containers (detached)
docker run -d --name python1 python-app
docker run -d --name python2 python-app

# Run helper containers and link them to the app containers (legacy --link used here for illustration)
# Note: --link is a legacy Docker feature and not recommended for new deployments; use user-defined networks instead.
docker run -d --name helper1 --link python1:app1 helper
docker run -d --name helper2 --link python2:app2 helper

The --link flag is a legacy Docker feature. For modern local development and production deployments, prefer user-defined Docker networks or service discovery mechanisms. Using --link can introduce brittle dependencies between containers.

Simple mapping representation:

Component	Role	Volume
Python1	App1	Vol1
Python2	App2	Vol2
helper1	Helper	—
helper2	Helper	—

Kubernetes manifests and control-plane troubleshooting

Below is an example snippet of a static pod manifest (illustrative; e.g., a kube-scheduler static pod). It mounts a kubeconfig, uses host networking, and sets a cluster-critical priority class.

apiVersion: v1
kind: Pod
metadata:
  name: kube-scheduler
spec:
  hostNetwork: true
  priorityClassName: system-cluster-critical
  containers:
    - name: kube-scheduler
      # image and command shown illustratively; actual manifests may vary by distro/version
      image: k8s.gcr.io/kube-scheduler:v1.20.0
      command:
        - kube-scheduler
        - --kubeconfig=/etc/kubernetes/scheduler.conf
      volumeMounts:
        - mountPath: /etc/kubernetes/scheduler.conf
          name: kubeconfig
          readOnly: true
  volumes:
    - name: kubeconfig
      hostPath:
        path: /etc/kubernetes/scheduler.conf
        type: FileOrCreate
status: {}

Key manifest fields (quick reference):

Field	Purpose	Example / Notes
`hostNetwork`	Use host’s network namespace	`true` for control-plane components
`priorityClassName`	Scheduling priority for pods	`system-cluster-critical`
`volumeMounts`	Where volumes are mounted inside the container	`mountPath: /etc/kubernetes/scheduler.conf`
`volumes`	Declares hostPath or other volume sources	`hostPath.path: /etc/kubernetes/scheduler.conf`

Common diagnostic workflow on a control-plane node

When a control-plane component (like kube-scheduler) fails to come up, a typical workflow is:

Inspect and edit the static pod manifest (e.g., fix paths, permissions, or config flags):

root@controlplane:~# vi /etc/kubernetes/manifests/kube-scheduler.yaml
root@controlplane:~#

Check pod status in the kube-system namespace to see current state and events:

root@controlplane:~# kubectl get pods -n kube-system
NAME                                   READY   STATUS              RESTARTS   AGE
coredns-74ff55c5b-fz97g                1/1     Running             0          24m
coredns-74ff55c5b-wfmdz                1/1     Running             0          24m
etcd-controlplane                      1/1     Running             0          24m
kube-apiserver-controlplane            1/1     Running             0          24m
kube-controller-manager-controlplane   1/1     Running             0          24m
kube-flannel-ds-b85q5                  1/1     Running             0          24m
kube-proxy-pthlt                       1/1     Running             0          24m
kube-scheduler-controlplane            0/1     ContainerCreating   0          15s

After fixing the manifest (for example, correcting file paths or adjusting permissions), the scheduler pod should transition to Running:

root@controlplane:~# kubectl get pods -n kube-system
NAME                                   READY   STATUS    RESTARTS   AGE
coredns-74ff55c5b-fz97g                1/1     Running   0          24m
coredns-74ff55c5b-wfmdz                1/1     Running   0          24m
etcd-controlplane                      1/1     Running   0          24m
kube-apiserver-controlplane            1/1     Running   0          24m
kube-controller-manager-controlplane   1/1     Running   0          24m
kube-flannel-ds-b85q5                  1/1     Running   0          24m
kube-proxy-pthlt                       1/1     Running   0          24m
kube-scheduler-controlplane            1/1     Running   0          15s
root@controlplane:~#

We will walk you through these steps, plus how to use kubectl describe, kubectl logs, and node-level checks (file permissions, SELinux/AppArmor contexts, and hostPath validity) to systematically identify and resolve issues.

Kubernetes Basics

Course Introduction

What you’ll learn in this module

Example: running multiple containers locally

Kubernetes manifests and control-plane troubleshooting

Common diagnostic workflow on a control-plane node

Links and references

Watch Video

​What you’ll learn in this module

​Example: running multiple containers locally

​Kubernetes manifests and control-plane troubleshooting

​Common diagnostic workflow on a control-plane node

​Links and references

Watch Video

What you’ll learn in this module

Example: running multiple containers locally

Kubernetes manifests and control-plane troubleshooting

Common diagnostic workflow on a control-plane node

Links and references