Mastering Kubernetes: From Beginner to Certified Administrator

Kubernetes has revolutionized application deployment and management. But with so many components, it can confuse newcomers.

So I’ve hand-picked the 14 best Kubernetes tutorials for smooth sailing from beginner to certified Kubernetes administrator.

Here’s what we’ll cover:

• Kubernetes architecture simplified
• Install local Kubernetes cluster
• Core concepts explained
• Sample apps deployment
• CKA exam tips
• Managed services overview
• Career guide
• Expert-curated resources

Let’s get learning!

Kubernetes Demystified

Think of Kubernetes (K8s) as a city planner for containerized apps. It automatically handles mundane infrastructure tasks so developers can focus on building great products.

Some key benefits:

• Portability across infra
• Auto-scaling
• Self-healing capabilities
• Service discovery
• Storage orchestration
• Smooth app rollouts

With modular components and APIs, Kubernetes enables the ultimate DevOps workflow.

Now let’s break down what all those complex K8s terms actually mean:

Clusters: The K8s control plane consisting of master and worker nodes

Nodes: The physical/virtual machines controlled by the cluster

Pods: The basic units deployed on nodes. Wraps 1 or more containers.

Deployments: Declarative way to manage pods. Handles scaling and rollbacks.

Services: Networking abstraction to connect group of pods.

Here‘s a simple visual overview of how they all fit together:

[Diagram showing Kubernetes architecture]

Getting familiar with these core components will provide immense clarity. Now let‘s install our own demo cluster to see them in action.

Install Local Kubernetes Cluster

To get hands-on experience, we‘ll deploy a simple single-node cluster with kubeadm.

First, create a Linux VM with the latest OS packages. I prefer Debian or Ubuntu.

Next install Docker runtime and the kubeadm toolkit using apt:

$ apt update 
$ apt install docker.io kubeadm

Now initialize the Kubernetes master with:

$ kubeadm init 

Kubeadm handles all the crypto keys and certificates for secure cluster communications.

To start using the cluster, configure local access with:

$ mkdir ~/.kube
$ cp /etc/kubernetes/admin.conf ~/.kube/config
$ kubectl get nodes

The get nodes command shows our single node up and ready!

With the foundations laid, we can now start deploying apps. But first, let‘s solidify those core concepts.

Kubernetes Concepts Explained

Now that we have a test cluster, let‘s demystify key components by relating them to real-world examples:

Pods

Pods are much like shipping containers you see on trains and trucks. They‘re a standard box to pack your application modules into.

Like containers, pods have limited compute resources allocated to them by the cluster. CPU, memory limits ensure no pod hogs resources.

Each pod gets a unique internal IP address within the cluster network. Containers inside share the same network namespace and storage volumes.

Pod health is monitored via liveness and readiness probes like regular HTTP checks. Unhealthy pods get restarted or rescheduled.

In summary, pods abstract and run one or more containers as a portable, networkable application unit.

Deployments and ReplicaSets

While pods run individual containers, deployments handle keeping pods running the desired application state.

Like city planners ensuring enough power, water and housing capacity for residents, deployments ensure sufficient pods to satisfy user demand.

This is done via ReplicaSets – tell it 3 replicas, you get 3 identical pods running for scale and redundancy.

If a pod goes down, the ReplicaSet notices and launches a replacement. Scaling up/down pods is also a simple change to the replica count.

Deployments also rollout changes smoothly via rolling updates. This transitions pods to new versions with minimal downtime. Rollbacks revert quickly in case of issues.

This automation frees developers to code features rather than worry about infrastructure reliability!

Services and Networking

How do frontend JavaScript pods talk to database API pods in a secure, reliable way? Enter Kubernetes Services.

Services provide internal DNS names for group of pods, abstracting away complex cluster networking.

Just refer to the service DNS and traffic gets intelligently load balanced across pod replicas.

Services integrate seamlessly with deployments. Scaling pods scales ability to handle traffic. No manual IP and port changes!

There are different service types optimized for internal or external access. Cluster IPs for internal use and NodePort/LoadBalancer to expose apps publicly.

Kubernetes handles all the complex TCP/UDP forwarding and access policies so apps connect securely.

Storage and Volumes

What about stateful apps like databases that need persistent storage beyond the container lifespan?

Kubernetes Volume abstraction binds storage devices/cloud drives into pods in a portable manner. They survive pod restarts and moves across nodes.

Common volume types are Azure Disks, AWS EBS Volumes and Network File Shares mounted into pods.

The cluster manages attaching and detaching volumes as pods start and stop. State persists storage lifecycle independent of application code!

With volumes, moving databases across envs or regions becomes effortless. Kubernetes is a DBA‘s dream!

This has been a simplified overview of pivotal Kubernetes basics. Let‘s look next at configuring cluster resources.

Configuration Best Practices

To follow security best practices, Kubernetes provides ConfigMaps and Secrets:

ConfigMaps store non-confidential data like application settings as key-value pairs:

apiVersion: v1
kind: ConfigMap 
metadata:
  name: app-config
data:
  LOG_LEVEL: DEBUG
  TIMEOUT: "60"

ConfigMaps decouple static config from container images. Pods reference ConfigMaps directly without baking them in.

Secrets securely inject sensitive data like passwords into pods:

apiVersion: v1
kind: Secret
metadata: 
  name: db-secret
type: Opaque
stringData:
  DB_HOST: "prod-db.com"
  DB_USER: "appuser"
  DB_PASS: "S3curePa$$w0rd"

Secrets store base64 encoded data encrypted at rest. Only target pods get decrypted values.

Next let‘s explore running real world apps on Kubernetes.

Deploy Sample Applications

Enough theory – let‘s get our hands dirty by deploying test apps on the learning cluster.

I‘ll provide all the manifest YAMLs for you to apply as-is. Tweak them later once comfortable!

1. Hello World

Let‘s start with the classic…

First create a Deployment and expose a Service:

hello-world.yaml:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: hello-world 
  labels:
    app: hello-world
spec:
  replicas: 3
  selector:
    matchLabels:
      app: hello-world 
  template:
    metadata:
      labels:
        app: hello-world
    spec:
      containers:
      - name: hello-world
        image: mcr.microsoft.com/azuredocs/containerapps-hello-world:latest
        ports:
        - containerPort: 80

---  

apiVersion: v1
kind: Service
metadata:
  name: hello-world-svc
spec:
  type: ClusterIP  
  selector:
    app: hello-world
  ports:
  - port: 80
    targetPort: 80

Apply it:

kubectl apply -f hello-world.yaml

Check deployment is up via:

kubectl get pods
# Should see 3 hello-world pods soon 

The app is now HA with 3 replicas load balanced by the internal ClusterIP Service!

2. MongoDB Database

Let‘s make things more interesting…

Deploying stateful MongoDB requires persistent storage volumes:

mongo.yaml

# Mongo DB
apiVersion: apps/v1
kind: StatefulSet 
metadata:
  name: mongo
spec:
  serviceName: "mongo"  
  replicas: 3
  selector:
    matchLabels:  
      app: mongo
  template:
    metadata:
      labels:
        app: mongo 
    spec:
      containers:
        - name: mongo
          image: mongo
          volumeMounts:
            - name: mongo-persistent-storage
              mountPath: /data/db
  volumeClaimTemplates:  
  - metadata:
      name: mongo-persistent-storage
    spec:
      accessModes: [ "ReadWriteOnce" ]
      resources:
        requests:
          storage: 1Gi

---

# Mongo Service       
apiVersion: v1
kind: Service
metadata:
  name: mongo 
spec:
  ports:
  - port: 27017
    targetPort: 27017
  clusterIP: None  
  selector:
    app: mongo

This creates a headless service for peer discovery between MongoDB replicas.

Each pod claims 1GB persistent volumes from the infrastructure. Data survives restarts!

Let‘s connect to test it out…

First exec into the mongo pod:

$ kubectl exec -it mongo-0 bash

In the mongo shell:

$ mongo

> show dbs 
admin   0.000GB
config  0.000GB 
local   0.000GB

> db.foo.insert({"name": "test"})
> db.foo.find()
{ "_id" : ObjectId("5f355482e4b0594d5807a96c"), "name" : "test" }

> exit

It works! We inserted a document into MongoDB running on Kubernetes.

This shows just a small sampling of real world apps deployable on K8s.

Let‘s now prep for the popular CKA certification exam.

Preparing for CKA Certification

The Certified Kubernetes Administrator exam is all hands-on – no multiple choice questions.

You perform admin tasks live on a temporary cluster. Areas tested:

• Installation, configuration and validation
• Core concepts – pods, deployments, services networking
• State persistence and data storage
• Troubleshooting and cluster maintenance
• Security – authentication, authorization, TLS policies
• Cluster scaling and upgrades

Here is a short practice scenario:

Create a deployment with pod template spec that runs nginx with 2 container replicas. Only exposed port should be 80. Default namespace

Solution:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-nginx
spec:
  selector:
    matchLabels:
      run: my-nginx
  replicas: 2  
  template:
    metadata:
      labels:
        run: my-nginx
    spec:
      containers:
      - name: nginx
        image: nginx
        ports:
        - containerPort: 80

Certification opens many doors on exciting DevOps career pathways as we‘ll see next.

Kubernetes Job Market Overview

Kubernetes skills are a golden ticket to lucrative DevOps careers with massive growth:

[insert chart showing Kubernetes job trends]

Salaries have also been rising with high demand:

[insert Kubernetes average US salary chart]

CNCF survey found 92% of companies running containers in production rely on Kubernetes.

Popular roles include:

• Site Reliability Engineer
• Platform Engineer
• Cloud Architect
• DevOps Engineer

Certified Kubernetes Administrator is the perfect launch pad. Consider combining with AWS/Azure/GCP cloud expertise for an unbeatable stack!

Comparing Managed Kubernetes Services

For production systems, managed Kubernetes services reduce ops overhead substantially.

Let‘s compare offerings from the big three cloud providers:

Feature	Amazon EKS	Azure AKS	Google GKE
Managed Control Plane	Yes	Yes	Yes
Serverless option	EKS Anywhere	AKS on Azure Arc	GKE Autopilot
Integrated monitoring tools	CloudWatch	Azure Monitor	Stackdriver
Ingress support	ALB Ingress	Application Gateway	Load Balancer
Isolated network policies	Yes – Security Groups	Yes – Calico	Yes – Network Policies
Spot/preemptible node support	Yes	No	Yes
Price per hour	$0.10 – $0.20	$0.10 – $0.30	$0.10 – $0.30

All three provide robust Kubernetes platforms that lift operational burden for production systems and focus engineering on shipping code!

Pick based on existing cloud vendor relationship or regional data regulations. Can‘t go wrong with any option here.

Additional Resources for Learning

Hopefully this beginner‘s guide has shown Kubernetes need not be scary! Here are expert-curated resources for your ongoing education:

Courses

• Kubernetes Deep Dive on Pluralsight
• Certified Kubernetes Application Developer by CNCF

Interactive Learning

• Katacoda Scenarios
• Kubernetes By Example

Docs

• Official Kubernetes Docs
• CNCF Cloud Native Interactive Landscape

Books

• Kubernetes: Up & Running
• Kubernetes Patterns
• Kubernetes Best Practices

This wraps up our epic Kubernetes journey from fundamentals to operating production-grade clusters.

You‘re now ready to dive deeper into containerized application delivery powered by cloud native technologies! Wishing you happy deployments ahead 🙂