Kubernetes Handbook for Beginners: Deploy Apps & Understand K8s Architecture

Struggling to understand Kubernetes? This guide breaks down k8s, explaining its purpose, history, and how it simplifies deploying and managing applications, even if you're just getting started. We'll cover everything from basic concepts to deploying your first application.

What is Kubernetes? Demystifying k8s for Beginners

Kubernetes (often called k8s) is like a super-efficient manager for applications built from microservices. Instead of one large application, modern apps are often broken down into smaller, independent services called microservices.

Microservices are like building blocks. Think of a banking app:

• One microservice handles user onboarding.
• Another processes deposits.
• A separate one manages payments.

To the user, it looks like one app, but behind the scenes, many small apps are working together. Managing these microservices manually can be a mess. Kubernetes automates deployment, scaling, monitoring, and ensures reliability. It organizes your microservices, making sure they run smoothly, regardless of traffic.

Why Kubernetes? Understanding Application Deployment Before k8s

Before Kubernetes, deploying applications, especially those with many microservices, was a complex task.

The Old Way: Distributed Systems Nightmare

Microservices were installed on separate servers (physical or virtual). This involved:

• Installing each microservice individually.
• Installing necessary software dependencies on each server.
• Configuring everything manually, server by server.

Managing updates, bug fixes, and scaling was a major headache.

Containers to the Rescue (Sort Of)

Containers package a microservice with everything it needs: code, settings, and libraries. Docker made this easy, allowing deployment on single servers, multiple servers, or cloud platforms.

The Problem Kubernetes Solves: Managing Container Chaos

Containers simplified deployment but introduced new challenges at scale.

The Container Management Headache

Managing a few containers manually is manageable. But with dozens or hundreds of microservices, the process becomes overwhelming:

• Manual container deployment
• Manual restarts if one crashed.
• One-by-one scaling during traffic spikes.

Docker and Docker Compose were great for small projects but not enterprise applications.

Cloud-Managed Services: A Partial Solution

Services like AWS Elastic Beanstalk, Azure App Service, and Google Code Engine allowed container deployment without server setup. You could deploy and scale containers automatically.

Grouping microservices was awkward and expensive. Each microservice often needed its own cloud instance. The expense adds up quickly, even if microservices are barely used.

Kubernetes: The Smarter, Leaner Alternative

Kubernetes allows using one or two servers (VMs). It decides which container goes where based on space and resources. It is also less stressful.

Kubernetes: Customization and Flexibility

Here are some things you can customize using Kubernetes:

• Resource assignments: Allocate resources (vCPUs, memory) based on microservice needs.
• Minimum instance count: Ensure a minimum number of copies of critical services are always running.
• Grouping: Organize containers by team or environment.
• Automatic Scaling: Scale individual containers based on traffic.
• Server scaling: Increase the number of servers (VMs) when traffic grows.

Kubernetes works consistently across environments (AWS, Google Cloud, Azure, or your laptop). This isn't the case for managed services like Elastic Beanstalk or Azure App Service.

How Kubernetes Works: Understanding the Core Components

Kubernetes automates microservice management, keeping them alive, scaling them, and restarting them if they crash. Let's look at the parts that make up the Kubernetes setup.

1. Cluster: The Foundation

A Kubernetes Cluster is the entire setup of machines (physical or cloud-based) where Kubernetes runs. A cluster consists of:

• Master Node (Control Plane): The brain of Kubernetes.
• Worker Nodes: Where the applications run.

Think of it like a playground for your microservices.

2. Master Node (Control Plane): The Brains

The Master Node manages the entire cluster, deciding which applications run where, monitoring health, and scaling as needed. It watches over the worker nodes and ensures everything runs smoothly.

Inside the master node are mini-components:

• API Server: The front door to Kubernetes, handling communication.
• Scheduler: Assigns applications (Pods) to Worker Nodes based on resources.
• Controller Manager: Ensures the system's actual state matches the desired state.
• etcd: Kubernetes' memory, storing config files, state, and metadata.

3. Worker Nodes: The Muscle

Worker Nodes are the servers that run the actual application containers. The worker nodes run your containers and each has their own helpers to manage microservices:

• Kubelet: The agent on each Worker Node, ensuring containers are healthy.
• Kube Proxy: Handles network traffic, ensuring communication between services.

To summarize, the Master Node plans, watches, and assigns tasks, while the Worker Nodes perform the actual work.

4. Kubernetes Workflow

Components work together. Components like etcd, Kubelet, Scheduler, Controller Manager, and Kube Proxy all work together like parts of a well-oiled machine. Kubernetes handles microservices automatically, and scaling them up, moving them around, and restarting them if they crash.

Kubernetes Workloads: Pods, Deployments, Services, & More

Kubernetes workloads are the building blocks for managing and running your applications. They tell Kubernetes what to run and how to run it.

1. Pods: The Core Unit

A Pod is the smallest unit in Kubernetes, representing a single instance of a running process. It can contain one or more containers that share storage and network resources. Each share the same network IP and storage, allowing them to communicate easily and share data.

Pods are ephemeral, meaning they can be replaced easily. If a Pod dies, Kubernetes creates a new one to replace it instantly.

2. Deployments

A Deployment provides declarative updates for Pods and ReplicaSets. In essence, it manages the desired state of your application.