Munich Kubernetes training course

1. Day 1

   1. 1. Linux containers and Kubernetes

      Lecture + hands-on labs + challenges

      Kubernetes doesn't know how to deploy apps written in languages such as Java, Node.js, or .NET. Instead, it only understands and uses Linux containers. But how do these Linux containers work? Are those strictly necessary to master Kubernetes? In this course, you will familiarise yourself with containers and Docker.

      1. Containers vs VMs

      2. Understanding process isolation

      3. Is Docker the only one?

      4. Docker client-server architecture

      5. Running containers

      6. Building Docker images

      7. Mounting volumes

      8. Exposing ports

      9. Managing containers lifecycle

      10. Injecting environment variables

      11. Debugging running containers

   2. 2. Kubernetes fundamentals

      Lecture + hands-on labs + challenges

      In this course, you will learn how to build, deploy and scale your application in a Kubernetes cluster. You will also learn how to expose your app to the internet and architect apps that are designed to be horizontally scalable.

      1. Managing containers at scale

      2. The battle of container orchestrators

      3. Visualising the data centre as a single VM

      4. The scheduler is the best Tetris player

      5. Kubernetes as an infrastructure as a service provider

      6. What are Pods, Services, and Ingresses?

      7. Creating a local cluster with minikube

      8. Creating a Deployment

      9. Exposing Deployments

      10. What is a Pod?

      11. Scaling applications

      12. Testing resiliency

   3. 3. Deployment strategies

      Lecture + hands-on labs + challenges

      Every time you deploy new features in production, you shouldn't stop your app, change the version and start it again. With zero-downtime deployments, no one notices any glitch while you're upgrading your apps. How does that work in Kubernetes? In this course, you will learn how Services work in Kubernetes and how you can roll out changes with zero downtime using rolling updates. You will also learn about Canary Deployments and Blue-green deployments.

      1. Monitoring for uptime

      2. Liveness probe

      3. Readiness probe

      4. Startup probe

      5. Executing zero downtime deployments with rolling updates

      6. Using labels and selectors

      7. Testing features with canary deployments

      8. Releasing features with blue-green deployments

      9. Understanding rollbacks and ReplicaSets

2. Day 2

   1. 1. Templating Kubernetes resources

      Lecture + hands-on labs

      Resources in Kubernetes are described as YAML files. If you wish to have the same resources for different environments such as development, preproduction and production, you may be tempted to copy the files three times. Or you could use a templating engine. In this course, you will learn how to do that with Helm, Kustomize or with your programs in any language.

      1. Creating reusable templates

      2. Helm's templating engine

      3. Understanding the Helm architecture

      4. Templating resources with Go and Sprig

      5. Managing releases with Helm

      6. Reverting changes with rollbacks

      7. Depending on other charts

      8. Storing reusable templates in repositories

      9. Structured templating introduction with YQ

      10. Kubernetes specific structured templating with Kustomize

      11. Using Kubernetes SDKs for templating

   2. 2. Kubernetes Architecture

      Lecture + hands-on labs

      Can Kubernetes recover from failures? In this course, you will learn the Kubernetes core components by building a cluster from scratch using kubeadm. But the best way to learn something is by breaking it. So you will also break the cluster one node at the time and observe what happens.

      1. Single and multi-node clusters

      2. Examining the control plane

      3. Persisting changes in etcd

      4. Syncing changes with RAFT

      5. Event-based architecture

      6. Understanding the kubelet

      7. Verifying "no single point of failure"

      8. Setting up a multi-master cluster

      9. Investigating multi-master setup in EKS

      10. Exploring multi-master setup in Monzo

      11. Creating a 3 node cluster with kubeadm

      12. Installing an overlay network

      13. Installing an Ingress controller

      14. Exploring the API without kubectl

      15. Taking down the cluster one node at a time

3. Day 3

   1. 1. Cluster networking and east-west traffic

      Lecture + hands-on labs

      How does Kubernetes handle internal traffic between your microservices? How can two apps in the cluster talk to each other? How is Kubernetes assigning IP addresses to Pods and Services? In this course, you will explore how the traffic is routed inside the cluster.

      1. Network challenge with multiple nodes

      2. Network routing recap

      3. Understanding network requirements

      4. Understanding cluster address limits

      5. Assigning IP addresses

      6. The challenge of service discovery

      7. Exploring the Endpoints

      8. Balancing in-cluster traffic

      9. Routing traffic with kube-proxy

      10. Discovering Service types: headless and ClusterIP

      11. Network security for east-west traffic

      12. Network policy targets

      13. Network policy best practices

   2. 2. North-south traffic and Service Meshes

      Lecture + hands-on labs

      How to expose application frontends to the internet from a Kubernetes cluster? What's the solution for Layer 4 and Layer 7? In this course, you will learn about more Service types, and the Ingress.

      1. Layer 4 solution to expose a service

      2. The details of using Nodeport

      3. Provision loadbalancers automatically

      4. Helping out the world to save on IPs

      5. HTTP based routing for domains and paths

      6. Routing traffic with Ingress manifests

      7. The battle of Ingress controllers

      8. End-to-end packet journey

      9. Service mesh use-cases

      10. The ins and outs of service meshes

   3. 3. Advanced scheduling

      Lecture

      Master advanced placements of workloads in your infrastructure. Learn how to schedule machine learning deployments to nodes with GPU or how you can segregate workloads for regions (useful if you need to comply with policies and regulations).

      1. How the Scheduler works in Kubernetes

      2. Filters and predicates

      3. nodeSelector

      4. Node affinity

      5. Pod affinity/anti-affinity

      6. Taints and tolerations

      7. Topology Spread Constraints

      8. Custom schedulers

4. Day 4

   1. 1. Managing state in Kubernetes

      Lecture + hands-on labs

      How does Kubernetes store state? Can you host databases in your cluster? Can you extract configurations and share them with different deployments? How do you make sure that your storage layer is replicated and persisted even if a node becomes unavailable? In this course, you will learn how to deploy a database with durable persistence.

      1. Managing configurations

      2. Managing secrets

      3. Using Kubernetes Volumes

      4. Creating Persistent Volumes

      5. Creating Persistent Volume Claims

      6. Provisioning volumes dynamically

      7. Managing stateful applications

      8. Deploying a single database with persistence

      9. Deploying a clustered database with persistence

   2. 2. Autoscaling

      Lecture + Hans-on labs

      After deploying your app to production, the received traffic may change in unpredictable ways. How do you keep your app responsive at all times? You can adapt the number of replicas. But is it feasible to do this manually, or are there better ways? In this course, you will learn how to autoscale an application based on an application-specific custom metric.

      1. Introduction to autoscaling

      2. The Horizontal Pod Autoscaler

      3. The Kubernetes metrics registry

      4. Exposing metrics from your apps

      5. Installing and configuring Prometheus

      6. Understanding custom and external metrics adapters

      7. Tuning the Horizontal Pod Autoscaler

   3. 3. Security

      Lecture

      Wear your black hat and try to break the cluster. Study mitigation and countermeasure to secure your cluster against malicious attacks.

      1. Attack matrix of threats

      2. Security for Docker apps

      3. Security for Kubernetes clusters

      4. Security for Kubernetes networking

      5. Authentication in Kubernetes

      6. Role-based access control

What are the prerequisites for the Kubernetes course?

• Knowledge of basic Linux commands and navigation.
• Familiarity with Linux networking.
• Some experience with reverse proxies such as Nginx or HAProxy.
• Exposure to Virtual Machines.
• A laptop with 8GB of memory and 20GB of space available.
• Windows, macOS, Ubuntu (or your favourite Linux distribution).

The LearnKube guarantee: our promise to you

We care more about our students' success than taking their money.

If you follow the lectures and practise the material (without being distracted by your day to day duties) and still DO NOT feel like you made any progress, we'll give you a full refund.

We're honest to the end about the level of effort, skills, and other ingredients required.

This is not a watch someone else presenting a PowerPoint and become an expert type of course. The learning curve is steep; then, the plateau of usefulness is very long and smooth. It's a great feeling operating Kubernetes after you've mastered it.

Frequently asked questions