Kubernetes training for teams running real systems

Instructor-led Kubernetes training for engineering teams, delivered privately and tailored to your platform, workloads, and goals.

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  • Launch to production with confidence, because engineers understand shutdown behavior, probes, resource sizing, rollout strategy, dashboards, alerts, rollback, and on-call visibility.
  • Migrate workloads to Kubernetes without carrying over old assumptions about deployments, networking, ownership, and day-two operations.
  • Take over an inherited cluster and know what is safe to change, what needs attention, and where the operational risks are hiding.
  • Get developers, platform engineers, and operators working from the same mental model, so more people can deploy and troubleshoot safely on the shared platform.

This is a full-time course on learning and mastering Kubernetes.

Things you need to know about the course:

  • The training is available in person or via online remote learning, giving choice and flexibility.
  • Engaging learning, which is 40% lecture and 60% hands-on lab-based. You will get practical knowledge, not just bland theory.
  • We teach small groups so that you can ask questions and dig into the concepts — everyone has the chance to take part and deep dive into the concepts.
  • You will have access to all the material even after completing the training.
  • It's beginner-friendly, but you will learn some pretty advanced topics too.

On this course, there'll be:

  • No death by PowerPoint. Yes, there are slides, but the content is immersive, relevant and hands-on, applied to real-life scenarios.
  • No boredom central. You won't be passively listening to the instructors; you'll need to answer questions and get actively involved in the sessions.
  • No pushy sales guys. We are vendor-neutral, with no interest in "selling" or suggesting a particular vendor. We're unbiased and will only recommend tools that we know will work for you.

You can choose from a three, four or five day course – whatever works best for you. A typical schedule for a 4 day course is as follows:

    1. 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. 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. 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

    1. 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. 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

    1. 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. 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. 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

    1. 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. 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. 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

In private classes, you can:

  • Customise your schedule, liaising with our expert consultants to devise your programme of learning from a choice of topics;
  • Even skip the basics if you don't need to learn them!

Where's a list of the most popular requests for customisation:

  • Machine learning pipelines in Kubernetes.
  • Kubernetes on the edge and IoT.
  • Kubernetes for on-premise clusters.
  • Kubernetes for highly regulated (or air-gapped) environments.
  • Kubernetes on Amazon Web Service (AWS) with EKS.
  • Kubernetes on Azure with AKS.
  • Kubernetes on Google Cloud with GKE.
Speak to an instructor

Success! We sent you a confirmation email and an instructor will be with you as soon as possible.

  • Lifetime access to the online material.
  • All the slide decks.
  • A virtual workstation in the cloud for each delegate for the duration of the course.
  • Lifetime access to the private Slack channel where your team can always ask for help.
  • A certificate of completion signed by the instructor.

LearnKube has been delivering Kubernetes training since 2017.

We have worked with hundreds of teams across different industries, cluster sizes, and maturity levels.

This experience gives us a wide view of what often goes wrong in production and what teams usually miss before making changes.

During the training, we use your context to make Kubernetes concrete: deployments, scaling, networking, security, observability, and ownership are explained through the decisions your engineers actually face.

The goal is shared operating confidence. Your team leaves with a common model of how Kubernetes behaves, where the risks are, and how to make safer decisions together after the course.

Companies trusting LearnKube training include

Teams consistently mention the depth, practical labs, and the ability to connect Kubernetes concepts to the systems they work with every day.

  • "The technical depth of demos and deep-dive explanations - so much better than any of the many online on-demand classes I've taken."

    - Dana Finster, Walmart

  • "Ability to ask questions and apply what we're learning to the specific use cases of our org. Sal was great at fielding our questions and engaging with us."

    - Chris, Bluestaq

  • "I really liked how well everything was structured and how a lot of concepts would fall back towards previous lessons to paint a bigger picture on how Kubernetes operates as a whole."

    - Jonathan, Coinbase

  • "The clear layout of all learning modules, and the flexibility to focus on more relevant areas than others."

    - Nathaniel Casely-Hayford, EDF

  • "It was the most comprehensive course I have ever taken. It made me feel like I am ready to use Kubernetes immediately."

    - Simon, Tromero

  • "This course is very good in explaining the basic and advanced topics of Kubernetes and it was presented in a very digestible, and easy to understand format."

    - James Seaman, Sabel Systems

Instructor-led Kubernetes training for engineering teams, delivered privately and tailored to your platform, workloads, and goals.

Request a private training proposal

Success! We sent you a confirmation email and an instructor will be with you as soon as possible.

Download the private training brief →

Private training helps your team build the skills to operate Kubernetes, but sometimes the first question is simpler:

Is the cluster actually ready for production?

A LearnKube instructor can review your manifests, architecture, deployment process, dashboards, alerts, runbooks, and operational assumptions with your engineers. We check the production risks, explain what needs attention, and turn the findings into clear next steps for your team.

Book a production readiness review

Software developers, Data engineers, Architects and DevOps seeking to learn how to use Kubernetes to automate deployment, scaling and management of containerised applications.

You will receive the joining instructions with all the material needed to run the course after you sign up for the course.

We can run private courses starting from only 5 delegates but only in specific cases. Otherwise, the minimum class size is 10 delegates. If you are not sure, please get in touch to discuss.

Yes. Private training gives the team the Kubernetes foundation behind CKA and CKAD exams, and we can shape the course around exam-relevant areas such as workloads, services, networking, storage, troubleshooting, scheduling, and security. It helps engineers prepare faster because they understand the system, not just the commands.

Sure - send an email to hello@learnkube.com.