Instructor-led Kubernetes training for engineering teams, delivered privately and tailored to your platform, workloads, and goals.
Send us an email at hello@learnkube.com.
Send us a message:
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This is a full-time course on learning and mastering Kubernetes.
Things you need to know about the course:
On this course, there'll be:
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:
Day 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.
Containers vs VMs
Understanding process isolation
Is Docker the only one?
Docker client-server architecture
Running containers
Building Docker images
Mounting volumes
Exposing ports
Managing containers lifecycle
Injecting environment variables
Debugging running containers
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.
Managing containers at scale
The battle of container orchestrators
Visualising the data centre as a single VM
The scheduler is the best Tetris player
Kubernetes as an infrastructure as a service provider
What are Pods, Services, and Ingresses?
Creating a local cluster with minikube
Creating a Deployment
Exposing Deployments
What is a Pod?
Scaling applications
Testing resiliency
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.
Monitoring for uptime
Liveness probe
Readiness probe
Startup probe
Executing zero downtime deployments with rolling updates
Using labels and selectors
Testing features with canary deployments
Releasing features with blue-green deployments
Understanding rollbacks and ReplicaSets
Day 2
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.
Creating reusable templates
Helm's templating engine
Understanding the Helm architecture
Templating resources with Go and Sprig
Managing releases with Helm
Reverting changes with rollbacks
Depending on other charts
Storing reusable templates in repositories
Structured templating introduction with YQ
Kubernetes specific structured templating with Kustomize
Using Kubernetes SDKs for templating
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.
Single and multi-node clusters
Examining the control plane
Persisting changes in etcd
Syncing changes with RAFT
Event-based architecture
Understanding the kubelet
Verifying "no single point of failure"
Setting up a multi-master cluster
Investigating multi-master setup in EKS
Exploring multi-master setup in Monzo
Creating a 3 node cluster with kubeadm
Installing an overlay network
Installing an Ingress controller
Exploring the API without kubectl
Taking down the cluster one node at a time
Day 3
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.
Network challenge with multiple nodes
Network routing recap
Understanding network requirements
Understanding cluster address limits
Assigning IP addresses
The challenge of service discovery
Exploring the Endpoints
Balancing in-cluster traffic
Routing traffic with kube-proxy
Discovering Service types: headless and ClusterIP
Network security for east-west traffic
Network policy targets
Network policy best practices
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.
Layer 4 solution to expose a service
The details of using Nodeport
Provision loadbalancers automatically
Helping out the world to save on IPs
HTTP based routing for domains and paths
Routing traffic with Ingress manifests
The battle of Ingress controllers
End-to-end packet journey
Service mesh use-cases
The ins and outs of service meshes
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).
How the Scheduler works in Kubernetes
Filters and predicates
nodeSelector
Node affinity
Pod affinity/anti-affinity
Taints and tolerations
Topology Spread Constraints
Custom schedulers
Day 4
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.
Managing configurations
Managing secrets
Using Kubernetes Volumes
Creating Persistent Volumes
Creating Persistent Volume Claims
Provisioning volumes dynamically
Managing stateful applications
Deploying a single database with persistence
Deploying a clustered database with persistence
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.
Introduction to autoscaling
The Horizontal Pod Autoscaler
The Kubernetes metrics registry
Exposing metrics from your apps
Installing and configuring Prometheus
Understanding custom and external metrics adapters
Tuning the Horizontal Pod Autoscaler
Lecture
Wear your black hat and try to break the cluster. Study mitigation and countermeasure to secure your cluster against malicious attacks.
Attack matrix of threats
Security for Docker apps
Security for Kubernetes clusters
Security for Kubernetes networking
Authentication in Kubernetes
Role-based access control
In private classes, you can:
Where's a list of the most popular requests for customisation:
Send us an email at hello@learnkube.com.
Send us a message:
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
We are Kubernetes practitioners with experience in:
We were also selected to speak at KubeCon — the world's largest Kubernetes and Cloud-Native conference. You can watch the tech talks here:
You can chat with us on the LearnKube's Telegram Group!
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.
Send us an email at hello@learnkube.com.
Send us a message:
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 reviewSoftware 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.