Kubernetes Pro
Course Overview
Inspired by cncf and kubernetes.io, the Kubernetes Pro course is designed for developers and system administrators who want to get more advanced experience with Kubernetes. It is focused on Cloud Native principles and microservices architectures.
This course aligns with Certified Kubernetes Administrator and Certified Kubernetes Application Developer exams from the Cloud Native Computing Foundation. Once you master Kubernetes, you can manage other container-orchestration solutions such as: RedHat Openshift, Rancher, Amazon EKS, Azure AKS, Google GKE, IBM Cloud Kubernetes Service.
What You'll Learn
By the end of this course, you will master:
- Decouple application configuration
- Add state persistence to your application
- Configure cluster authorization and access control
- Autoscale your application based on compute metrics
- Isolate workloads with Network Policies
- Advanced continuous deployment strategies used in Kubernetes
- Zero-downtime cluster upgrades
- Multi-tenant cluster design and implementation
- Bootstrap a Kubernetes cluster
- Use Observability pillars to improve cluster and application reliability
- Complex networking troubleshooting
- Troubleshoot a real K8s application in a 2h “Capture the Flag” session
- And much more!
Who Should Attend
- Developers looking to containerize and orchestrate applications
- DevOps Engineers managing production Kubernetes
- Platform Engineers building Kubernetes platforms
- Site Reliability Engineers ensuring service reliability
- Cloud Architects designing enterprise solutions
- Team Leads responsible for Kubernetes adoption
- Consultants implementing Kubernetes for clients
Course Format
- Duration: 3 days (24 hours)
- Format: Part lecture, part discussion, exercises and heavy hands-on practice.
- Materials: Digital course materials and lab guides
Certification Preparation
This course covers the foundational concepts needed for:
- CKA (Certified Kubernetes Administrator) - Core administration tasks
- CKAD (Certified Kubernetes Application Developer) - Application deployment basics
Difficulty
Intermediate to advanced
Course Prerequisites
To get the most out of this course, you should have:
- Previous experience with linux containers (Docker)
- Basic Linux command line skills
- File editing skills (yaml, json)
- Kubernetes Fundamentals
Course Content
Day 1
- Course introduction
- Course goals
- Recommended lectures
- Kubernetes certifications
- Your practice environment
Persistance in Kubernetes
- Types of Volumes
- Persistent Volume
- Persistent Volume Claim
Lab: Add persistance to an existing application deployed on a K8s cluster
Advanced Kubernetes Networking
- Networking implementation on Kubernetes
- Container Network Interface (CNI)
- CNI Plugins
- TCP/IP model overview
- Isolate workloads with Network Policies
Lab: Secure an application using network policies
Package management with Helm
- Explain Helm Charts
- Working with Chart Repositories
- Helm Releases
Lab: Deploy an application on a K8s cluster using Helm
DaemonSets
- DemonSet overview
- DemonSet vs Deployment
- Manage DaemonSet
Lab: Working with DaemonSets
StatefulSets
- Stateful applications overview
- Stateful vs Stateless applications
- StatefulSets Components
Lab: Deploy a stateful application on a K8s cluster
Day 2
- Jobs and CronJobs
- Parallel and Non-parallel Jobs
- Job Termination and Cleanup
- Working with CronJobs
Lab: Deploy short-lived applications using Jobs and CronJobs on a K8s cluster
Mastering kubectl
- Configuration Best Practices
- Understanding Kubeconfig
- Kubectl cheatsheet
- Kubectl explain
Lab: Boost your kubectl productivity
Role-Based Access Control
- Authorization with RBAC
- Roles and ClusteRoles
- RoleBindings and ClusterRoleBindigs
- Default ClusterRoles
- Working with user permissions at the namespace level
Lab: Create a user with limited access on a K8s namespace
Cluster Administration and Multitenancy
- Type of workloads
- Managing compute allocation and quotas
- Defining policies for resource usage and workload isolation
Lab: Isolate a namespace on a K8s cluster
AI on Kubertnetes: Running ML Model Inference on Kubernetes
- Understanding ML Inference
- Serving Models on Kubernetes
- Packaging & Deploying a Model
Lab: Deploy a Model as a REST API
Day 3
Obervability
- Monitoring Kubernetes components with Prometheus
- Setup prometheus on K8s
- Monitoring an application deployed on K8s cluster
- The Four Golden Signals from Google SRE book
Lab: Use Prometheus to monitor K8s components
Deployment strategies on Kubernetes
- Explain Recreate strategy
- Explain RollingUpdate strategy Explain Blue/Green strategy
- Explain Canary strategy
- Explain A/B testing strategy
- Explain Shadow strategy
Lab: Deploy an application on K8s using Blue/Green and Canary strategies
Troubleshooting and CTF
- Loggging
- Strategies to debug applications and K8s components
- Trooublshooting an application deployed on a K8s cluster
Lab: Solve real K8s application challanges in a 1.5h “Capture the Flag” session
Next Steps
After completing this course:
- Consider specialized workshops (Security, Networking, Storage)
- Pursue advanced certifications (CKS, cloud-specific)
- Join our advanced practitioners community
- Explore custom enterprise training options