Prep for Certified Kubernetes Administrator (CKA)

Duration

5 Day

Course Code

BDT397

Available Formats

Instructor-Led Online and Classroom

Description:

This comprehensive course provides a deep dive into Kubernetes administration, covering all aspects of Kubernetes clusters, including installation, configuration, networking, storage, and security. Participants will learn how to configure and manage clusters in both test and production environments, troubleshoot common issues, and implement best practices. This bootcamp prepares participants for the CKA exam and provides hands-on experience with Kubernetes components, managing workloads, and networking configurations essential for Kubernetes administrators.

Duration: 5 Day

Course Code: BDT397

Learning Objectives:

By the end of the training, participants will:

Understand the architecture and components of Kubernetes clusters
Deploy, configure, and manage Kubernetes clusters
Work with Kubernetes networking and storage solutions
Troubleshoot and manage workloads within Kubernetes
Prepare for the Certified Kubernetes Administrator (CKA) exam

This course is intended for IT professionals, DevOps engineers, system administrators, and cloud architects who want to become certified in Kubernetes administration. It is also suitable for individuals responsible for managing and deploying Kubernetes clusters in production environments.

Familiarity with Linux command-line operations
Basic knowledge of containers (Docker recommended)
Understanding of basic cloud and networking concepts

Course Outline:

Module 1: Introduction to Kubernetes and Cluster Architecture

Overview of Kubernetes: History, architecture, and components
Kubernetes Components:
- Master components (API Server, Scheduler, Controller Manager, etcd)
- Node components (kubelet, kube-proxy, container runtime)
Cluster Architecture: Nodes, pods, namespaces, deployments, and services
Installation Methods: kubeadm, kubectl, and minikube
Hands-On Labs:
- Setting up a Kubernetes cluster using Minikube
- Exploring cluster components and architecture
- Understanding and creating namespaces

Module 2: Kubernetes Installation and Configuration

Cluster Setup: Using kubeadm to install Kubernetes
Configuring Networking for Kubernetes: CNI plugins, network policies, and service networking
Control Plane and Node Management: Managing API server, scheduling, and configuring worker nodes
Cluster Add-Ons: CoreDNS, metrics server, and dashboard installation
Hands-On Labs:
- Setting up Kubernetes clusters using kubeadm
- Configuring Calico or Flannel for network policies
- Installing and configuring Kubernetes add-ons

Module 3: Workloads and Scheduling

Managing Kubernetes Workloads:
- Pods, ReplicaSets, Deployments, and DaemonSets
- Configuring Jobs and CronJobs for scheduled workloads
Advanced Scheduling:
- Node selectors, affinities, and anti-affinities
- Taints and tolerations to control pod placement
Scaling and Self-Healing: Horizontal Pod Autoscaler and health checks
Hands-On Labs:
- Deploying and managing Kubernetes workloads
- Configuring job automation with CronJobs
- Implementing node affinity and tolerations

Module 4: Networking in Kubernetes

Kubernetes Networking Basics: Cluster IPs, NodePort, LoadBalancer, and Ingress
Configuring Services and Ingress:
Service types and DNS within clusters
Ingress resources for managing external access
Network Policies: Restricting traffic within Kubernetes with network policies
Hands-On Labs:
- Creating services and exposing workloads
- Configuring Ingress to manage HTTP and HTTPS traffic
- Defining network policies to control pod communications

Module 5: Storage Management in Kubernetes

Persistent Storage in Kubernetes:
- Persistent Volumes (PV) and Persistent Volume Claims (PVC)
- Configuring StorageClasses
Dynamic Provisioning: Integrating with cloud storage providers (e.g., AWS EBS, GCE PD)
Volume Types and Data Persistence: EmptyDir, hostPath, ConfigMaps, and Secrets
Hands-On Labs:
- Configuring Persistent Volumes and Persistent Volume Claims
- Using ConfigMaps and Secrets to store sensitive data
- Integrating external storage for persistent data

Module 6: Security and Access Control

Authentication and Authorization:
- Role-Based Access Control (RBAC) and service accounts
- API server access and security contexts
Network Security: Pod security policies and enforcing isolation
Kubernetes Secrets Management: Storing sensitive data securely
Hands-On Labs:
- Configuring RBAC to manage access control
- Implementing pod security policies
- Using Secrets to manage sensitive information in applications

Module 7: Troubleshooting and Monitoring

- Troubleshooting Kubernetes:
  - Common cluster issues and diagnostic tools

Debugging workloads and node failures

- Monitoring and Logging:
  - Configuring Prometheus, Grafana, and the ELK stack
  - Working with Kubernetes logs
Hands-On Labs:
Diagnosing and troubleshooting cluster issues
Setting up Prometheus and Grafana for cluster monitoring

Module 8: Exam Preparation and Practice

- - CKA Exam Overview: Structure, domains covered, and scoring
  - Preparation Tips and Resources: Time management, documentation, and practical tips
  - Practice Labs and Mock Exams:
  - OS-level troubleshooting and real-world cluster management scenarios
  - Mock exam scenarios similar to CKA to test and reinforce learning

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I completed the Big Data Developer and Mentorship Program. The course is very informative and interactive. A well defined plan, course contents (labs, extra course material, offshore support team) and tracking system help us learn each component with ease and helps us stay focused.

Java/Hadoop Developer

Overall the content of this training was very good and it provided all details required in slideshow. The trainer was also knowledgeable and was able to clarify the questions raised during the training.

Director

This was an excellent introductory class for a non-specialist that provided me with exactly the kind of foundation and background I was seeking. I would recommend it highly to anyone who wants to understand more about the subject or to use it as the first steps in getting into the field. It will help me evaluate proposals we receive and also guide faculty, staff and students on whether they might benefit from using ML/AI in their work.

Senior Manager

It was extremely helpful to have the beginning of the day explaining more about the background of data governance/etc. I did find that the Tableau exercise was helpful conceptually but I still don’t know if I feel like I know anything about the product. Overall, this was extremely helpful though! Thank you!

Data Architect

I thought Instructor did a great job in these difficult times. One suggestion would be to come up with a uniform plan for acknowledging questions and stick to it throughout the course. I feel like this course met my needs as a beginner to AWS and can’t wait to do more labs. Thanks.

Data Engineer

I love the way he taught Machine Learning class. He started with theory and followed up with some hands-on example of his own. Then he gave students to do some work based on the topics he covered. Also, he always tried to make class interactive, encouraged students to ask questions and clarified almost unlimited time if there are any questions. He is a great instructor and I love to take class with him in future.

Software Developer

I am very interested in further training in Machine Learning and Neural Network and would like to know which course to take next. This is exactly the class I have been looking for to try and set up my project of creating a “smart” medical record system. I would love to be in touch with Instructor in the future to get more advice.

Healthcare Practitioner

Run-through of all concepts. Learning the basic concept of GCP and connecting dot with my work. Simple concepts explained. Holding students attention in an 8 hours virtual class is not easy. I appreciate Instructor’s calm attitude and answering every question asked.

Director

The course was very well presented. An all-day Zoom class is challenging but it was interesting. I thought some of the exercises and quizzes could be made a little more advanced or challenging, but they are good for a general audience.

Software Developer

Large bulk of information being provided in the course as well as really good in depth explanations. The practice exercises are very helpful and I will be referring to them post the class completion.

Software Architect

We just wanted to reiterate our thanks for providing the Intro to ChatGPT training! We had so many individuals very interested in this topic and appreciate your guidance and graciousness in facilitating their learning. We hope to work with you in the future to provide additional sessions.

Project Manager

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