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Introduction to Kubernetes

Standard Course
Intermediate
Early Access

About the Course

Explore Kubernetes architecture, cluster setup, workload management, networking, and monitoring. Gain hands-on experience configuring components to efficiently manage containerized applications at scale.

Learning Outcomes

By the end of this course, participants will be able to:

  • Understand Kubernetes Architecture
  • Set up and configure Kubernetes clusters
  • Manage workloads efficiently
  • Implement networking and security
  • Monitor and troubleshoot clusters

Curriculum

  • Chapter 1: Kubernetes Fundamentals and Architecture

    Overview:

    Gain a comprehensive understanding of Kubernetes architecture, core components, and containerization essentials.

    Topics to Cover

    • Containers vs. Virtual Machines
    • Kubernetes Core Concepts and Use Cases
    • Kubernetes Architecture: Control Plane, Nodes, Pods, and etcd
    • Core Components: API Server, Scheduler, Controller Manager, Kubelet, Kube-proxy

  • Chapter 2: Cluster Installation and Configuration

    Overview:

    Learn to set up, configure, and validate Kubernetes clusters on local and cloud environments.

    Topics to Cover

    • Installation Options: Minikube, Docker Desktop
    • Configuring the Cluster: Networking, Initial Setup, and Cluster Verification
    • Essential kubectl Commands for Cluster Management
    • Configuring Networking Components: CNI Plugins

  • Chapter 3: Workloads and Scheduling

    Overview:

    Master workload management and scheduling strategies in Kubernetes to run applications reliably.

    Topics to Cover

    • Pods, ReplicaSets, Deployments, and StatefulSets
    • Managing Jobs and CronJobs
    • Labels, Selectors, and Annotations
    • Configuring Node Selectors, Taints, and Tolerations
    • Resource Requests and Limits for Optimized Scheduling

  • Chapter 4: Services and Networking

    Overview:

    Learn to expose applications and manage networking within Kubernetes for cluster-wide and external access.

    Topics to Cover

    • Services: ClusterIP, NodePort, LoadBalancer
    • Networking Policies: Implementing Isolation and Security
    • Ingress: Configuring Rules, Load Balancing, and Custom Routing
    • Core DNS for Service Discovery
  • Chapter 5: Storage Management and Configuration

    Overview:

    Understand Kubernetes storage mechanisms and how to manage configurations for secure and persistent application data.

    Topics to Cover

    • Kubernetes Storage Fundamentals: Volumes, Persistent Volumes, and Persistent Volume Claims
    • Storage Classes and Dynamic Provisioning
    • ConfigMaps and Secrets for Application Configuration Management
    • Managing Sensitive Data and Best Practices for Security
  • Chapter 6: Security and Cluster Hardening

    Overview:

    Secure your Kubernetes cluster by implementing role-based access and network policies.

    Topics to Cover

    • Kubernetes Security Fundamentals: Role-Based Access Control (RBAC)
    • Network Policies for Pod-Level Security
    • Securing Access to the Kubernetes API Server
    • Authentication, Authorization, and Admission Control
  • Chapter 7: Monitoring, Logging, and Troubleshooting

    Overview:

    Learn essential methods for monitoring, logging, and troubleshooting to ensure a healthy Kubernetes environment.

    Topics to Cover

    • Troubleshooting Tools: kubectl Debugging Commands, Logs, and Events
    • Diagnosing Pod, Node, and Cluster Issues
  • Chapter 8: Application Lifecycle and Configuration Management

    Overview:

    Understand best practices for managing application lifecycles and configurations in Kubernetes.

    Topics to Cover

    • Managing Application Deployments and Rollbacks
    • Horizontal Pod Autoscaling and Cluster Autoscaler
    • Implementing Rolling Updates and Canary Deployments
    • Helm Basics for Application Management
  • Chapter 9: Advanced Topics and Best Practices

    Overview:

    Deepen your knowledge with advanced Kubernetes features and best practices for cluster operations.

    Topics to Cover

    • Custom Resource Definitions (CRDs)
    • Helm for Package Management and Templating
    • Kubernetes Operator Pattern
    • Disaster Recovery Planning: Backup and Restore Methods

Tools

Minikube
Docker Desktop
Kubectl
Kubeadm
Helm
AWS CLI
VS Code
Terminal
Git/GitHub
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STUDENT REVIEWS

What our graduates are saying

I had an incredible experience at this data science bootcamp! Coming in with no prior knowledge, I was amazed at how quickly I gained a solid understanding of the field. The curriculum is intensive and hands-on, allowing me to learn real, applicable skills through working on real client projects. The staff are exceptionally supportive and always ready to help. This bootcamp truly transformed my career path, and I couldn’t be more grateful for the knowledge and confidence I’ve gained. Highly recommended for anyone looking to break into data science!

My experience was awesome. I was taught by professional data engineers who shared their insights based on their professional experience. The topics covered are relevant to what employers are looking for and I enjoyed hands-on projects. I learned all the skills I needed to be a data engineer and I got a full-time offer as a data engineer, thanks to the mentors from WecloudData. I highly recommend this program. I was able to land interviews at Amazon, Yelp, CI Financial e.t.c

Deciding to go with WeCloudData was one of the best decisions I made during my career switch. Their Bootcamps are intense but they get you where you need to go. The instructors are amazing and the TAs very knowledgeable. Their client projects taught me a lot even after the bootcamp was done. I was able to land my current job thanks to the skills and training from the course.

I had the pleasure of attending WeCloudData’s Data Fundamentals bootcamp, which was fantastic. The highly qualified instructors used cutting-edge teaching techniques that greatly facilitated understanding the logic of coding and programming. They carefully progressed us from fundamental to more complex subjects, avoiding any feeling of overload. I wholeheartedly endorse this course for anyone hoping to become a data analyst—it’stheonly one you’ll need. The teachers are very outstanding!

This bootcamp provided me with the necessary technical skills and industry knowledge to secure a data job. The instructors are knowledgeable and shared everything they know to help me achieve my goals. The TAs are resourceful and patient answering my questions. The projects in the bootcamp enhanced my knowledge and impressed interviews. This is a wonderful bootcamp if you are looking to either imporve your skills or switch career!

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Common Questions

Find answers to your questions about the Learning Track
  • Standard Courses: Focused, short courses that build foundational or intermediate skills through hands-on exercises, enabling you to apply what you learn immediately.
  • Track Courses: Structured learning paths that guide you from beginner to advanced levels. They include practical projects that integrate multiple tools and workflows, aligned with industry best practices, helping you gain the skills and confidence to tackle real-world challenges.

No. Track Courses are only accessible through the Professional or Unlimited+ subscription plans.

  • Standard Plan gives you access to all Standard Courses.
  • Professional Plan gives you access to both Standard and Track Courses within your chosen domain.
  • Unlimited+ Plan provides full access to all courses — both Standard and Track — across all domains.

 

Yes, all courses are designed to be self-paced. Learn when it fits your schedule.

Each course includes prerequisites if needed. Many Standard Courses are beginner-friendly.

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