Kubernetes Training: Learn K8s from Zero to Cloud
What you'll learn
- Deploy containerized applications using Kubernetes pods
- Implement service discovery for inter-application communication
- Organize and isolate resources using Kubernetes namespaces
- Scale applications using Kubernetes Deployments
- Deploy databases using StatefulSets and manage storage with Persistent Volumes
- Separate configuration from code using ConfigMaps and Secrets
- Implement automatic scaling with Horizontal Pod Autoscaler (HPA)
- Manage external access to services using Ingress Controllers
- Streamline application deployment using Helm Charts
- Automate complex application management with Kubernetes Operators
- Deploy a Kubernetes cluster to Amazon Web Services (AWS)
- Understand and apply Kubernetes' self-healing and resilience features
- Perform rolling updates and rollbacks for zero-downtime deployments
- Implement health checks using Liveness and Readiness probes
- Use the Kubernetes CLI and VS Code extensions for efficient cluster management
Requirements
- Familiarity with any programming language will be helpful, but no expert-level skills are required.
- Some comfort with using command-line interfaces will be beneficial, but we'll review essential commands.
- You'll need a computer (Windows, Mac, or Linux) with a stable internet connection to follow along with the hands-on exercises.
- A basic understanding of containerization concepts is recommended. However, we provide an optional Docker crash course for those new to containerization.
- The most important prerequisite is enthusiasm and a desire to learn about cloud-native technologies!
Description
Since its open-source release by Google in 2014, Kubernetes has revolutionized cloud computing. Now supported by major cloud providers like AWS, Azure, and Google Cloud, it's the industry standard for managing cloud-native applications at scale.
This End-to-End Kubernetes training course will guide you through developing and deploying cloud-native applications on Kubernetes. From foundational concepts to advanced techniques, you'll gain hands-on experience with key Kubernetes features and best practices. The course culminates in a real-world deployment to Amazon Web Services (AWS), providing you with practical, applicable skills for cloud-native development.
By the end of this course, you will be able to:
Deploy containerized applications using Kubernetes pods
Implement service discovery for inter-application communication
Organize and isolate resources using Kubernetes namespaces
Scale applications using Kubernetes Deployments
Deploy databases using StatefulSets and manage storage with Persistent Volumes
Separate configuration from code using ConfigMaps and Secrets
Implement automatic scaling with Horizontal Pod Autoscaler (HPA)
Manage external access to services using Ingress Controllers
Streamline application deployment using Helm Charts
Automate complex application management with Kubernetes Operators
Deploy a Kubernetes cluster to Amazon Web Services (AWS)
Understand and apply Kubernetes' self-healing and resilience features
Perform rolling updates and rollbacks for zero-downtime deployments
Implement health checks using Liveness and Readiness probes
Use the Kubernetes CLI and VS Code extensions for efficient cluster management
Enroll in our Kubernetes Bootcamp today and gain the practical skills you need to effectively orchestrate your cloud native projects.
Who this course is for:
- Software developers looking to transition to cloud-native development
- Students and professionals wanting to future-proof their careers in cloud computing
- DevOps engineers seeking to enhance their Kubernetes skills
- Cloud architects interested in mastering Kubernetes for large-scale deployments
- Anyone with basic Docker knowledge looking to advance their container orchestration skills
Instructors
- 4.6 Instructor Rating
- 1,267,061 Reviews
- 4,249,682 Students
- 87 Courses
Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, SalesForce, Starbucks, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.
- 4.5 Instructor Rating
- 560 Reviews
- 230,486 Students
- 2 Courses
Senior DevOps Engineer with over a decade of software development experience, now leading high-impact initiatives in DevOps and cloud-native solutions. I’m passionate about simplifying complex technologies and empowering developers to thrive in modern software environments. Through my courses, I’ve mentored over 250,000 students worldwide on container orchestration, CI/CD pipelines, and best practices for building scalable, resilient systems. My mission is to bridge the gap between theory and real-world application—ensuring that learners walk away with the practical skills and confidence to excel in today’s fast-evolving tech landscape.
- 4.5 Instructor Rating
- 30,828 Reviews
- 203,756 Students
- 9 Courses
Jad studied mechanical engineering at the University of Ottawa. Jad also has extensive experience in software development, cloud development, machine learning, computer vision, mathematical modeling, computer simulation, and intelligent systems. Jad has also developed many deep learning applications, and is currently pursuing an interest in autonomous machines and Full Stack Development.
- 4.5 Instructor Rating
- 19,697 Reviews
- 149,368 Students
- 7 Courses
Hi I'm Amer. I'm a full-time developer with a specialized interest in Artificial intelligence (AI). AI is now taking on more sophisticated roles that can truly amplify human capabilities.
With a background in Mechanical Engineering and computer science I have always looked for ways to use the power of AI to create practical solutions that revolutionize the way we live.
I aim to make artificial intelligence more accessible to all students, no matter the skill level!
- 4.6 Instructor Rating
- 25,858 Reviews
- 156,557 Students
- 7 Courses
Hi! I'm Sarmad, and I have graduate level expertise in Mechanical Engineering. My main areas of interest and research include autonomous robotics, self driving car technology and machine learning. I currently work as a Senior Machine Learning Engineer with the Government of Canada.
In my spare time, I enjoy teaching courses on Udemy and sharing my knowledge with all of you!
- 4.5 Instructor Rating
- 34,541 Reviews
- 198,502 Students
- 9 Courses
Rayan is a seasoned DevOps Engineer who transforms complex cloud-native technologies into accessible knowledge. With over a decade of experience, he's guided 250,000+ students through container orchestration, CI/CD, and building resilient systems.
Join Rayan and follow his latest DevOps content to bridge the gap between theory and real-world implementation.