LEARNING PATH: Learning Docker and Kubernetes
What you'll learn
- Learn the core Kubernetes architecture, concepts, and highly-available deployments at-scale and in depth
- Grasp industry-proven standards and patterns for deploying apps to Kubernetes
- Learn how to configure the Docker daemon, troubleshooting containers and images, and using continuous integration techniques to automatically build and test Docker images
- Learn deployment patterns and concepts for making Kubernetes highly-available
- Manage a local Kubernetes deployment using MiniKube
- Build images automatically with GitLab
- Kubernetes knowledge is not required
- Familiarity with basic concepts of Docker will make the course easier.
Docker is a portable container format that allows you to run code anywhere from your desktop to the cloud. Docker's workflow makes development, testing, and deployment much easier and much faster. Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. To deploy Docker for real-world applications and gain hands-on experience with, deploying and managing market leading cloud platforms, you must be familiar with the basic concepts of Docker.
This comprehensive 2-in-1 course teaches you to deploy and manage applications on leading cloud platforms, such as Docker and Kubernetes. You’ll learn through practical demonstrations, clear explanations, and interesting real-world examples. It will give you a versatile range of Docker and Kubernetes skills, which you will put to work in your own applications.
This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.
The first course, Learning Kubernetes, starts off with basic installation of Kubernetes and all its dependencies. You will then learn deployment patterns and concepts for making Kubernetes highly-available. You will also learn how to manage a local Kubernetes deployment using MiniKube, Next, you will understand how to use secrets in your applications by creating and decoding secrets. You will learn to deploy your docker applications on Kubernetes.
The second course, Working with Advanced Docker Operations, teaches you how to create pods and multi-container pods. You will then learn how to use services and volumes with pods such as labels and selectors, Kubernetes services, creating secrets and ConfigMaps, and plain and persistent volumes.You will also learn how to install the ELK stack, view logs in Kibana, and view performance data in Grafana. Next, you will learn how to use continuous integration techniques to automatically build and test Docker images. You will be glanced through some use cases on containers wherein each use case highlights a particular problem and you will find how Docker helps solve it.
By the end of this training program, you’ll be able to use Kubernetes orchestration system, monitor Docker cluster, and automate your applications to build, test, and deploy.
Meet Your Expert(s):
We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:
● Braithe E.S. Warnock is currently a managing cloud architect for the financial services division of Ernst & Young. He has had the opportunity to work with several of the largest PCF installations on an international scale. He helped build the framework for the adoption of PCF at top companies such as Ford, Comcast, DISH, HSBC, and Charles Schwab. As a vendor-neutral consultant, he enjoys helping people understand the rapidly-evolving world of cloud and application architecture. He has more than six years of experience and specialization in global digital transformations. He has expertise in various cloud and cloud platform technologies (PCF, AWS, Azure, VMware, Netflix OSS, Kubernetes, and OpenShift) and also the Java and Spring Boot frameworks. He has developed over 100 microservices using Spring Boot, Java 7/8, Spring Cloud, and Netflix OSS, spanning half a dozen unique cloud-native microservice architectures. He also has experience in developing machine learning models using AWS, Spark, and MLlib to support product recommendations and enhance customer data.
● Randall Smith is a senior systems administrator at Adams State University. He has been administering Windows, Linux, and BSD systems since 1999.He has been active in helping other sysadmins solve problems online and off. He has presented at the Colorado Higher Ed Computing Organization and Educause conferences on topics including Linux KVM and Ceph.In his spare time, Randall streams Let's Play gaming videos at Music Free Gaming on YouTube and Twitch.
Who this course is for:
- This Learning Path is for developers, architects, system administrators, and other technologists who want to learn about and gain hands-on experience with, deploying and managing market leading cloud platforms.
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