When you enroll through our links, we may earn a small commission—at no extra cost to you. This helps keep our platform free and inspires us to add more value.
Leveraging Advanced Features on the Google Cloud Kubernetes Engine
This course specifically deals with some advanced, real-world use-cases involving the use of GKE including rolling updates and rollbacks, managing cluster security and networking, and implementing CI/CD pipelines with Jenkins and the GKE.
This Course Includes
pluralsight
4 (15 reviews )
2 hour 31 minutes 
english
Online - Self Paced
core courses
pluralsight
About Leveraging Advanced Features on the Google Cloud Kubernetes Engine
Kubernetes is a container orchestration technology that is fast emerging as the most popular computing option for hybrid and multi-cloud architectures. A key attraction of Kubernetes is its suitability for use cases involving Continuous Integration and Continuous Delivery (CI/CD); however, building such pipelines can get quite complicated. In this course, Leveraging Advanced Features on the Google Cloud Kubernetes Engine, you will gain the ability to fine-tune the networking and security aspects of your GKE clusters, as well as to orchestrate complex CI/CD pipelines on the Google Cloud Platform.
First, you will learn the deployment of stateful and stateless applications, jobs and cron jobs. Next, you will discover the uses of network policies, private clusters, and pod-security policies. Finally, you will explore how to pull together Jenkins, Cloud Source Repositories, and the Google Container Registry to orchestrate a CI/CD pipeline."
When you’re finished with this course, you will have the skills and knowledge of the Google Kubernetes Engine needed to fine-tune your clusters and construct CI/CD pipelines with minimal effort.
What You Will Learn?
- Course Overview : 2mins.
- Creating and Managing Deployments on GKE Clusters : 64mins.
- Working with Networking and Security on GKE Clusters : 40mins.
- Leveraging Continuous Integration and Continuous Delivery (CI/CD) Using GKE : 43mins.