Learning Kubernetes
Gain the skills to deploy and manage container-based applications with Kubernetes, the widely-used open-source orchestration engine. Learn how to use Kubernetes to maximize efficiency and scalability. ▼
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Course Feature
Cost:
Free Trial
Provider:
LinkedIn Learning
Certificate:
No Information
Language:
English
Start Date:
Self Paced
Course Overview
❗The content presented here is sourced directly from LinkedIn Learning platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [March 06th, 2023]
This course provides an overview of Kubernetes, the world's most popular open-source container orchestration engine. Participants will learn how to get a Kubernetes environment up and running on Mac or Windows using Minikube, and understand the components for Kubernetes. Additionally, participants will learn how to deploy a more complicated application with a database and APIs, as well as how to run jobs and cron jobs. Finally, more advanced topics on Kubernetes, including production deployments, namespaces, monitoring and logging, and authentication and authorization will be discussed.
[Applications]
After completing this course, learners can apply their knowledge of Kubernetes to create and manage containerized applications in production. They can use Minikube to set up a local Kubernetes environment and deploy more complicated applications with databases and APIs. Learners can also use Kubernetes to run jobs and cron jobs, as well as explore more advanced topics such as production deployments, namespaces, monitoring and logging, and authentication and authorization.
[Career Paths]
1. Kubernetes Engineer: Kubernetes Engineers are responsible for designing, deploying, and managing Kubernetes clusters. They must have a deep understanding of the Kubernetes architecture and be able to troubleshoot and optimize Kubernetes deployments. This role is becoming increasingly important as more organizations are adopting Kubernetes for their production workloads.
2. DevOps Engineer: DevOps Engineers are responsible for automating and streamlining the software development process. They must have a deep understanding of both the development and operations sides of the software development lifecycle. They must also be able to work with Kubernetes to deploy and manage applications in production.
3. Cloud Architect: Cloud Architects are responsible for designing and implementing cloud-based solutions. They must have a deep understanding of cloud computing technologies, including Kubernetes, and be able to design and implement solutions that are secure, scalable, and cost-effective.
4. Site Reliability Engineer: Site Reliability Engineers are responsible for ensuring the availability, performance, and scalability of applications and services. They must have a deep understanding of Kubernetes and be able to troubleshoot and optimize Kubernetes deployments. This role is becoming increasingly important as more organizations are adopting Kubernetes for their production workloads.
[Education Paths]
1. Bachelor of Science in Computer Science: This degree path provides students with a comprehensive understanding of computer science fundamentals, including programming, software engineering, and systems design. It also covers topics related to Kubernetes, such as distributed systems, cloud computing, and container orchestration. Developing trends in this field include the use of machine learning and artificial intelligence to automate and optimize Kubernetes deployments.
2. Master of Science in Cloud Computing: This degree path focuses on the development and deployment of cloud-based applications and services. It covers topics related to Kubernetes, such as container orchestration, distributed systems, and cloud security. Developing trends in this field include the use of Kubernetes to manage and deploy cloud-native applications.
3. Master of Science in Data Science: This degree path focuses on the analysis and interpretation of large datasets. It covers topics related to Kubernetes, such as distributed systems, container orchestration, and data visualization. Developing trends in this field include the use of Kubernetes to manage and deploy data-driven applications.
4. Master of Science in Artificial Intelligence: This degree path focuses on the development of intelligent systems and algorithms. It covers topics related to Kubernetes, such as distributed systems, container orchestration, and machine learning. Developing trends in this field include the use of Kubernetes to manage and deploy AI-driven applications.
Course Syllabus
Introduction
What you should know
How to use the exercise files
Course Provider
Provider LinkedIn Learning's Stats at AZClass
Gain the skills to deploy and manage container-based applications using Kubernetes, the widely used open source orchestration engine. This course covers Kubernetes basics, such as how to use Minikube to get a Kubernetes environment up and running on Mac or Windows, and learn about the components of Kubernetes. It also covers more advanced topics such as deploying more complex applications with databases and APIs, running jobs and cron jobs, production deployments, namespaces, monitoring and logging, and authentication and authorization. Learners can learn how to use Kubernetes to manage their applications.
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