Docker for DevOps: 2-in-1 | Business Analytics & Intelligence Online Course by Udemy

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Deploy and run Docker containers efficiently by setting up Jenkins consistently and measure performance optimizations

An excellent training about Business Analytics & Intelligence

Docker for DevOps: 2-in-1

Docker has been a game changer when it comes to containerization. It is been used more and more by developers, system administrators, and IT administrators on a daily basis. The container idea comes to simplify application development, testing, and deployment. Using Docker, you get a unique way to package your application. This comprehensive 2-in-1 course teaches you to deploy and run Docker containers efficiently by setting up Jenkins consistently and measuring your performance optimizations. You will also to work with various components to run Docker in production and will interact with containers using standard Linux tools for debugging and demonstrating. It covers each and every concept of Docker with the help of practical examples making it easy for you to understand and implement in your own production environments. This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible. The first course, Deploying and Running Docker Containers, starts off with explaining you a basic deployment-pipeline setup in Jenkins. You will then learn how to create two minimal Docker environments: one for development and one for production. You will also learn to set up Jenkins inside a Docker container to support and automate your deployment pipeline. Next, you will learn how to provide reliability and scalability to your application by setting up a cluster of Docker hosts using Docker Swarm mode, and then automate the deployment of Docker hosts using Chef. You will learn how to monitor, log, and manage your Docker containers. Finally, you will work with the various components required to run Docker in production. The second course, Optimizing Docker Workflows, begins with demonstrating various techniques and tools to build Docker images faster. You will then master various ways to speed up deploying containers to your production environment. Finally, you will look at standard Linux tools for debugging and demonstrating how to use them to interact with containers. By the end of this Learning Path, you’ll be able to deploy code to your production environment and optimize your workflow efficiently. Meet Your Expert(s): We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth: Allan Espinosa is a DevOps practitioner and an active open source contributor to various distributed systems tools, such as Docker and Chef. He maintains several Docker images for popular open source software that were popular even before their official release from the upstream open source groups. Throughout his career, he has worked on large distributed systems containing hundreds to thousands of servers in production. He has built scalable applications on various platforms ranging from large supercomputing centers to production clusters in the enterprise. He is currently managing distributed systems at scale for Bloomberg, where he oversees the company’s Hadoop infrastructure.

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