Deploy and Run Apps with Docker, Kubernetes, Helm, Rancher (Udemy.com)

Build, deploy, and run apps in Docker and Kubernetes. Use Helm to package apps. Manage multiple clusters with Rancher.

( 1 Reviews )

Created by: Martin Bergljung

Produced in 2022

What you will learn

Docker fundamentals
Building development and production Docker images
Service communication in a Docker Network
Automatically building Docker images with Travis CI and publish to Docker Hub
Using Docker Compose for basic container orchestration
Docker container deployment to Amazon Elastic Beanstalk
Kubernetes Concepts, such as Pod, Service, Deployment, StatefulSet, ConfigMap, Secret etc.
Kubernetes architecture and abstractions of hardware, storage, and network
Running Kubernetes locally with Docker for Desktop on Mac and Windows and MicroK8s on Linux Desktop
Microservices communication in a Kubernetes environment
Using Helm to package your applications for deployment to Kubernetes cluster
Setting up your own Helm Repository for your charts
Deploy Helm charts automatically to Helm Repository with Travis CI
Running Kubernetes in the Cloud with Google Cloud Platform and GKE

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 100 / 100

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Course Description

In this course we will take a simple Angular Client application that talks to a Node.JS server and deploy and run it as Docker containers. We will learn how to build both development and production Docker images for these types of applications. We will then be introduced to basic container orchestration with Docker Compose.
After this we will refactor the application to be more decoupled, resilient and scalable by using a Microservice architecture, making the app more Cloud native. We will learn how we can build Docker images and publish them to Docker hub automatically with Travis CI. We will deploy the containerized application to the Cloud with the help of Amazon Elastic Beanstalk service. We will also look at automating the deployment to Elastic Beanstalk with Travis CI. When we deploy the application to Elastic Beanstalk we will also see how we can use AWS services such as AWS RDS, AWS Elasticsearch and AWS Elasticache instead of running these as our own containers.
Then it's time for Kubernetes. We will spend a lot of time on Kubernetes as it is the preferred choice for most people when they want to run a container workload in Production. We will write Kubernetes manifest files (YAML) to deploy the application to a Kubernetes cluster. We will look at deploying both to a local Docker for Desktop single node Kubernetes cluster and to a multi node Kubernetes cluster in the Cloud (Google GKE, Amazon Kops, Amazon EKS).
Then we will look at Kubernetes Helm that can be used to package the Kubernetes manifest files so they can be versioned and released as one entity. Learn how to use Travis CI to build docker images and deploy automatically to Kubernetes clusters. Finally see how you can manage multiple Kubernetes clusters with Rancher. Who this course is for:

Developers
Architects
DevOps
IT

Time: 23.5h

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Instructor Details

Martin Bergljung

5.0 Rating
1 Reviews

I have been working with Alfresco for the past 10 years. I started out building an email integration for Alfresco, integrating Apache James, so my first experience with the product was a deep dive into coding a customisation. I then started doing consulting projects based on Alfresco and found out quite quickly that I really like the product. It is very open and allows you to build pretty much anything you can come up with (or your client can come up with!).
In 2011 I got the opportunity to write a book about Alfresco, which was a great experience as I really like to mentor, train, and educate people. I then did more consulting and got into bigger projects in the publishing space. During a couple of years I was also an instructor giving Alfresco classroom training courses. Then in 2014 I got the opportunity to write another book about Alfresco and specifically the CMIS standard that you can use to talk to the Alfresco content management system, again a great experience.
In 2015 I started working for Alfresco with all kinds of stuff, such as developing the Alfresco SDK, creating developer documentation, writing articles, talking at conferences, prototyping new features. What I really like to do is take what we develop internally at Alfresco and try and explain it in an easy and understandable way.
Since 2017 I have been working a lot with container technology as version 6.x of the Alfresco product is deployed and run with containers. The product is run locally with D

Reviews

5.0

1 total reviews

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By Soeren Ganik on

Very good match. I think this course is containing just what i need.

By Aaron Albert on

I'm now about 60% through the course and would still recommend it. Working through the development of the sample application from local processes, to local containers, to docker-compose, to elastic beanstalk, to kubernetes has been very valuable. Working through the evolution of the software and the operational environment is much more valuable than just deploying a prepared application and then playing with commands. Though clearly not the focus of the course, it provides a good example of SDLC and related ideas for those of us who are more on the Ops side of DevOps. There is a lot of value beyond simply learning docker or kubernetes. Even if you already have basic knowledge and skill with these, the review may be valuable to you. I still have not reached the helm and rancher parts of the course which is why I originally purchased it but I feel like I have already gotten more value than the price would suggest.Previous Review: I am only about 30% through this course but so far it has been excellent and I would recommend it. I was mainly interested in the kubernetes, helm, and rancher part of this course (which I am only just now getting to) but I found the docker and docker-compose sections to be a good review for me and it helped me set up nice lab environment for later use. The instructor has a notable accent (to an American) but his English is very good and he is easy to understand. He speaks a little slow but I found that 1.25 is perfect for me. 1.5 speed is usable but since this also speeds up the video I have to pause sometimes to study the screen.

By Ishau Oyeti on