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DevOps Training

DevOps Training

Due to the COVID-19 our training courses will be taught via an online classroom.

Receive in-depth knowledge from industry professionals, test your skills with hands-on assignments & demos, and get access to valuable resources and tools.

This course is an introduction into DevOps technologies such continuous integration/continuous deployment (CI/CD), Docker, and Kubernetes. The lessons that are presented here focus on git and the GitFlow paradigm, managing and building Docker containers, including best practices. Additionally, this course covers not only basic concepts in Kubernetes but also advanced ones such as package management using Helm. After completing this training, you will be able to design CI/CD pipelines with confidence. This course is ideal for data engineers/scientists who want to take the next step into DevOps. As requirements, experience with programming languages such as python or java should be enough.

Are you interested? Contact us and we will get in touch with you.

 

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Academy: DevOps
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About the training & classes

The DevOps training is split in 4 days. Click below to see a detailed description of each class: 

 
 
Git, GitFlow, CI/CD

During this lesson you will learn the fundamentals of Git, what makes up a commit and how Git stores files. We will also teach you about branches, merging and rebases. These fundamentals will allow you to deal with conflicts in a more profound way.

Next to that, this lesson is filled with best practices and Git goodies such as amending commits, committing single lines and cherry-picking. Understanding how Git works, allows you to fully unlock its potential, making you more productive at writing code.

We will also look at a way of working with Git in a production environment through the method of GitFlow. This paradigm for handling releases allows teams to grow bigger and isolates features, thereby reducing interdependency. Following GitFlow your team can release faster and more often. Finally, we will dive into Continuous Integration / Continuous Deployment, which connects to GitFlow, for always be releasing updates to your project in a controlled manner.

The training includes theory and hands-on exercises. After this training you will have gained knowledge about:

  • Fundamentals of Git
  • Branches, merging, and rebases
  • Git best practices
  • GitFlow
  • Continuous Integration / Continuous Deployment
  • Lab session to get hands-on experience with these tools
Docker

During this training you will become familiar with the world’s leading container platform - Docker. You will learn how Docker bridges the gap between operations and development teams and how Docker works ‘under the hood’. During the practical session you will build a small API that uses several Dockerized components. This practical session will teach you the basics of building Docker images and cover the most used Docker command line tools. During the training we will also provide you with recommendations and best practices when using Docker for development and operations.

The training includes theory and hands-on exercises. After this training you will have gained knowledge about:

  • Basic introduction to Docker
  • What Docker offers developers, operations and the enterprise as a whole
  • A technical breakdown of Docker internals
  • Managing and building Docker containers
  • Docker best practices
Kubernetes: I

This training aims to give an overview of what Kubernetes does, how it works and how to use it in practice. It is part 1 of 2 courses on this topic.

In the first Kubernetes class of the DevOps training, we will discuss core principles such as containers, clusters, container dependencies, image registries, deployments, load balancing, scaling, and others. Then we will deep dive into the main components of Kubernetes clusters - (master) nodes, pods, services and replication controllers. We then move to more practical information about how to use the kubectl command line tool, writing specification files and the Kubernetes Dashboard.

After this theoretical overview we gain hands-on experience in a two-part lab session, in which we learn how to set up a local Kubernetes cluster and deploy applications in practice.

The training includes theory, demos, and hands-on exercises. After this training you will have gained knowledge about:

  • Recap Docker and Docker Compose
  • Container automation & orchestration
  • Container dependencies
  • Image registries
  • Automated deployments
  • Features such as load balancing, health checks, scaling and rolling updates
  • Cluster components: master, nodes, pods, services, replication controllers, labels
  • Kubectl command line
  • Specification files (yaml, json)
  • Kubernetes Dashboard
  • Lab session to get hands-on experience deploying apps in a Kubernetes Cluster
Kubernetes: II

In the second part of the Kubernetes training, we aim to go deeper into specific tools that build on top of Kubernetes.

First, we discuss Package Management in Kubernetes using HELM. We explain the concepts of Charts and the HELM client together with Chart Repositories. Then, we go into Monitoring using Prometheus. Here, the concepts of Alerts and Targets are explained, the Prometheus architecture, its query language (PromQL) and how to use it in conjunction with the Grafana analytics platform. Next, we cover Istio, a Service Mesh, i.e. a distributed system of microservices. We delve into the fallacies of distributed computing that it aims to solve, its architecture, and core features. Finally, we will focus on Kubeflow, the Machine Learning toolkit for Kubernetes. Each of these tools is accompanied by a lab exercise that will give us some hands-on experience.

The training includes theory, demos, and hands-on exercises. After this training you will have gained knowledge about the architecture, usage and (dis)advantages of:

  • HELM: package management for Kubernetes
  • Prometheus: monitoring
  • Istio: service meshes
  • Kubeflow: machine learning toolkit
  • Lab session to get hands-on experience with these tools