Cursus 28

Big Data architectures are evolving with new needs, such as on-demand scalability or application deployments in hybrid environments (mix of multiple public clouds and on-premises environments). Kubernetes is one of the technologies behind this transformation. Kubernetes (K8s) is an open-source system for automating the deployment, scaling and management of containerized applications. The course leads to the understanding, installation, management of this very powerful infrastructure.

The training is aimed at a technical population (IT staff, IS architects) who have solid experience in infrastructure management in the IS and who have a devops experience.

It’s the ideal training to understand the architectures of tomorrow, whether they are Big Data or not.


Day 1


The Docke environment

  • Principles and architecture
  • Creation of image Docker
  • Compose & Swarm


  • Principles and architecture
  • Cluster Relationships
  • Terminology
    • pods, master, node, label, service, replication controller, tools (kubeadm, kubelet, kubectl …)


  • Presentation
  • Creation and operation of a Pod


  • Deployment
  • DaemonSets
  • Jobs

Installation and configuration

  • Become familiar with kubctl
  • Create a deployment, a replica set, a pod

How to administer your cluster

Practical work

Day 2

Deployment strategy

  • The different strategies
  • Rolling update

Expose its applications

  • Communication between pods
  • Expose a service

Configure your application

  • Via files
  • Via environment variables

Case of statefull applications

  • Volume management
  • HA applications with StatefulSets

How to secure your cluster

Production features

  • CPU / RAM resource management
  • Application self-scaling
  • Manage your logs
  • Helm
  • The arrival of mesh services

Practical work

Conclusion and Key Take aways