Learning outcomes

At the end of this course, students will be able to:
  • Define and explain DevOps and its methodological, technical, and managerial aspects.
  • Design and configure a continuous delivery pipeline for a given application.
  • Discuss the security aspects of a continuous delivery pipeline.
  • Discuss the relevance of a continuous delivery pipeline for an application relying on machine learning models.

Content

The course presents the different aspects of DevOps approaches and continuous delivery pipelines. It focuses on the automated aspects of a software engineering process (version control, automated build and deployment, automated monitoring and logging, infrastructure as code), the security aspects tightened to this process (DevSecOps), and the application of continuous delivery to machine learning-based application (DevMLOps).

Assessment method

The evaluation is based on the completion of assignments.

Sources, references and any support material

  • Nicole Forsgren, Jez Humble, and Gene Kim. 2018. Accelerate: The Science of Lean Software and DevOps Building and Scaling High Performing Technology Organizations. IT Revolution Press.
  • Gene Kim, Patrick Debois, John Willis, and Jez Humble. 2016. The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations. IT Revolution Press.
 

Language of instruction

Anglais
Training Study programme Block Credits Mandatory
Master in Computer Science, Professional focus Standard 0 5
Master in Computer Science, Professional focus Standard 1 5