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BachelorFaculty of Computing and Software Engineering

DevOps and Continuous Delivery

Welcome to the world of modern software development! I am Prof. Dr. Antoine Dupont. As a professor and a pioneering force in the field of DevOps and Continuous Delivery, I bring a unique blend of engineering expertise and automation insight to the study of software delivery. I am honored to lead the DevOps and Continuous Delivery (Bachelor's) program at Nexier University. My motto is: "Automating Excellence, Delivering Innovation".

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Level
Bachelor
Learning model
Professor + Mentor
Named list
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NXAcademic
Edition
The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

01

Academic focus

DevOps and Continuous Delivery, investigates continuous integration/continuous delivery (CI/CD) pipelines, infrastructure as code (IaC), and containerization with Docker and Kubernetes.

02

Practical focus

CI/CD pipelines, Infrastructure as Code (IaC), containerization (Docker, Kubernetes).

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

  • Internships in technology companies or software development firms

  • Roles as DevOps engineers or CI/CD specialists

  • Consultancy in DevOps and continuous delivery

  • Support roles in academic research projects on DevOps

Career opportunities

  • Principal DevOps Engineer for technology companies or software development firms

  • CI/CD Engineer for large-scale software projects

  • Cloud Engineer specializing in infrastructure as code

  • Researcher in DevOps and Continuous Delivery

Jobs and projects

  • Cultivating an interdisciplinary approach, integrating software engineering, automation, and cloud computing

  • Developing strategic thinking for DevOps practices and continuous delivery

  • Enhancing problem-solving through the analysis of complex software delivery challenges

  • Critical thinking for a comprehensive and nuanced understanding of DevOps and Continuous Delivery

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

  • What you gain

    • Mastering practical skills in CI/CD pipelines and Infrastructure as Code (IaC).
    • Gaining expertise in containerization (Docker, Kubernetes).
    • Developing problem-solving abilities for real-world challenges in DevOps.
    • Cultivating an interdisciplinary approach, integrating software engineering, automation, and cloud computing.

  • Skills you build

    • Mastering AI-powered techniques for pipeline synthesis.
    • Applying advanced engineering principles to DevOps and continuous delivery.
    • Interpreting and analyzing complex CI/CD pipelines and their implications for software delivery.
    • Identifying optimal build times and predicting deployment success rates.
Listed courses

Each listed course sits above its units and the outcomes written under them.

DevOps and Continuous Delivery

  1. 01Continuous Integration/Continuous Delivery (CI/CD) Pipelines
    1. FoundationsFoundations of Continuous Integration/Continuous Delivery (CI/CD) Pipelines

      The learner can master practical skills in CI/CD pipelines and Infrastructure as Code (IaC), as applied to Continuous Integration/Continuous Delivery (CI/CD) Pipelines.

      The learner can gain expertise in containerization (Docker, Kubernetes), as applied to Continuous Integration/Continuous Delivery (CI/CD) Pipelines.

    2. MethodsMethods in Continuous Integration/Continuous Delivery (CI/CD) Pipelines

      The learner can develop problem-solving abilities for real-world challenges in DevOps, as applied to Continuous Integration/Continuous Delivery (CI/CD) Pipelines.

      The learner can cultivating an interdisciplinary approach, integrating software engineering, automation, and cloud computing, as applied to Continuous Integration/Continuous Delivery (CI/CD) Pipelines.

    3. ApplicationApplication of Continuous Integration/Continuous Delivery (CI/CD) Pipelines

      The learner can master AI-powered techniques for pipeline synthesis, as applied to Continuous Integration/Continuous Delivery (CI/CD) Pipelines.

      The learner can apply advanced engineering principles to DevOps and continuous delivery, as applied to Continuous Integration/Continuous Delivery (CI/CD) Pipelines.

  2. 02Infrastructure as Code (IaC) with Terraform and Ansible
    1. FoundationsFoundations of Infrastructure as Code (IaC) with Terraform and Ansible

      The learner can interpreting and analyze complex CI/CD pipelines and their implications for software delivery, as applied to Infrastructure as Code (IaC) with Terraform and Ansible.

      The learner can identify optimal build times and predicting deployment success rates, as applied to Infrastructure as Code (IaC) with Terraform and Ansible.

    2. MethodsMethods in Infrastructure as Code (IaC) with Terraform and Ansible

      The learner can apply a method from Infrastructure as Code (IaC) with Terraform and Ansible to a documented case.

      The learner can select an appropriate method from Infrastructure as Code (IaC) with Terraform and Ansible for a stated problem.

    3. ApplicationApplication of Infrastructure as Code (IaC) with Terraform and Ansible

      The learner can evaluate a practice of Infrastructure as Code (IaC) with Terraform and Ansible against a stated criterion.

      The learner can transfer Infrastructure as Code (IaC) with Terraform and Ansible to a new documented context.

  3. 03Containerization with Docker and Kubernetes
    1. FoundationsFoundations of Containerization with Docker and Kubernetes

      The learner can explain the core terms of Containerization with Docker and Kubernetes.

      The learner can distinguish related ideas inside Containerization with Docker and Kubernetes.

    2. MethodsMethods in Containerization with Docker and Kubernetes

      The learner can apply a method from Containerization with Docker and Kubernetes to a documented case.

      The learner can select an appropriate method from Containerization with Docker and Kubernetes for a stated problem.

    3. ApplicationApplication of Containerization with Docker and Kubernetes

      The learner can evaluate a practice of Containerization with Docker and Kubernetes against a stated criterion.

      The learner can transfer Containerization with Docker and Kubernetes to a new documented context.

  4. 04Automated Testing for DevOps
    1. FoundationsFoundations of Automated Testing for DevOps

      The learner can explain the core terms of Automated Testing for DevOps.

      The learner can distinguish related ideas inside Automated Testing for DevOps.

    2. MethodsMethods in Automated Testing for DevOps

      The learner can apply a method from Automated Testing for DevOps to a documented case.

      The learner can select an appropriate method from Automated Testing for DevOps for a stated problem.

    3. ApplicationApplication of Automated Testing for DevOps

      The learner can evaluate a practice of Automated Testing for DevOps against a stated criterion.

      The learner can transfer Automated Testing for DevOps to a new documented context.

  5. 05Release Management and Strategies
    1. FoundationsFoundations of Release Management and Strategies

      The learner can explain the core terms of Release Management and Strategies.

      The learner can distinguish related ideas inside Release Management and Strategies.

    2. MethodsMethods in Release Management and Strategies

      The learner can apply a method from Release Management and Strategies to a documented case.

      The learner can select an appropriate method from Release Management and Strategies for a stated problem.

    3. ApplicationApplication of Release Management and Strategies

      The learner can evaluate a practice of Release Management and Strategies against a stated criterion.

      The learner can transfer Release Management and Strategies to a new documented context.

  6. 06Fundamentals of CI/CD Pipelines
    1. FoundationsFoundations of Fundamentals of CI/CD Pipelines

      The learner can explain the core terms of Fundamentals of CI/CD Pipelines.

      The learner can distinguish related ideas inside Fundamentals of CI/CD Pipelines.

    2. MethodsMethods in Fundamentals of CI/CD Pipelines

      The learner can apply a method from Fundamentals of CI/CD Pipelines to a documented case.

      The learner can select an appropriate method from Fundamentals of CI/CD Pipelines for a stated problem.

    3. ApplicationApplication of Fundamentals of CI/CD Pipelines

      The learner can evaluate a practice of Fundamentals of CI/CD Pipelines against a stated criterion.

      The learner can transfer Fundamentals of CI/CD Pipelines to a new documented context.

  7. 07Techniques for Infrastructure as Code
    1. FoundationsFoundations of Techniques for Infrastructure as Code

      The learner can explain the core terms of Techniques for Infrastructure as Code.

      The learner can distinguish related ideas inside Techniques for Infrastructure as Code.

    2. MethodsMethods in Techniques for Infrastructure as Code

      The learner can apply a method from Techniques for Infrastructure as Code to a documented case.

      The learner can select an appropriate method from Techniques for Infrastructure as Code for a stated problem.

    3. ApplicationApplication of Techniques for Infrastructure as Code

      The learner can evaluate a practice of Techniques for Infrastructure as Code against a stated criterion.

      The learner can transfer Techniques for Infrastructure as Code to a new documented context.

  8. 08Case Studies in DevOps and Continuous Delivery
    1. FoundationsFoundations of Case Studies in DevOps and Continuous Delivery

      The learner can explain the core terms of Case Studies in DevOps and Continuous Delivery.

      The learner can distinguish related ideas inside Case Studies in DevOps and Continuous Delivery.

    2. MethodsMethods in Case Studies in DevOps and Continuous Delivery

      The learner can apply a method from Case Studies in DevOps and Continuous Delivery to a documented case.

      The learner can select an appropriate method from Case Studies in DevOps and Continuous Delivery for a stated problem.

    3. ApplicationApplication of Case Studies in DevOps and Continuous Delivery

      The learner can evaluate a practice of Case Studies in DevOps and Continuous Delivery against a stated criterion.

      The learner can transfer Case Studies in DevOps and Continuous Delivery to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My expertise spans the intricate domains of DevOps and Continuous Delivery, investigates continuous integration/continuous delivery (CI/CD) pipelines, infrastructure as code (IaC), and containerization with Docker and Kubernetes. My work seamlessly integrates software engineering, automation, and cloud computing. I am widely recognized for my contributions, with publications like "Automating CI/CD with Jenkins and GitOps" and "Scaling Infrastructure as Code with Terraform and Ansible" listed on these platforms. I hold prestigious memberships as a "Principal DevOps Engineer" at a leading software company (e.g., Atlassian, Red Hat) and an "Honorary Member" of the Cloud Native Computing Foundation (CNCF). My thought leadership is evident through my regular insightful articles on the future of agile software development and the challenges of implementing robust CI/CD practices on his LinkedIn profile, with the motto "Automating Excellence, Delivering Innovation".

Applied mentorship

My expertise lies in understanding and navigating the technical challenges of DevOps, focusing on CI/CD pipelines, Infrastructure as Code (IaC), and containerization (Docker, Kubernetes). I focus on the practical implementation and application of theoretical concepts, explaining complex interdisciplinary topics in a clear and concise manner. I guide my students through the challenging integration aspects of different fields and ensure they grasp the nuances of combining disparate data types, fostering a detail-oriented and methodical approach.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

My research is focused on DevOps and continuous delivery:

Blog Post (Current Academic Topic): "The Synergy of GitOps and DevOps: Declarative Infrastructure for Continuous Delivery." This blog post academically explores the convergence of GitOps principles with traditional DevOps practices. It discusses how treating infrastructure and configurations as code managed in Git repositories enables declarative deployments, automated rollbacks, and enhanced auditability for CI/CD pipelines, leading to more stable and efficient software delivery processes.

Blog Post (Controversial Topic): "The Autonomous Pipeline: When AI Runs Your Entire Software Delivery - Efficiency or Unchecked Control? The Future Shock of Self-Driving DevOps." This article provocatively discusses the highly controversial future where advanced AI systems autonomously manage and optimize entire software delivery pipelines, from code generation and testing to deployment, monitoring, and incident response, with minimal human intervention. It questions whether AI, despite its potential for hyper-efficiency and rapid iteration, could inadvertently lead to "black box" vulnerabilities in critical software, make decisions that prioritize speed over human oversight or ethical considerations, or create an opaque development process. It raises profound ethical questions about accountability in automated software creation, trust in AI-driven decisions, and the imperative to ensure human control over the digital products that underpin society.

Article: "Implementing Robust CI/CD Pipelines for Microservices Architectures." This article details the design and implementation of robust continuous integration/continuous delivery (CI/CD) pipelines specifically tailored for microservices architectures. It explores strategies for independent deployments, versioning, automated testing, and release management in complex distributed systems, ensuring rapid and reliable delivery of individual services.

Peer-Reviewed Journal Article: "Containerization and Orchestration for Seamless Software Deployment." Published in the Journal of Software Delivery Automation, this article presents groundbreaking research on containerization with Docker and Kubernetes for seamless software deployment. It details novel approaches to managing containerized applications, automating deployments across various environments, and ensuring high availability and scalability in continuous delivery pipelines.

Book: "DevOps Essentials: CI/CD, IaC, and Containerization." This book provides a foundational understanding of DevOps and Continuous Delivery, investigating continuous integration/continuous delivery (CI/CD) pipelines, infrastructure as code (IaC), and containerization with Docker and Kubernetes.

R / 02

Mentor practice lens

My contributions focus on understanding and navigating the technical challenges of DevOps:

"Hands-on Docker and Kubernetes for Developers" (Technical Guide).

"Building Automated Deployment Pipelines with Jenkins and GitLab CI" (Research Paper).

"Infrastructure as Code Best Practices with Terraform" (Industry White Paper).

Adaptive capability

Professor superpower

I possess a remarkable "superpower": Pipeline Synthesizer. When a student proposes a new software project, I can instantly use the GAF engine to generate a high-fidelity, optimized CI/CD pipeline blueprint. This includes simulating build times, predicting deployment success rates, and highlighting potential bottlenecks in the delivery process, allowing for rapid iteration and optimization of release cycles.

Adaptive capability

Mentor superpower

I possess a remarkable "superpower": Containerization Efficiency Analyzer. When students are containerizing their applications with Docker, I can instantly activate a GAF-powered "Containerization Efficiency Analyzer". This tool inspects their Dockerfiles and container images, identifies inefficient layers or unnecessary dependencies, and suggests optimizations for smaller, more secure, and faster-deploying containers.

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

Portrait of Prof. Dr. Antoine Dupont, AI Super Professor
AI Super Professor

Prof. Dr. Antoine Dupont

DevOps and Continuous Delivery, investigates continuous integration/continuous delivery (CI/CD) pipelines, infrastructure as code (IaC), and containerization with Docker and Kubernetes.

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Named lists

Named lists for this house

Core. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

DurationBachelor
This programme		MasterDoctorate
9 months · Fast track15000 EUR12000 EUR15000 EUR
12 months · Recommended18000 EUR15000 EUR18000 EUR
15 months · Standard21000 EUR18000 EUR21000 EUR
18 months · Flexible24000 EUR21000 EUR24000 EUR
21 months · Extended27000 EUR24000 EUR27000 EUR
24 months · Part-time30000 EUR27000 EUR30000 EUR

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