Containers and Virtual Machines (VMs) Training in Lyon

Edge AI represents a strategic approach to executing machine learning inference in proximity to data sources, ensuring low-latency, high-efficiency, and scalable processing capabilities.

Delivered by an instructor in a live format (either online or on-site), this training is tailored for intermediate to advanced professionals seeking to deploy, orchestrate, and refine AI workloads within Kubernetes-based edge ecosystems.

Upon completion, participants will gain the ability to:

• Establish lightweight Kubernetes distributions suited for edge environments.
• Efficiently distribute AI inference workloads across resource-constrained edge nodes.
• Address connectivity challenges and implement effective synchronization patterns.
• Enhance performance, storage management, and networking configurations for practical edge scenarios.

Course Structure

• Instructor-led presentations enriched with real-world case studies.
• Scenario-driven labs and practical exercises focused on edge deployment.
• Practical engagement with various Kubernetes edge frameworks.

Customization Possibilities

• To obtain a training program customized to your specific edge platform requirements, please reach out to us to make arrangements.

Kubernetes serves as a leading container orchestration platform for managing distributed applications at scale.

This instructor-led live training, available online or on-site, is designed for advanced practitioners aiming to leverage AI and machine learning techniques to enhance Kubernetes resource utilization, scheduling decisions, and autoscaling strategies.

By the end of this program, participants will be equipped to:

• Leverage AI/ML models to refine workload scheduling decisions within Kubernetes.
• Utilize predictive analytics to fine-tune CPU, GPU, and memory allocation.
• Implement intelligent autoscaling through reinforcement learning and metric forecasting.
• Minimize infrastructure costs and latency via automated resource optimization.

Course Format

• Instructor-guided technical presentations and in-depth discussions.
• Practical lab work conducted on real Kubernetes clusters.
• Exercises focused on applying AI models to genuine operational scenarios.

Customization Options

• For tailoring this course to specific platform configurations or operational needs, please contact us for bespoke solutions.

MLOps on Kubernetes serves as a framework for automating the training, validation, packaging, and deployment of machine learning models through containerized pipelines and GitOps workflows.

This instructor-led live training, available online or onsite, targets intermediate-level practitioners aiming to build automated, scalable MLOps pipelines on Kubernetes.

Upon completing this training, participants will be able to:

• Design end-to-end CI/CD pipelines for machine learning.
• Implement GitOps workflows for model deployment and versioning.
• Automate the training, testing, and packaging of ML models.
• Integrate monitoring, alerting, and rollback strategies.

Course Format

• Instructor-guided presentations and technical deep dives.
• Hands-on exercises that build real-world CI/CD workflows.
• Live-lab practice deploying ML workloads to Kubernetes.

Course Customization Options

• Organizations may request tailored content aligned with their internal MLOps tools and infrastructure.

Kubeflow is an open-source platform designed to streamline building, training, and deploying machine learning workloads on Kubernetes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to build reliable ML workflows using Kubeflow.

Upon completion of this training, attendees will gain the skills to:

• Explore the Kubeflow ecosystem and its core components.
• Develop reproducible workflows using Kubeflow Pipelines.
• Execute scalable training jobs within a Kubernetes environment.
• Deploy machine learning models efficiently via Kubeflow Serving.

Format of the Course also allows for the evaluation of participants.

• Guided presentations and collaborative discussions.
• Hands-on labs with real Kubeflow components.
• Practical exercises to build end-to-end ML workflows.

Course Customization Options

• Customized versions of this training can be arranged to align with your team’s technology stack and project requirements.

CI/CD for AI represents a structured methodology for automating the packaging, testing, containerization, and deployment of models through continuous integration and delivery pipelines.

This instructor-led live training (available online or onsite) targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completion of the training, participants will be able to:

• Establish automated pipelines for building and testing AI model containers.
• Ensure version control and reproducibility throughout model lifecycles.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically tailored to machine learning operations.

Format of the Course also allows for the evaluation of participants.

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations conducted in a controlled environment.

Course Customization Options

• If your organization requires customized pipeline workflows or platform integrations, please contact us to tailor this course.

This instructor-led, live training in Lyon (online or onsite) is aimed at advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

By the end of this training, participants will be able to:

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics for pods, nodes, and services.
• Create dynamic dashboards to visualize cluster health and performance.
• Implement alerting strategies for proactive issue resolution.
• Apply best practices for scaling monitoring solutions in Kubernetes environments.

Hybrid AI deployment involves executing AI inference across cloud, on-premise, and edge environments using unified container-based workflows.

This instructor-led live training (available online or onsite) is designed for advanced professionals aiming to architect and deploy distributed AI inference systems within heterogeneous infrastructures.

After completing this training, participants will be equipped to:

• Create secure and scalable containerized AI services for multi-location setups.
• Leverage Docker to deploy AI inference workloads across cloud platforms, local servers, and edge devices.
• Utilize orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across diverse infrastructure components.

Course Format

• Instructor-led presentations and expert-driven discussions.
• Comprehensive hands-on practice and applied exercises.
• Real-world experimentation within a controlled live-lab environment.

Customization Options

• To tailor this course to your organization’s specific infrastructure or use cases, please contact us for customization services.

Kubernetes is an open-source platform designed for automating the deployment, scaling, and management of containerized applications.

This instructor-led live training, available either online or onsite, is designed for beginner to intermediate IT professionals who want to master the core concepts and components of Kubernetes and utilize it to manage containerized applications at scale.

Upon completion of this training, participants will be able to:

• Comprehend the architecture and components of Kubernetes.
• Deploy and manage containers within a Kubernetes cluster.
• Configure networking, storage, and scaling for various workloads.
• Troubleshoot common issues and adhere to best practices for cluster operations.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical sessions.
• Hands-on implementation within a live lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange a session.

This instructor-led, live training in Lyon (online or onsite) is aimed at DevOps engineers and developers who wish to use Kubernetes to build, deploy, and manage containers and cluster components in a secure and scalable environment.

By the end of this training, participants will be able to:

• Understand the architecture, core concepts, and components of a Kubernetes ecosystem.
• Set up, install, and configure a Kubernetes cluster for container orchestration.
• Learn how to execute Kubernetes operations using the command line tools.
• Get a hands-on experience from basic to advanced Kubernetes operations and administration.

Docker serves as a containerization platform designed to create portable, isolated, and secure deployment environments for AI inference services.

This instructor-led training (available online or onsite) is intended for beginner to intermediate technical professionals seeking to develop secure, portable AI inference microservices that can be consistently deployed across local machines, servers, or cloud virtual machines.

Upon completing this workshop, participants will be able to:

• Create lightweight inference containers suitable for both local and cloud deployment.
• Secure containerized AI services by applying best-practice techniques.
• Implement portable microservice workflows to ensure consistent environments.
• Deploy AI inference endpoints across diverse infrastructures.

Course Format

• Guided lectures combined with practical demonstrations.
• Hands-on exercises to reinforce deployment and security techniques.
• Live-lab practice for building and running portable inference services.

Customization Options

• To tailor this training to your specific infrastructure or AI tooling stack, please contact us to arrange.

In this instructor-led, live training in Lyon (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking participants through the process of securing, networking and monitoring a Kubernetes cluster.

By the end of this training, participants will be able to:

• Set up and run a Docker container.
• Deploy containerized databases and servers.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage different environments under the same cluster.
• Secure, scale and monitor a Kubernetes cluster.

Utilizing GPU acceleration is pivotal for executing high-performance deep learning tasks with both scalability and efficiency.

Designed for intermediate-level technical experts, this instructor-led live training (available online or onsite) focuses on the configuration, optimization, and execution of GPU-capable AI workloads within Docker containers.

Upon completion, participants will be equipped to:

• Develop and execute GPU-enabled containers for both training and inference phases.
• Set up CUDA, drivers, and runtime libraries to support containerized AI pipelines.
• Enhance resource allocation and isolation strategies for applications with high GPU demands.
• Implement scalable, containerized deep learning services within production environments.

Course Delivery Methodology

• Engaging instruction complemented by practical, real-world examples.
• Exercise-centric practice emphasizing GPU-assisted development workflows.
• Direct, hands-on application in a live laboratory setting.

Customization Opportunities

• To align the training with your specific infrastructure or GPU configuration, please reach out to us for arrangements.

This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level professionals who wish to effectively deploy, manage, and scale containerized applications using Kubernetes.

By the end of this training, participants will be able to:

• Understand the Kubernetes architecture and its components.
• Isolate resources effectively using Namespaces.
• Manage and customize workloads with Deployments, StatefulSets, and DaemonSets.
• Define computational resources using Requests and Limits.
• Work with Jobs and CronJobs for scheduled tasks.
• Understand Services and DNS within Kubernetes.
• Expose applications using Ingress.
• Manage ConfigMaps, Secrets, and Persistent Volumes.
• Scale and upgrade Kubernetes clusters using advanced strategies.
• Analyze and troubleshoot Kubernetes issues.
• Deploy resources efficiently using Helm Charts.

This instructor-led, live training in Lyon (online or onsite) is designed for intermediate to advanced developers, DevOps professionals, and architects who aim to design, deploy, and manage resilient applications utilizing microservices, containers, and continuous integration/continuous deployment (CI/CD) pipelines.

By the end of this training, participants will be able to:

• Understand and implement microservices architecture.
• Deploy and manage containerized applications with Docker and Kubernetes.
• Set up and optimize CI/CD pipelines for automated deployments.
• Apply best practices for security, monitoring, and observability.

This instructor-led, live training in Lyon (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes.

By the end of this training, participants will be able to:

• Design and implement scalable microservices architectures.
• Deploy and manage applications on Kubernetes clusters.
• Utilize Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance in a Kubernetes environment.

Gain foundational knowledge of containers, Kubernetes, and OpenShift through practical, hands-on training designed for developers, DevOps engineers, and IT professionals. Participants will master the techniques to build containerized applications, deploy workloads, manage Kubernetes resources, and leverage OpenShift to streamline modern application delivery across cloud and hybrid environments.

Docker serves as a robust containerization platform, enabling the creation of reproducible, portable, and scalable environments tailored for machine learning systems.

This live, instructor-led training, available online or on-site, is designed for intermediate to advanced technical professionals seeking to containerize and operationalize comprehensive ML pipelines using Docker.

By the end of this program, participants will be equipped to:

• Encapsulate ML training, validation, and inference workloads within containers.
• Architect and orchestrate full-cycle ML pipelines leveraging Docker and associated tools.
• Establish versioning, reproducibility, and CI/CD workflows for ML components.
• Deploy, oversee, and scale ML services within containerized infrastructure.

Course Structure

• Engaging lectures complemented by practical demonstrations.
• Practical exercises centered on developing authentic ML pipeline elements.
• Real-time lab sessions implementing end-to-end containerized workflows.

Customization Options

• For tailored training aligned with specific ML infrastructure requirements, please reach out to us to explore available options.

Docker serves as a containerization platform that facilitates consistent, portable, and reproducible environments specifically for AI and machine learning workloads.

This instructor-led, live training session, available online or onsite, is designed for intermediate-level professionals looking to package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development to production.

Upon completion of this course, participants will be equipped to:

• Construct and oversee Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and dependencies within containers.
• Tune Docker environments for enhanced performance and portability.
• Implement containerized ML services across various runtime environments.

Instructional Methodology

• Conceptual demonstrations accompanied by guided discussions.
• Practical exercises centered on real-world containerization scenarios.
• Applied implementation within live-lab Docker environments.

Customization Possibilities

• Please reach out to us to discuss tailoring this training to fit your organizational environment.

This instructor-led live training in Lyon (online or onsite) is aimed at beginner-level developers who wish to learn the basics of Kubefirst and how it simplifies, secures, and accelerates Kubernetes and Swarm cluster management at enterprise scale.

By the end of this training, participants will be able to:

• Set up a Kubefirst development environment.
• Write and run a basic Kubefirst program.
• Annotate code with Kubefirst directives and clauses.
• Use Kubefirst API and libraries.
• Profile and debug Kubefirst programs.

This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level developers and DevOps engineers who wish to integrate Minikube into their development workflows.

By the end of this training, participants will be able to:

• Set up and manage a local Kubernetes environment using Minikube.
• Deploy, manage, and debug applications on Minikube effectively.
• Integrate Minikube into continuous integration and deployment pipelines.
• Leverage Minikube's advanced features to streamline their development process.
• Apply industry best practices for local Kubernetes development.

This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to build, deploy, and manage microservices using Spring Cloud and Docker.

By the end of this training, participants will be able to:

• Develop microservices using Spring Boot and Spring Cloud.
• Containerize applications with Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices in production environments.
• Deploy and orchestrate microservices using Kubernetes.

This instructor-led, live training in Lyon (online or onsite) is designed for beginner to intermediate software developers and DevOps professionals who want to learn how to set up and manage a local Kubernetes environment using Minikube.

By the end of this training, participants will be able to:

• Install and configure Minikube on their local machine.
• Understand the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for developing, testing, and debugging applications.

Training Objectives: Gain theoretical and practical skills in Docker and Kubernetes.

In this instructor-led live training in Lyon (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training goes on to more advanced topics, walking participants through the process of securing, scaling and monitoring a Kubernetes cluster.

By the end of this training, participants will be able to:

• Set up and run a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage a clustered web application.
• Secure, scale and monitor a Kubernetes cluster.

The Certified Kubernetes Administrator (CKA) program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes has become a leading platform for container orchestration.

NobleProg has been providing Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training companies globally in the field of containerization.

Since 2019, we have also been helping our customers validate their performance in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams.

This instructor-led, live training (online or onsite) is designed for System Administrators and Kubernetes users who wish to validate their knowledge by passing the CKA exam.

Additionally, the training focuses on gaining practical experience in Kubernetes Administration, so we recommend participating even if you do not intend to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

In this instructor-led live training in Lyon (online or onsite), participants will learn how to set up and manage a production-scale container environment using Kubernetes on AKS.

By the end of this training, participants will be able to:

• Configure and manage Kubernetes on AKS.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Azure.
• Migrate an existing Kubernetes environment from on-premise to AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

Master the skills to build, deploy, and administer containerized environments using Docker, Kubernetes, and OpenShift. This intensive five-day, hands-on training covers container images, Kubernetes workloads, cluster networking, storage solutions, security protocols, monitoring techniques, and practical OpenShift administration. Participants will acquire the necessary competencies to operate modern container platforms effectively and troubleshoot applications across both development and production environments.

This instructor-led, live training (online or onsite) is designed for engineers seeking to automate, secure, and monitor containerized applications within a large-scale Kubernetes cluster.

Upon completion of this training, participants will be able to:

• Utilize Kubernetes to deploy and manage distinct environments within a single cluster
• Enhance the security, scalability, and monitoring capabilities of a Kubernetes cluster

Course Format

• Interactive lectures and discussions
• Extensive exercises and practical activities
• Hands-on implementation in a live-lab environment

Customization Options

• To request a customized version of this course, please contact us to make arrangements.

The Certified Kubernetes Application Developer (CKAD) program was created by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host organization for Kubernetes.

This instructor-led, live training (available online or onsite) is designed for Developers who want to validate their expertise in designing, building, configuring, and exposing cloud native applications on Kubernetes.

Furthermore, the training emphasizes gaining practical experience in Kubernetes application development; therefore, we recommend participating even if you do not plan to take the CKAD exam.

NobleProg has been providing Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training providers worldwide in the field of containerization. Since 2019, we have also been assisting our customers in validating their performance in k8s environments by preparing them and encouraging them to pass the CKA and CKAD exams.

Course Format

• Interactive lectures and discussions.
• Abundant exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live course in Lyon provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.

Istio is an open-source service mesh designed for Kubernetes, enabling secure, observable, and manageable communication between microservices. By utilizing Istio's Envoy-based sidecar proxies, teams can enforce policies, secure communications via mTLS, gain deep traffic visibility, and enhance reliability at scale.

This instructor-led live training (available online or onsite) targets intermediate-level engineers looking to deploy, secure, and manage microservices applications using Istio on Kubernetes.

Upon completing this training, participants will be able to:

• Install and configure Istio on Kubernetes clusters.
• Understand and apply service mesh concepts, including traffic management, security, and observability.
• Deploy microservices applications within an Istio service mesh.
• Secure service-to-service communications using mutual TLS (mTLS) and Zero Trust principles.
• Monitor, trace, and troubleshoot microservices using Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico for advanced network policies and security.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live lab environment.

Customization Options

• To request customized training for this course, please contact us to arrange.

The advancement of microservices and containers in recent years has profoundly transformed the way we design, develop, deploy, and operate software. Contemporary applications must be optimized for scalability, elasticity, fault tolerance, and adaptability to change. Meeting these new demands requires modern architectures to adopt a distinct set of patterns and practices. This training explores methods to identify, comprehend, and adapt to these evolving requirements.

Audience
This training is designed for individuals who have a basic understanding of container technology and Kubernetes concepts but may lack practical, hands-on experience. The curriculum is grounded in use cases and lessons learned from real-world projects, aiming to inspire participants to build and manage more effective cloud-native applications.

• Developers
• Operations personnel
• DevOps engineers
• QA Engineers
• IT Project Managers

Course Format

• Interactive lectures and discussions
• Extensive exercises and practical activities
• Hands-on implementation in a live-lab environment

Course Customization Options

• To request a customized training session for this course, please contact us to make arrangements.

This instructor-led, live training in Lyon (online or onsite) is designed for engineers looking to utilize Helm to streamline the installation and management of Kubernetes applications.

Upon completion of this training, participants will be able to:

• Install and configure Helm.
• Create reproducible builds for Kubernetes applications.
• Distribute applications as Helm charts.
• Run third-party applications stored as Helm charts.
• Manage Helm package releases.

This instructor-led, live training in Lyon (online or onsite) is aimed at DevOps engineers who wish to use Kubernetes and GitLab to automate the DevOps lifecycle.

By the end of this training, participants will be able to:

• Automate application builds, tests, and deployments.
• Create an automated build infrastructure.
• Deploy an application to a containerized cloud environment.

This instructor-led, live training in Lyon (online or onsite) is designed for Kubernetes practitioners aiming to prepare for the CKS exam.

By the end of this training, participants will understand how to secure Kubernetes environments and container-based applications throughout the various stages of an application's lifecycle: build, deployment, and runtime.

This instructor-led, live training in Lyon (online or onsite) is designed for developers and DevOps engineers who wish to apply a serverless approach to building enterprise applications using Kubernetes.

By the end of this training, participants will be able to:

• Set up and configure the Kubernetes system to begin developing with a serverless architecture.
• Understand the concepts and principles foundational to serverless environments.
• Operate toolchains necessary for serverless development and integrate them with Kubernetes components.
• Practice their skill in the Python programming language and apply it to implement serverless systems.
• Secure enterprise applications deployed through a serverless framework on Kubernetes.
• Utilize modern cloud computing methods to optimize DevOps task processing workflows.

This instructor-led live training in Lyon (online or onsite) targets engineers who want to secure Kubernetes clusters beyond the default security settings.

By the end of this training, participants will be able to:

• Understand the vulnerabilities exposed by a default Kubernetes installation.
• Prevent unauthenticated access to the Kubernetes API, database, and other services.
• Protect a Kubernetes cluster from accidental or malicious access.
• Put together a comprehensive security policy and set of best practices.

This instructor-led, live training in Lyon (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker so as to deploy applications at a larger scale while maintaining control.

By the end of this training, participants will be able to:

• Build their own Docker images.
• Deploy and manager large number of Docker applications .
• Evaluate different container orchestration solutions and choose the most suitable one.
• Set up a continuous integration process for Docker applications.
• Integrate Docker applications with existing continuous tools integration processes.
• Secure their Docker applications.

This seven-day program offers a comprehensive, hands-on journey into designing, deploying, and managing cloud-native applications through modern DevOps practices.

Participants will learn how to design scalable microservices architectures, optimize container environments, and manage production workloads using Kubernetes. The course covers advanced deployment strategies, GitOps-based automation, and observability techniques to ensure system reliability and performance.

A strong emphasis is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The program concludes with the use of AI-powered tools to support troubleshooting and accelerate operational decision-making.

By the end of the training, participants will have a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems in a Kubernetes-based environment.

Docker is an open-source platform designed to automate the process of building, shipping, and running applications within containers.

This instructor-led live training (available online or onsite) is designed for engineers who want to deploy and manage software as containers rather than traditional standalone applications.

Upon completing this training, participants will be able to:

• Install and configure Docker.
• Understand and implement software containerization.
• Manage Docker-based applications.
• Network different Docker applications and systems.
• Understand and edit Docker registries.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Customization Options

• To request customized training for this course, please contact us to arrange it.
• To learn more about Docker, please visit: https://www.docker.com

This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate to advanced DevOps engineers and system administrators who wish to deploy and manage self-hosted Kubernetes clusters without cloud dependencies.

By the end of this training, participants will be able to: deploy production-ready Kubernetes clusters using kubeadm on bare-metal or virtual machines; configure high-availability control planes and etcd clusters; implement container networking and storage for self-managed environments; set up monitoring and observability using self-hosted solutions.

In this instructor-led live training in Lyon, participants will learn the essentials of building microservices using Spring Cloud and Docker. Their understanding will be tested through exercises and the step-by-step development of sample microservices.

By the end of this training, participants will be able to:

• Understand the fundamentals of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerized microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Use Docker Compose for end-to-end integration testing.

OpenShift is one of the leading Kubernetes-based platforms for deploying and managing containerized applications in cloud, hybrid, and on-premises environments.

This hands-on training teaches participants how to install, administer, and troubleshoot OpenShift clusters while applying security, networking, and storage best practices. Through practical exercises, participants gain the skills needed to confidently manage production-ready OpenShift environments.

Discover how to develop, deploy, and manage containerized applications using OpenShift, a leading Kubernetes-based platform for cloud-native development. This practical training covers application deployment, containers, networking, CI/CD, and DevOps workflows, providing participants with the skills necessary to build and maintain modern applications in production environments.

This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level virtualization administrators who wish to use open-source platforms to migrate away from VMware.

By the end of this training, participants will be able to:

• Install and configure KVM, oVirt, and Proxmox VE.
• Migrate virtual workloads from VMware.
• Implement high availability and disaster recovery.
• Optimize performance in open-source virtualization environments.