Containers and Virtual Machines (VMs) Training in Enschede

Edge AI represents a paradigm focused on executing machine learning inference near data sources to deliver low-latency, efficient, and scalable processing.

This instructor-led, live training (available online or onsite) targets intermediate to advanced practitioners who aim to deploy, orchestrate, and optimize AI workloads within Kubernetes-based edge environments.

Upon completing this course, participants will be equipped to:

• Establish lightweight Kubernetes distributions suitable for edge deployments.
• Effectively deploy AI inference workloads across resource-constrained edge nodes.
• Address connectivity challenges and implement synchronization patterns.
• Optimize performance, storage, and networking for real-world edge scenarios.

Course Format

• Guided presentations enriched with real-world examples.
• Scenario-based labs and practical exercises for edge deployment.
• Hands-on experience working with Kubernetes edge frameworks.

Customization Options

• To request training customized to your specific edge platform requirements, please contact us to make arrangements.

Kubernetes is a widely adopted container orchestration platform designed for managing large-scale distributed applications.

This instructor-led live training (available online or onsite) targets advanced practitioners looking to leverage AI and machine learning techniques to optimize resource usage, scheduling decisions, and autoscaling strategies within Kubernetes.

Upon completing this program, participants will be able to:

• Utilize AI/ML models to enhance workload scheduling efficiency in Kubernetes.
• Apply predictive analytics to refine CPU, GPU, and memory allocation.
• Deploy intelligent autoscaling mechanisms using reinforcement learning and metric forecasting.
• Lower infrastructure costs and reduce latency through automated resource optimization.

Course Format

• Instructor-led technical presentations coupled with in-depth discussions.
• Practical lab exercises conducted on real Kubernetes clusters.
• Hands-on exercises that apply AI models to genuine operational scenarios.

Customization Options

• To adapt this course to your specific platform configuration or operational needs, please contact us for customization details.

MLOps on Kubernetes provides 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, is designed for intermediate-level practitioners looking to build automated, scalable MLOps pipelines on Kubernetes.

Upon completion, 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 to build real-world CI/CD workflows.
• Live-lab practice for deploying ML workloads to Kubernetes.

Course Customization Options

• Organizations can 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:

• Navigate the Kubeflow ecosystem and core components.
• Build reproducible workflows with Kubeflow Pipelines.
• Run scalable training jobs on Kubernetes.
• Serve machine learning models efficiently using Kubeflow Serving.

Format of the Course

• 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 systematic methodology for automating the packaging, testing, containerization, and deployment of machine learning models through continuous integration and delivery pipelines.

This instructor-led training (available online or onsite) targets intermediate-level professionals eager to streamline end-to-end AI model delivery workflows by leveraging Docker alongside CI/CD platforms.

Upon completing the training, participants will be able to:

• Design automated pipelines for constructing and testing AI model containers.
• Establish version control and ensure reproducibility throughout the model lifecycle.
• Deploy integrated automation strategies for AI services.
• Apply CI/CD best practices specifically adapted for machine learning operations (MLOps).

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Enschede (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 platforms, on-premise data centers, and edge locations through unified, container-driven workflows.

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

Upon completing this course, participants will be equipped to:

• Develop secure and scalable containerized AI services tailored for multi-site deployments.
• Execute AI inference workloads across cloud servers, local infrastructure, and edge devices using Docker.
• Leverage orchestration tools to automate distributed AI operations effectively.
• Enhance inference speed, reliability, and resilience across diverse technical landscapes.

Course Format

• In-depth presentations led by industry experts.
• Substantial practical exercises and real-world application sessions.
• Hands-on experimentation within a controlled, live laboratory environment.

Customization Opportunities

• To adapt this course specifically to your organization’s infrastructure or unique use cases, please reach out to discuss customization options.

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

This instructor-led live training (available online or on-site) targets beginner to intermediate IT professionals eager to master the core concepts and components of Kubernetes, enabling them to manage containerized applications at scale.

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

• Grasp the architecture and key 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.

Format of the Course

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

Course Customization Options

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

This instructor-led live training, held in Enschede (online or onsite), is designed for DevOps engineers and developers who wish to utilize 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 live training, available either online or onsite, targets beginner to intermediate technical professionals who aim to develop secure, portable microservices for AI inference. These services can be consistently deployed across local machines, servers, or cloud VMs.

Upon completing this workshop, participants will be equipped with the following capabilities:

• Construct lightweight inference containers suitable for both local and cloud deployment.
• Enhance the security of containerized AI services by applying best-practice techniques.
• Establish portable microservice workflows to ensure consistent environments.
• Deploy AI inference endpoints across various infrastructures.

Course Format

• A combination of guided lectures and practical demonstrations.
• Hands-on exercises designed to reinforce deployment and security techniques.
• Live lab sessions focused on building and running portable inference services.

Course Customization Options

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

In this instructor-led live training in Enschede (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.

GPU acceleration is critical for executing high-performance deep learning workloads in a scalable and efficient manner.

This instructor-led, live training (available online or onsite) targets intermediate-level technical professionals seeking to configure, optimize, and deploy GPU-enabled AI workloads within Docker containers.

Upon completing this course, participants will be capable of:

• Constructing and running GPU-enabled containers for both training and inference tasks.
• Setting up CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimizing resource allocation and isolation for GPU-intensive applications.
• Deploying scalable, containerized deep learning services in production environments.

Format of the Course

• Interactive instruction supported by real-world demonstrations.
• Exercise-driven practice focused on GPU-enabled development.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For tailored training aligned with your infrastructure or GPU stack, please contact us to arrange.

This instructor-led, live training in Enschede (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 Enschede (online or onsite) is designed for intermediate to advanced developers, DevOps professionals, and architects who want to design, deploy, and manage resilient applications using 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 Enschede (online or on-site) 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.

Master the fundamentals of containers, Kubernetes, and OpenShift in a practical, hands-on training designed for developers, DevOps engineers, and IT professionals. Participants will learn how to build containerized applications, deploy workloads, manage Kubernetes resources, and utilize OpenShift to streamline modern application delivery in cloud and hybrid environments.

Docker serves as a containerization platform designed to build reproducible, portable, and scalable environments for ML systems.

This instructor-led live training (available online or onsite) targets intermediate to advanced technical professionals who aim to containerize and operationalize complete ML pipelines using Docker.

After completing this training, participants will be able to:

• Containerize ML training, validation, and inference workloads.
• Design and orchestrate end-to-end ML pipelines using Docker and supporting tools.
• Implement versioning, reproducibility, and CI/CD for ML components.
• Deploy, monitor, and scale ML services in containerized environments.

Course Format

• Interactive lectures supported by practical demonstrations.
• Hands-on exercises focused on building real ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Course Customization Options

• For customized training aligned with specific ML infrastructure needs, please contact us to discuss options.

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

This instructor-led live training (available online or onsite) targets intermediate-level professionals who aim to package ML codebases, dependencies, and models using Docker to establish reliable workflows from development to production.

Upon completing this course, participants will be able to:

• Build and manage Docker images specifically designed for AI and ML applications.
• Containerize machine learning pipelines, tools, and their dependencies.
• Optimize Docker environments for enhanced performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Concept demonstrations supported by guided discussion.
• Hands-on exercises focused on real-world containerization tasks.
• Practical implementation using live-lab Docker environments.

Course Customization Options

• To customize this training for your organizational environment, please contact us to arrange.

This instructor-led live training in Enschede (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 Enschede (online or onsite) targets intermediate-level developers and DevOps engineers eager to integrate Minikube into their development workflows.

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

• Establish and manage a local Kubernetes environment using Minikube.
• Gain insights into deploying, managing, and troubleshooting applications on Minikube.
• Integrate Minikube seamlessly into continuous integration and deployment pipelines.
• Enhance their development process by leveraging Minikube’s advanced features.
• Adopt best practices for local Kubernetes development.

This instructor-led live training in Enschede (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 Enschede (online or onsite) targets 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 basic concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Utilize Minikube for developing, testing, and debugging applications.

Training objectives: Acquire theoretical and practical skills in Docker and Kubernetes.

In this instructor-led live training in Enschede (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) credential was established by The Linux Foundation in partnership with the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as the leading platform for container orchestration.

Since 2015, NobleProg has specialized in delivering Docker and Kubernetes training. With over 360 successfully completed training projects, we have established ourselves as one of the globally recognized leaders in containerization education.

Since 2019, we have further supported our customers by helping them validate their expertise in Kubernetes environments through rigorous preparation for the CKA and CKAD examinations.

This instructor-led live training (available online or onsite) is designed for System Administrators and Kubernetes practitioners seeking to validate their skills by passing the CKA exam.

Additionally, the course emphasizes gaining practical experience in Kubernetes administration. Therefore, we recommend participating even if you do not plan to sit for the CKA exam.

Course Format

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

Customization Options

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

In this instructor-led live training in Enschede (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.

Learn how to build, deploy, and administer containerized environments using Docker, Kubernetes, and OpenShift. This five-day, hands-on training covers container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants gain the skills needed to operate modern container platforms and troubleshoot applications across development and production environments.

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

By the conclusion of this course, participants will be able to:

• Leverage Kubernetes to deploy and manage multiple environments within a single cluster
• Secure, scale, and monitor a Kubernetes environment

Course Format

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

Customization Options

• For information regarding customized training for this course, please contact us to make arrangements.

The Certified Kubernetes Application Developer (CKAD) certification is administered by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

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

Additionally, the course emphasizes practical experience in Kubernetes application development. We recommend participating even if you do not plan to take the CKAD exam.

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

Course Format

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

Course Customization Options

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

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

Istio serves as an open-source service mesh operating on Kubernetes to deliver secure, observable, and manageable connectivity between microservices. By utilizing Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications through mTLS, gain deep traffic observability, 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 capable of:

• Installing and configuring Istio on Kubernetes clusters.
• Understanding and applying service mesh concepts such as traffic management, security, and observability.
• Deploying microservices applications within an Istio service mesh.
• Securing service-to-service communications using mutual TLS (mTLS) and Zero Trust principles.
• Monitoring, tracing, and troubleshooting microservices with Prometheus, Grafana, and Jaeger.
• Integrating Istio with Calico for advanced network policies and security.

Course Format

• Interactive lecture and discussion.
• Numerous exercises and practical sessions.
• Hands-on implementation in a live laboratory environment.

Customization Options

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

In recent years, the advancement of microservices and container technologies has fundamentally transformed how software is designed, developed, deployed, and operated. To meet these modern demands, applications must be optimized for scalability, elasticity, fault tolerance, and adaptability. Consequently, contemporary architectures necessitate a distinct set of patterns and practices. This training explores methods to identify, comprehend, and adapt to these evolving requirements.

Audience
This course is designed for professionals who possess a foundational knowledge of container technology and Kubernetes concepts but may lack extensive practical experience. Rooted in use cases and lessons learned from real-world projects, the training aims to inspire participants to design and manage superior cloud-native applications.

• Developers
• Operations Specialists
• DevOps Engineers
• QA Engineers
• IT Project Managers

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Enschede (delivered online or on-site) is designed for engineers looking to utilize Helm to simplify the installation and management of Kubernetes applications.

Upon completion of this training, participants will be capable of:

• Installing and configuring Helm.
• Generating reproducible builds for Kubernetes applications.
• Distributing applications as Helm charts.
• Executing third-party applications packaged as Helm charts.
• Administering releases of Helm packages.

This instructor-led, live training in Enschede (online or on-site) is designed for DevOps engineers who wish to utilize 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 Enschede (online or onsite) is aimed at Kubernetes practitioners who wish to prepare for the CKS exam.

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

This instructor-led, live training in Enschede (online or onsite) is targeted at developers and DevOps engineers who wish to adopt a serverless approach for constructing enterprise applications using Kubernetes.

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

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

This instructor-led live training in Enschede (online or onsite) targets engineers seeking to enhance Kubernetes cluster security beyond default settings.

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

• Understand 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 Enschede (online or onsite) is designed for engineers who wish to advance their knowledge of Docker 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 manage a 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 7-day programme provides a comprehensive, hands-on journey into designing, deploying, and operating cloud-native applications using modern DevOps practices.

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

A strong focus is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme 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 creation, distribution, and execution of applications within containers.

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

Upon completing this training, participants will be able to:

• Install and configure Docker.
• Grasp and implement software containerization principles.
• Manage applications built on Docker.
• Network various Docker applications and systems effectively.
• Understand and edit Docker registries.

Course Format

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

Customization Options

• To request tailored training for this course, please contact us to make arrangements.
• For more information on Docker, visit: https://www.docker.com

This instructor-led, live training in Enschede (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 held at Enschede, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge is put to the test 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 a leading Kubernetes-based platform for deploying and managing containerized applications in cloud, hybrid, and on-premises environments.

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

Learn how to develop, deploy, and manage containerized applications with OpenShift, one of the leading Kubernetes-based platforms for cloud-native development. This practical training covers application deployment, containers, networking, CI/CD, and DevOps workflows, giving participants the skills to build and maintain modern applications in production environments.

This instructor-led, live training in Enschede (online or onsite) is targeted at intermediate-level virtualization administrators who wish to utilize open-source platforms for migrating 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.