Containers and Virtual Machines (VMs) Training in Bratislava

Edge AI represents a paradigm that focuses on executing machine learning inference in close proximity to data sources, thereby enabling low-latency, efficient, and scalable processing.

This instructor-led live training, available both online and onsite, is designed for 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 capable of:

• Establishing lightweight Kubernetes distributions suitable for edge deployments.
• Effectively deploying AI inference workloads across resource-constrained edge nodes.
• Addressing connectivity challenges and implementing synchronization patterns.
• Optimizing performance, storage, and networking for practical edge scenarios.

Course Format

• Guided presentations complemented by real-world examples.
• Scenario-based labs and practical exercises focused on edge deployment.
• Hands-on experience with Kubernetes edge frameworks.

Customization Options

• To arrange customized training tailored to your specific edge platform requirements, please contact us.

Kubernetes is a widely adopted container orchestration platform used for managing distributed applications at scale.

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 decisions in Kubernetes.
• Apply predictive analytics to optimize CPU, GPU, and memory allocation.
• Implement intelligent autoscaling using reinforcement learning and metric forecasting.
• Minimize infrastructure costs and latency through automated resource optimization.

Course Format

• Instructor-guided technical presentations and in-depth discussions.
• Hands-on lab exercises using real Kubernetes clusters.
• Practical exercises involving the application of AI models to real-world operational scenarios.

Course Customization Options

• To tailor this course to your specific platform setup or operational requirements, please contact us for customization.

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 and scalable MLOps pipelines on Kubernetes.

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

• Design end-to-end CI/CD pipelines tailored 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:

• 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 offers 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 on-site, targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completing the training, participants will be able to:

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

Course Format

• 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 Bratislava (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-premises, and edge environments through unified container-based workflows.

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

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

• Create secure and scalable containerized AI services for multi-site environments.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Integrate orchestration tools to automate distributed AI operations.
• Optimize inference latency, reliability, and resilience across diverse infrastructure.

Course Format

• Guided presentations and expert-led discussions.
• Extensive hands-on practice and applied exercises.
• Real-world experimentation in a controlled live-lab setup.

Course Customization Options

• For tailored adjustments to align this course with your organization’s infrastructure or specific use cases, please contact us to customize the training.

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 onsite) targets beginner to intermediate IT professionals seeking to grasp the core concepts and components of Kubernetes, enabling them to manage containerized applications at scale.

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

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

Format of the Course

• 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 for this course, please contact us to arrange.

This instructor-led live training in Bratislava (online or onsite) is tailored 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:

• Comprehend the architecture, core concepts, and key components of a Kubernetes ecosystem.
• Establish, install, and configure a Kubernetes cluster for effective container orchestration.
• Master the execution of Kubernetes operations using command-line tools.
• Gain practical experience ranging 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 online or onsite) targets beginner to intermediate technical professionals who want to develop secure, portable AI inference microservices that can be consistently deployed across local machines, servers, or cloud virtual machines.

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

• Build lightweight inference containers suitable for both local and cloud deployment.
• Secure containerized AI services by applying industry best practices.
• Implement portable microservice workflows to ensure consistent environments.
• Deploy AI inference endpoints across diverse infrastructure setups.

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 a session.

In this instructor-led, live training in Bratislava (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 a critical component for executing high-performance deep learning workloads in a scalable and efficient manner.

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

Upon completing this course, participants will be equipped to:

• Create and operate GPU-enabled containers for both training and inference tasks.
• Set up CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimize resource allocation and isolation for applications that are intensive on GPUs.
• Deploy 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 Bratislava (online or onsite) is designed for intermediate-level professionals looking to effectively deploy, manage, and scale containerized applications using Kubernetes.

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

• Grasp the Kubernetes architecture and its core components.
• Effectively isolate resources 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 Bratislava (online or onsite) is aimed at intermediate-level to advanced-level developers, DevOps professionals, and architects who wish 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 Bratislava (online or onsite) is designed for advanced-level platform engineers and DevOps professionals who want to master application scaling using microservices and Kubernetes.

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

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

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

Docker serves as a containerization platform designed to create reproducible, portable, and scalable environments for machine learning systems.

This instructor-led training, available both online and onsite, targets intermediate to advanced technical professionals aiming to containerize and operationalize complete ML pipelines using Docker.

After completing this training, participants will be capable of:

• Containerizing ML workloads for training, validation, and inference.
• Designing and orchestrating end-to-end ML pipelines with Docker and related tools.
• Implementing versioning, reproducibility, and CI/CD processes for ML components.
• Deploying, monitoring, and scaling ML services within containerized environments.

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centered on constructing real-world ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Course Customization Options

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

This instructor-led live training, available online or onsite, targets intermediate professionals seeking to package ML codebases, dependencies, and models using Docker to ensure reliable development-to-production workflows.

Upon completing this course, participants will be capable of:

• Building and managing Docker images specifically tailored for AI and ML applications.
• Containerizing machine learning pipelines, tools, and dependencies.
• Optimizing Docker environments for improved performance and portability.
• Deploying containerized ML services across diverse runtime environments.

Format of the Course

• Concept demonstrations complemented by guided discussion.
• Hands-on exercises centered on real-world containerization tasks.
• Practical implementation within live-lab Docker environments.

Course Customization Options

• To tailor this training to your organizational needs, please reach out to us to make arrangements.

This instructor-led, live training in Bratislava (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 Bratislava (online or onsite) is designed for intermediate developers and DevOps engineers aiming to utilize Minikube within their development workflows.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and debug applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led, live training in Bratislava (online or onsite) is designed for intermediate-level developers and DevOps engineers who aim 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 Bratislava (online or onsite) is designed for beginner to intermediate software developers and DevOps professionals who wish 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 Bratislava (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) certification program was established by The Linux Foundation in partnership with the Cloud Native Computing Foundation (CNCF).

Kubernetes has become the dominant platform for container orchestration.

Since 2015, NobleProg has been providing Docker and Kubernetes training. With over 360 successfully completed training projects, we have established ourselves as one of the leading training providers globally in the field of containerization.

Since 2019, we have also assisted our clients in validating their expertise in Kubernetes environments by preparing them to successfully pass the CKA and CKAD exams.

This instructor-led, live training (available 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. Therefore, we recommend attending, even if you do not plan to take the CKA exam.

Course Format

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

Course Customization Options

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

In this instructor-led live training in Bratislava (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 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 acquire the skills necessary to operate modern container platforms and troubleshoot applications across development and production environments.

This instructor-led training, available online or on-site, is designed for engineers who want to automate, secure, and monitor containerized applications within large-scale Kubernetes clusters.

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

• Utilize Kubernetes to deploy and manage various environments within a single cluster
• Secure, scale, and monitor a Kubernetes cluster effectively

Course Format

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

Customization Options

• For customized training requests, please contact us to arrange.

The Certified Kubernetes Application Developer (CKAD) certification program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the organization responsible for hosting Kubernetes.

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

Additionally, 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 delivering Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most well-known training providers globally in the field of containerization. Since 2019, we have also assisted our customers in verifying their performance in k8s environments by preparing and encouraging 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-lab environment.

Course Customization Options

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

This instructor-led, live course in Bratislava 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 that enables secure, observable, and manageable connectivity between microservices. By utilizing Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications with mTLS, gain deep observability into traffic, and improve 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 with mutual TLS (mTLS) and Zero Trust principles.
• Monitor, trace, and troubleshoot microservices with Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico for advanced network policies and security.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

The rapid advancement of microservices and container technologies in recent years has fundamentally transformed the way software is designed, developed, deployed, and operated. Modern applications must be engineered for scalability, elasticity, fault tolerance, and adaptability to change. To meet these evolving demands, contemporary architectures rely on a distinct set of patterns and best practices. This training explores methods to identify, comprehend, and adapt to these new requirements.

Target Audience
This training is designed for individuals who possess a foundational understanding of container technology and Kubernetes concepts but may lack extensive real-world experience. Drawing on use cases and lessons learned from actual projects, the course aims to inspire participants to build and manage superior cloud-native applications.

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

Course Format

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

Course Customization Options

• For requests regarding customized training for this course, please contact us to arrange details.

This instructor-led, live training in Bratislava (online or onsite) is designed for engineers who want to use Helm to simplify the installation and management of Kubernetes applications.

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

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

This instructor-led live training in Bratislava (online or onsite) targets DevOps engineers who aim to automate the DevOps lifecycle using Kubernetes and Gitlab.

By the conclusion 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 Bratislava (online or on-site) is targeted at Kubernetes practitioners who wish 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 life cycle: build, deployment, and runtime.

This instructor-led, live training in Bratislava (online or onsite) is aimed at developers and DevOps engineers who wish to utilize a serverless approach for building enterprise applications in 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 Bratislava (online or onsite) is designed for engineers seeking to strengthen their Kubernetes cluster's security beyond default configurations.

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

• Identify vulnerabilities exposed by a standard Kubernetes installation.
• Prevent unauthenticated access to the Kubernetes API, databases, and other services.
• Safeguard the Kubernetes cluster against both accidental and deliberate unauthorized access.
• Develop a comprehensive security policy alongside a set of industry best practices.

The "Advanced Docker and Kubernetes" course is a comprehensive training program covering the Kubernetes platform and its ecosystem. It is designed for participants with varying levels of experience, providing a full range of basic and advanced Kubernetes functionalities. Key concepts covered include Containers, Labels, Controllers, Services, Secrets, Persistent Data Volumes, Namespaces, Quotas, the Container Networking Model, Service Discovery, Scaling, Load Balancing, Cluster Management, Kubernetes Installation, Cluster Security, Access Control, Controller High Availability, Monitoring and Logging, Application Auto-Scaling, Advanced Scheduling, Microservices-based Applications, Application Design Patterns, and Deploying Applications on a Kubernetes Cluster.

This instructor-led, live training in Bratislava (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:

• Create 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 offers 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.

This instructor-led live training, available online or onsite, targets engineers who aim to deploy and manage software as containers using Docker instead of traditional standalone software.

By the end of 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.

This instructor-led, live training in Bratislava (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 located in Bratislava, 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 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 with OpenShift, a leading Kubernetes-based platform for cloud-native development. This hands-on training covers application deployment, containerization, networking, CI/CD, and DevOps workflows, providing participants with the skills to build and maintain modern applications in production environments.

This instructor-led, live training in Bratislava (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.