Containers and Virtual Machines (VMs) Training in Nicosia

Edge AI refers to the approach of executing machine learning inference close to data sources to enable low-latency, efficient, and scalable processing.

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

Upon completing this course, participants will be able to:

• Set up lightweight Kubernetes distributions suitable for edge deployments.
• Deploy AI inference workloads effectively on constrained edge nodes.
• Address connectivity challenges and implement synchronization patterns.
• Optimize performance, storage, and networking for real-world edge scenarios.

Course Format

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

Course Customization Options

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

Kubernetes serves as a premier container orchestration platform, extensively utilized for managing distributed applications at scale.

This instructor-led live training, available online or onsite, is designed for advanced practitioners seeking to leverage AI and machine learning techniques to optimize Kubernetes resource usage, scheduling decisions, and autoscaling strategies.

Upon completing this program, participants will be equipped to:

• Apply AI/ML models to enhance workload scheduling decisions within Kubernetes.
• Utilize predictive analytics to optimize CPU, GPU, and memory allocation.
• Implement intelligent autoscaling solutions using reinforcement learning and metric forecasting.
• Reduce infrastructure costs and latency through automated resource optimization.

Course Format

• Instructor-guided technical presentations coupled with in-depth discussions.
• Hands-on lab sessions utilizing real-world Kubernetes clusters.
• Practical exercises focused on applying AI models to actual operational scenarios.

Customization Options

• To tailor this course to your specific platform setup or operational needs, 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, targets intermediate-level practitioners aiming to construct automated, scalable MLOps pipelines on Kubernetes.

Upon completion, participants will be capable of:

• Designing end-to-end CI/CD pipelines for machine learning.
• Implementing GitOps workflows for model deployment and versioning.
• Automating the training, testing, and packaging of ML models.
• Integrating monitoring, alerting, and rollback strategies.

Course Format

• Instructor-guided presentations and technical deep dives.
• Hands-on exercises focused on building real-world CI/CD workflows.
• Live-lab practice for 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 represents a structured methodology for automating the packaging, testing, containerization, and deployment of AI models via continuous integration and delivery pipelines.

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

Upon completing the training, participants will be equipped to:

• Establish automated pipelines for constructing and testing AI model containers.
• Enforce version control and reproducibility throughout model lifecycles.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for machine learning operations.

Course Format

• Instructor-led presentations coupled with 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 Nicosia (online or onsite) is designed for advanced-level Kubernetes administrators and DevOps engineers who want to improve 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 using unified, container-based workflows.

This instructor-led live training, available online or on-site, targets advanced professionals seeking to design and deploy distributed AI inference systems across heterogeneous environments.

Upon completing this training, participants will be capable of:

• Developing secure and scalable containerized AI services for multi-location settings.
• Deploying AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Integrating orchestration tools to automate distributed AI operations.
• Optimizing 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 within a controlled live-lab environment.

Course Customization Options

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

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, is tailored for IT professionals at beginner to intermediate levels who wish to master the core concepts and components of Kubernetes and leverage it to manage containerized applications at scale.

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

• Comprehend Kubernetes architecture and its constituent components.
• Deploy and manage containers within a Kubernetes cluster.
• Configure networking, storage, and scaling mechanisms 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 make arrangements.

This instructor-led live training Nicosia (online or on-site) 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, is designed for technical professionals at a beginner to intermediate level who aim to develop secure, portable AI inference microservices that can be deployed consistently across local machines, servers, or cloud VMs.

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

• Create 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 a variety of 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.

Course 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 Nicosia (onsite or remote), participants will learn how to deploy sample servers within containers and subsequently automate, scale, and manage these services in a Kubernetes cluster. The training covers advanced topics, guiding participants through the processes of securing, networking, and monitoring a Kubernetes environment.

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

• Set up and run Docker containers.
• Deploy containerized databases and servers.
• Configure a Docker and Kubernetes cluster.
• Utilize Kubernetes to deploy and manage multiple environments within the same cluster.
• Secure, scale, and monitor a Kubernetes cluster.

Harnessing GPU acceleration is crucial for executing high-performance deep learning workloads efficiently and at scale.

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

Upon completing this course, participants will be capable of:

• Constructing and executing containers equipped with GPU support for both training and inference tasks.
• Setting up CUDA, drivers, and runtime libraries specifically for containerized AI workflows.
• Optimizing resource allocation and isolation for applications that are intensive on GPUs.
• Deploying scalable, containerized deep learning services within production environments.

Course Format

• Interactive instruction complemented by real-world demonstrations.
• Exercise-driven practice centered on GPU-enabled development.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For specialized training tailored to your specific infrastructure or GPU stack, please reach out to us to make arrangements.

This instructor-led, live training in Nicosia (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 Nicosia (online or onsite) is aimed at intermediate to advanced 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 Nicosia (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.

Master the essentials of containers, Kubernetes, and OpenShift through a practical, hands-on training programme designed specifically for developers, DevOps engineers, and IT professionals. Attendees will learn how to construct 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 construct reproducible, portable, and scalable environments for machine learning systems.

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

By the end of this training, participants will be capable of:

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

Course Format

• Interactive lectures accompanied by practical demonstrations.
• Hands-on exercises centered on building real-world ML pipeline components.
• Live laboratory sessions for implementing end-to-end containerized workflows.

Course Customization 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, is designed for intermediate professionals seeking to package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development to production.

Upon completing this course, participants will be equipped to:

• Create and manage Docker images specifically tailored for AI and ML applications.
• Containerize machine learning pipelines, tools, and their associated dependencies.
• Optimize Docker environments to enhance performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Conceptual demonstrations accompanied by guided discussion.
• Practical exercises focusing on real-world containerization challenges.
• Hands-on implementation within live-lab Docker environments.

Customization Options

• To tailor this training to your organization's specific needs, please get in touch with us to arrange a customized session.

This instructor-led, live training in Nicosia (online or onsite) is tailored for beginner-level developers who wish to learn the fundamentals of Kubefirst and understand how it streamlines, secures, and accelerates Kubernetes and Swarm cluster management at an enterprise scale.

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

• Set up a Kubefirst development environment.
• Write and execute a basic Kubefirst program.
• Annotate code with Kubefirst directives and clauses.
• Utilize Kubefirst APIs and libraries.
• Profile and debug Kubefirst programs.

This instructor-led, live training in Nicosia (online or onsite) targets intermediate-level developers and DevOps engineers who intend to use Minikube as part of their development workflow.

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 Nicosia (online or onsite) is designed for 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 Nicosia (online or onsite) is aimed at beginner to intermediate-level software developers and DevOps professionals who want to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local machines.
• Grasp 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.
• Utilize Minikube for developing, testing, and debugging applications.

Training Objectives: Acquire theoretical and operational skills in Docker and Kubernetes.

In this instructor-led, live training in Nicosia (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).

Today, Kubernetes stands as a leading platform for container orchestration.

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

Since 2019, we have also been assisting our customers in validating their performance within Kubernetes environments by preparing them to 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 participating even if you do not intend to take the CKA exam.

Course Format

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

Course Customization Options

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

In this instructor-led, live training in Nicosia (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 required to build, deploy, and administer containerized environments utilizing Docker, Kubernetes, and OpenShift. This intensive five-day, hands-on training encompasses container images, Kubernetes workloads, cluster networking, storage solutions, security protocols, monitoring techniques, and practical OpenShift administration. Attendees will acquire the necessary expertise to operate modern container platforms effectively and troubleshoot applications across both development and production landscapes.

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

Upon completion, participants will be able to:

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

Course Format

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

Customization Options

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

The Certified Kubernetes Application Developer (CKAD) program has been developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host of Kubernetes.

This instructor-led, live training (online or onsite) is aimed at Developers who wish to confirm their skills in design, build, configure, and expose cloud native applications for Kubernetes.

On the other hand, training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part in it, even if you don't intend to take CKAD exam.

NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training company worldwide in field of containerization. Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.

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.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live training session, held in Nicosia, 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 to operate on Kubernetes, delivering secure, observable, and manageable connectivity between microservices. By utilizing Istio’s Envoy-based sidecar proxies, engineering teams can enforce policies, secure communications via mTLS, achieve 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 completion of this training, participants will be able to:

• Install and configure Istio on Kubernetes clusters.
• Comprehend and apply service mesh concepts, including traffic management, security, and observability.
• Deploy microservices applications within an Istio service mesh environment.
• 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 to implement advanced network policies and security measures.

Course Format

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

Course Customization Options

• For customized training requests, please contact us to make arrangements.

The rapid advancement of microservices and container technologies in recent years has fundamentally transformed software design, development, deployment, and operation. Contemporary applications demand optimization for scalability, elasticity, resilience, and adaptability. Responding to these evolving requirements, modern architectures necessitate a distinct set of patterns and best practices. This training explores strategies to identify, comprehend, and adapt to these new demands.

Target Audience
This course is designed for professionals who possess a foundational understanding of container technology and Kubernetes concepts but may lack practical, real-world experience. Drawing on use cases and lessons learned from actual projects, the training 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
• Numerous exercises and practical sessions
• Hands-on implementation within a live-lab environment

Course Customization Options

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

This instructor-led, live training in Nicosia (online or onsite) is aimed at engineers who wish to use Helm to streamline the process of installing and managing Kubernetes applications.

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

• Install and configure Helm.
• Create reproducible builds of Kubernetes applications.
• Share applications as Helm charts.
• Run third-party applications saved as Helm charts.
• Manage releases of Helm packages.

This instructor-led, live training in Nicosia (online or on-site) targets 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 Nicosia (online or onsite) is tailored for Kubernetes professionals 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 6]loc> (available online or onsite) is tailored for developers and DevOps engineers who aim to adopt a serverless approach for developing enterprise applications in Kubernetes.

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

• Set up and configure Kubernetes to initiate development using a serverless architecture.
• Grasp the core concepts and principles underpinning serverless environments.
• Manage the toolchains essential for serverless development and integrate them with Kubernetes components.
• Apply their Python programming skills to implement serverless systems.
• Secure enterprise applications deployed via serverless frameworks on Kubernetes.
• Leverage modern cloud computing techniques to optimize DevOps task processing workflows.

This instructor-led, live training in Nicosia (online or onsite) is aimed at engineers who wish to secure a Kubernetes cluster beyond the default security settings.

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

• Understand the vulnerabilities that are 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 Nicosia (online or on-site) 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.

Upon completion, participants will be able to:

• Create custom Docker images.
• Deploy and manage a high volume of Docker applications.
• Evaluate various container orchestration solutions and select the most appropriate option.
• Establish a continuous integration workflow for Docker applications.
• Integrate Docker applications with existing continuous integration toolchains.
• Implement security measures for Docker applications.
• Leverage Kubernetes to deploy and manage diverse environments within a single cluster.
• Secure, scale, and monitor a Kubernetes cluster effectively.

This 7-day programme offers a comprehensive, practical immersion into designing, deploying, and operating cloud-native applications through modern DevOps methodologies.

Participants will learn how to architect scalable microservices systems, optimise container environments, and manage production workloads with Kubernetes. The curriculum covers advanced deployment strategies, GitOps-driven automation, and observability techniques to guarantee system reliability and performance.

A significant emphasis is placed on overcoming real-world operational hurdles, such as incident response, failure simulation, and root cause analysis. The programme concludes by introducing AI-powered tools to aid troubleshooting and expedite operational decision-making.

Upon completion of the training, participants will possess a clear understanding of how to build, deploy, monitor, and sustain resilient distributed systems within a Kubernetes-based ecosystem.

This instructor-led live training in Nicosia (online or onsite) is tailored for engineers who want to deploy and manage software as containers using Docker, rather than as conventional standalone applications.

By the conclusion 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 Nicosia (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.

During this instructor-led live training in Nicosia, participants will learn the essentials of developing microservices using Spring Cloud and Docker. Understanding is validated through practical exercises and the incremental development of sample microservices.

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

• Understand the core principles 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.
• Utilize 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.

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 Nicosia (online or onsite) is designed for intermediate-level virtualization administrators who wish to utilize 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.