Containers and Virtual Machines (VMs) Training in Belgrade

Edge AI is an approach centered on executing machine learning inference near data sources to ensure low-latency, efficient, and scalable processing.

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

Upon completing this course, participants will be able to:

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

Format of the Course

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

Course Customization Options

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

Kubernetes is a widely adopted container orchestration platform designed to manage distributed applications at scale.

This instructor-led live training (available online or onsite) targets 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 able 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 mechanisms using reinforcement learning and metric forecasting.
• Reduce infrastructure costs and latency through automated resource optimization.

Format of the Course

• Instructor-guided technical presentations and deep-dive discussions.
• Hands-on lab work using real Kubernetes clusters.
• Practical exercises applying AI models to real 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 either online or onsite, is designed for intermediate-level professionals seeking to construct automated, scalable MLOps pipelines on Kubernetes.

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

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

Course Format

• Instructor-guided presentations and technical deep dives.
• Hands-on exercises designed to build 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 systematic methodology for automating the packaging, testing, containerization, and deployment of models through continuous integration and delivery pipelines.

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

Upon completing the training, participants will be equipped to:

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

Format of the Course

• 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 tailored pipeline workflows or platform integrations, please contact us to customize this course.

This instructor-led live training, conducted in Belgrade (online or onsite), targets advanced-level Kubernetes administrators and DevOps engineers who want 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, available online or on-site, is designed for advanced professionals seeking to architect and implement distributed AI inference systems across diverse environments.

Upon completing this course, participants will be able to:

• Develop secure and scalable containerized AI services tailored for multi-location settings.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Utilize orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across varied 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.

Customization Options

• To tailor this course to align with your organization’s specific infrastructure or 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 onsite) is designed for beginner to intermediate IT professionals who want to learn the core concepts and components of Kubernetes and use it to manage containerized applications at scale.

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

• Understand Kubernetes architecture and components.
• Deploy and manage containers in a Kubernetes cluster.
• Configure networking, storage, and scaling for workloads.
• Troubleshoot common issues and follow best practices for cluster operations.

Format of the Course

• Interactive lecture and discussion.
• Plenty 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.

This instructor-led, live training in Belgrade (available online or onsite) is designed for DevOps engineers and developers who wish to utilize Kubernetes to build, deploy, and manage containers and cluster components within a secure and scalable environment.

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

• Gaining a clear understanding of the architecture, core principles, and components that define the Kubernetes ecosystem.
• Successfully setting up, installing, and configuring a Kubernetes cluster for effective container orchestration.
• Learning how to perform Kubernetes operations using various command-line tools.
• Acquiring hands-on experience spanning 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 aim to develop secure, portable AI inference microservices that can be deployed consistently across local machines, servers, or cloud virtual machines (VMs).

Upon completing this workshop, participants will be able to:

• Create lightweight inference containers for both local and cloud deployment.
• Secure containerized AI services using industry best practices.
• Establish portable microservice workflows to ensure consistent operating environments.
• Deploy AI inference endpoints across diverse infrastructure setups.

Course Format

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

Customization Options

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

In this instructor-led, live training in Belgrade (onsite or remote), participants will learn how to deploy sample servers inside containers, then automate, scale, and manage these containerized servers within a Kubernetes cluster. The training progresses 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.
• Establish a Docker and Kubernetes cluster.
• Utilize Kubernetes to deploy and manage various environments within the same cluster.
• Secure, scale, and monitor a Kubernetes cluster.

GPU acceleration is crucial for executing high-performance deep learning tasks in a scalable and efficient way.

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

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

• Build and run GPU-enabled containers for training and inference.
• Configure CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimize resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerized deep learning services in production environments.

Course Format

• 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 Belgrade (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 Belgrade (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 Belgrade (online or onsite) is designed for advanced-level platform engineers and DevOps professionals who want to master application scaling 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.
• Use 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.

Learn 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 use OpenShift to streamline modern application delivery in 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, live training (available online or onsite) targets intermediate to advanced technical professionals who aim to containerize and operationalize complete ML pipelines using Docker.

Upon 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 complementary tools.
• Implement versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerized environments.

Format of the Course

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centered on building real-world 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 AI and machine learning tasks.

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

Upon completing this course, participants will be able to:

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

Course Format

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

Course Customization Options

• To tailor this training to your organizational needs, please contact us to arrange it.

This instructor-led, live training in Belgrade (online or onsite) is intended for beginner-level developers who wish to learn the basics of Kubefirst and how it simplifies, 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 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 Belgrade (online or onsite) is designed for intermediate-level developers and DevOps engineers who aim to use Minikube as part of their development workflow.

By the end 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 Belgrade (online or onsite) is designed for intermediate developers and DevOps engineers aiming to build, deploy, and manage microservices utilizing Spring Cloud and Docker.

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

• Build microservices utilizing Spring Boot and Spring Cloud.
• Containerize applications using Docker and Docker Compose.
• Deploy service discovery, API gateways, and inter-service communication mechanisms.
• Monitor and secure microservices within production environments.
• Deploy and orchestrate microservices using Kubernetes.

This instructor-led, live training in Belgrade (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.
• Grasp the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Configure persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for application development, testing, and debugging.

Course Objectives: Gain theoretical and operational skills in Docker and Kubernetes.

In this instructor-led live training conducted in Belgrade (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. With over 360 successfully completed training projects, we have become one of the most recognized training providers globally in the field of containerization.

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

This instructor-led, live training (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, so we recommend participation even if you do not intend to take the CKA exam.

Course Format

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

Course Customization Options

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

In this instructor-led live training in Belgrade (online or onsite), attendees 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.

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

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

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

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

Course Format

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

Customization Options

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

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 course in Belgrade 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, offering secure, observable, and manageable connectivity between microservices. By utilizing Istio's Envoy-based sidecar proxies, development teams can enforce strict policies, secure communications via mTLS, achieve deep traffic observability, and enhance reliability at scale.

This instructor-led training, available online or onsite, is designed for intermediate-level engineers seeking to deploy, secure, and manage microservices applications using Istio on Kubernetes.

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

• Install and configure Istio within Kubernetes clusters.
• Comprehend and apply core service mesh concepts, including traffic management, security, and observability.
• Deploy microservices applications into an Istio service mesh environment.
• Secure inter-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.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Customization Options

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

The rapid evolution of microservices and container technologies in recent years has fundamentally transformed the way software is designed, developed, deployed, and operated. Modern applications need to be optimized for scalability, elasticity, fault tolerance, and adaptability. To meet these evolving demands, contemporary architectures require a distinct set of patterns and best practices. This training explores methods for identifying, understanding, and adapting to these new requirements.

Audience
This course is designed for professionals who possess a foundational knowledge of container technology and Kubernetes concepts but may lack hands-on, real-world experience. It draws on use cases and lessons learned from actual projects, aiming to inspire participants to design 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 work
• Hands-on implementation within a live-lab environment

Customization Options

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

This instructor-led, live training in Belgrade (online or onsite) 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 able to:

• Install and configure Helm.
• Build reproducible Kubernetes application deployments.
• Distribute applications as Helm charts.
• Execute third-party applications packaged as Helm charts.
• Manage releases of Helm packages.

This instructor-led live training in Belgrade (online or onsite) targets DevOps engineers who wish to utilize Kubernetes and GitLab to automate their DevOps lifecycle.

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 Belgrade (online or onsite) is designed for Kubernetes practitioners seeking to prepare for the CKS exam.

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

This instructor-led live training in Belgrade (online or onsite) targets developers and DevOps engineers who aim 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 Belgrade (online or on-site) is designed for engineers seeking to fortify Kubernetes clusters beyond default security settings.

Upon completion, participants will be able to:

• Identify vulnerabilities inherent in standard Kubernetes installations.
• Block unauthenticated access to the Kubernetes API, databases, and associated services.
• Safeguard the cluster against both accidental and malicious intrusions.
• Develop a robust security policy and adopt industry best practices.

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

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

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

• Build their own Docker images.
• Deploy and 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.

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

• Create custom Docker images.
• Deploy and manage a high volume of Docker applications.
• Assess various container orchestration solutions and select the most appropriate option.
• Establish a continuous integration pipeline for Docker applications.
• Integrate Docker applications with existing continuous integration workflows.
• Enhance the security of Docker applications.
• Leverage Kubernetes to deploy and manage multiple environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters.

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 process of building, shipping, and running applications within containers.

This instructor-led live training (available online or onsite) targets engineers who want to use Docker to deploy and manage software as containers rather than traditional stand-alone applications.

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

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

Course Format

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

Customization Options

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

This instructor-led, live training in Belgrade (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 in Belgrade, participants will learn the essential principles of developing microservices using Spring Cloud and Docker. Knowledge is tested through exercises and the incremental development of sample microservices.

By the conclusion 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 stands as a leading Kubernetes-based platform for deploying and managing containerized applications in cloud, hybrid, and on-premises environments.

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

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

This instructor-led, live training in Belgrade (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.