Whether conducted online or onsite, instructor-led live training on Containers and Virtual Machines (VMs) provides practical, hands-on instruction covering both foundational concepts and advanced topics.
Training in Containers and Virtual Machines (VMs) is offered in two formats: 'online live training' or 'onsite live training.' Online live training (also referred to as 'remote live training') is delivered via an interactive remote desktop. Onsite live training can be conducted locally at the client's premises in Transylvania or at NobleProg's corporate training centers in Transylvania.
NobleProg -- Your Local Training Provider
Brasov, Calea Bucuresti Street
NobleProg Brasov, 13 Calea Bucuresti Street Sacele, Brasov, romania, 505600
The hotel is situated at the city entrance, being the best conference and training location in Brasov. Three conference rooms can accommodate up to 170 guests and can be modified for the company needs. These training rooms are equipped with the all necessities of a good conference or training.
Salile de training sunt situate central în Sibiu, pe principalul bulevard. Clădirea hotelului care le gazduieste este de factură clasicistă si reprezinta un punct de referinta arhitecturala a orasului.
Turnul Sfatului, Galeria de Arta Contemporana, sau parcurile Corneliu Coposu si Astra se află în imediata apropiere.
Pentru a ajunge aici de la gara, puteti merge pe jos 20min sau cu autobuzul 5 circa 10min
Locuri de parcare găsiți în parcarea supravegheata, sau pe străzile alăturate.
Cluj-Napoca, Pitești Street
NobleProg Cluj-Napoca, Strada Pitești 19, Cluj-Napoca, romania, 400124
ClujHUB has more rooms for events and training sessions, which can host from 4 to 80 people. These areas can be setup up to fit the companies need. The location is great, 10 minutes walk from the historical city center.
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 online or onsite) is designed for intermediate to advanced practitioners who aim to deploy, orchestrate, and optimize AI workloads within Kubernetes-based edge environments.
Upon completion of this course, participants will be equipped to:
Establish lightweight Kubernetes distributions suitable 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 practical 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 customized training tailored to your specific edge platform requirements, please contact us to arrange.
Kubernetes serves as a widely adopted container orchestration platform for managing large-scale distributed applications.
This instructor-led, live training (available online or onsite) targets advanced practitioners seeking to leverage AI and machine learning techniques to enhance Kubernetes resource usage, refine scheduling decisions, and improve autoscaling strategies.
Upon completing this program, participants will be equipped to:
Deploy AI/ML models to enhance workload scheduling within Kubernetes.
Utilize predictive analytics to optimize CPU, GPU, and memory allocation.
Implement intelligent autoscaling through reinforcement learning and metric forecasting.
Lower infrastructure costs and latency via automated resource optimization.
Course Format
Instructor-led technical presentations accompanied by in-depth discussions.
Practical lab sessions using real-world Kubernetes clusters.
Hands-on exercises applying AI models to actual operational scenarios.
Customization Options
To customize this course for your specific platform setup or operational needs, please contact us.
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 seeking to build automated, scalable MLOps pipelines on Kubernetes.
Upon completion of this training, participants will be able to:
Design end-to-end CI/CD pipelines for machine learning.
Implement GitOps workflows for model deployment and versioning.
Automate the training, testing, and packaging of ML models.
Integrate monitoring, alerting, and rollback strategies.
Course Format
Instructor-guided presentations and technical deep dives.
Hands-on exercises 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 systematic method for automating the packaging, testing, containerization, and deployment of models through continuous integration and continuous delivery pipelines.
This instructor-led, live training, available both online and onsite, targets intermediate-level professionals seeking to streamline end-to-end AI model delivery workflows using Docker and CI/CD platforms.
Upon completing the training, participants will be equipped to:
Construct automated pipelines for building and testing AI model containers.
Establish version control and reproducibility standards throughout the model lifecycle.
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 in a controlled environment.
Course Customization Options
Should your organization require customized pipeline workflows or specific platform integrations, please contact us to tailor this course accordingly.
This instructor-led live training in Transylvania (online or onsite) targets 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 through unified container-based workflows.
This instructor-led, live training (available online or onsite) targets advanced professionals aiming to design and deploy distributed AI inference systems within heterogeneous environments.
After completing this training, participants will be equipped to:
Construct secure and scalable containerized AI services for multi-location settings.
Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
Integrate orchestration tools to automate distributed AI operations.
Enhance 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 environment.
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) is designed for IT professionals ranging from beginner to intermediate levels who wish to understand 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 the architecture and 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.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical application.
Hands-on implementation in a live-lab environment.
Course Customization Options
To arrange a customized training session for this course, please contact us.
This instructor-led live training in Transylvania (available 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, targets technical professionals ranging from beginner to intermediate levels who aim to build secure, portable AI inference microservices. These services can be deployed consistently across local machines, servers, or cloud virtual machines.
Upon completion 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 best-practice techniques.
Implement portable microservice workflows to ensure consistent environments.
Deploy AI inference endpoints across diverse infrastructures.
Course Format
Guided lectures combined with practical demonstrations.
Hands-on exercises to reinforce deployment and security techniques.
Live-lab practice for building and running portable inference services.
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 in Transylvania (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.
Leveraging GPU acceleration is crucial for executing high-performance deep learning tasks in a manner that is both scalable and efficient.
This instructor-led live training, available online or on-site, targets intermediate-level technical professionals looking to configure, optimize, and execute GPU-enabled AI workloads within Docker containers.
Upon completing this course, participants will be equipped to:
Construct and operate GPU-enabled containers for model training and inference.
Set up CUDA, drivers, and runtime libraries specifically for containerized AI workflows.
Fine-tune resource allocation and ensure isolation for GPU-heavy applications.
Deploy scalable, containerized deep learning services within production environments.
Course Format
Interactive instruction reinforced by real-world demonstrations.
Practical exercises centered on GPU-enabled development.
Hands-on implementation within a live laboratory setting.
Customization Options
For customized training tailored to your specific infrastructure or GPU stack, please reach out to us to arrange.
This instructor-led, live training in Transylvania (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.
This instructor-led, live training in Transylvania (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 Transylvania (available online or onsite) is designed for advanced platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes.
Upon completion of this training, participants will be able to:
Design and implement scalable microservices architectures.
Deploy and manage applications within Kubernetes clusters.
Utilize Helm charts for efficient service deployment.
Monitor and maintain the health of microservices in production environments.
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 both online and onsite, targets intermediate to advanced technical professionals seeking to containerize and operationalize entire ML pipelines using Docker.
Upon completing this training, participants will be equipped to:
Containerize workloads related to ML training, validation, and inference.
Design and orchestrate end-to-end ML pipelines utilizing 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 supported by practical demonstrations.
Hands-on exercises focused 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 delivers consistent, portable, and reproducible environments specifically designed for artificial intelligence and machine learning workloads.
This instructor-led live training, available online or onsite, targets intermediate-level 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 able to:
Create and manage Docker images customized for AI and ML applications.
Containerize machine learning pipelines, tools, and associated dependencies.
Optimize Docker environments for enhanced 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 environment, please contact us to make arrangements.
This instructor-led live training in Transylvania (online or onsite) is designed for beginner-level developers seeking to learn the fundamentals of Kubefirst and how it simplifies, secures, and accelerates Kubernetes and Swarm cluster management at an enterprise scale.
By the conclusion 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.
This instructor-led, live training in Transylvania (online or onsite) is designed for intermediate-level developers and DevOps engineers looking to incorporate Minikube into their development workflows.
Upon completion of this training, participants will be able to:
Set up and manage a local Kubernetes environment using Minikube.
Gain an understanding of how to deploy, manage, and debug applications on Minikube.
Integrate Minikube into continuous integration and deployment pipelines.
Optimize their development process by leveraging Minikube's advanced features.
Apply best practices for local Kubernetes development.
This instructor-led live training, conducted Transylvania (online or onsite), targets intermediate developers and DevOps engineers seeking to build, deploy, and manage microservices using Spring Cloud and Docker.
By the conclusion 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 Transylvania (online or onsite) is designed for beginner to intermediate software developers and DevOps professionals who want to learn how to set up and manage a local Kubernetes environment using Minikube.
By the end of this training, participants will be able to:
Install and configure Minikube on their local machine.
Understand the basic concepts and architecture of Kubernetes.
Deploy and manage containers using kubectl and the Minikube dashboard.
Set up persistent storage and networking solutions for Kubernetes.
Utilize Minikube for developing, testing, and debugging applications.
In this instructor-led, live training in Transylvania (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.
The Certified Kubernetes Administrator (CKA) certification was established by The Linux Foundation in collaboration with the Cloud Native Computing Foundation (CNCF).
Kubernetes has emerged as the premier platform for container orchestration.
Since 2015, NobleProg has specialized in Docker and Kubernetes training. With over 360 successfully delivered training projects, we have become one of the world’s most recognized training providers in the field of containerization.
Since 2019, we have further supported our customers by preparing them to validate their performance in Kubernetes environments through 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 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 it.
For more information about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka
In this instructor-led, live training in Transylvania (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.
In this instructor-led, live training in Transylvania, participants will acquire the skills necessary to manage the Red Hat OpenShift Container Platform.
Upon completion of this training, participants will be capable of:
Creating, configuring, managing, and troubleshooting OpenShift clusters.
Deploying containerized applications on-premise, in public cloud environments, or on hosted cloud services.
Implementing security measures for OpenShift Container Platform
This instructor-led, live training (available online or on-site) is designed for engineers who want to automate, secure, and monitor containerized applications within large-scale Kubernetes clusters.
Upon completion of this training, participants will be capable of:
Deploying and managing diverse environments within a single Kubernetes cluster
Securing, scaling, and monitoring a Kubernetes cluster
Course Format
Interactive lectures and discussions
Numerous 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.
The Certified Kubernetes Application Developer (CKAD) program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.
This instructor-led live training (available online or onsite) targets developers who wish to validate their ability to design, build, configure, and expose cloud-native applications on Kubernetes.
Additionally, the training emphasizes gaining practical experience in Kubernetes application development, so we encourage participation even if you do not plan to take the CKAD exam.
NobleProg has delivered Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training companies globally in the field of containerization. Since 2019, we have also assisted our customers in validating their performance in Kubernetes environments by preparing and encouraging them to pass the CKA and CKAD exams.
Format of the Course
Interactive lecture and discussion.
Ample exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request customized training for this course, please contact us to arrange.
To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/
This instructor-led, live course in Transylvania 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 run on Kubernetes, enabling secure, observable, and manageable communication between microservices. By utilizing Istio’s Envoy-based sidecar proxies, development 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 on-site, targets intermediate-level engineers looking to deploy, secure, and manage microservices applications using Istio within Kubernetes environments.
Upon completion of this training, participants will be capable of:
Installing and configuring Istio on Kubernetes clusters.
Understanding and applying service mesh concepts such as traffic management, security, and observability.
Deploying microservices applications within an Istio service mesh.
Securing service-to-service communications using mutual TLS (mTLS) and Zero Trust principles.
Monitoring, tracing, and troubleshooting microservices with Prometheus, Grafana, and Jaeger.
Integrating Istio with Calico for advanced network policies and enhanced security.
Course Format
Interactive lectures and discussions.
Numerous exercises and practical activities.
Hands-on implementation within a live-lab environment.
Customization Options
To arrange a customized training session for this course, please contact us.
The rapid advancement of microservices and container technologies in recent years has fundamentally transformed how we design, develop, deploy, and operate software. Today's applications must be engineered to excel in scalability, elasticity, resilience, and adaptability. Addressing these modern challenges necessitates a fresh set of architectural patterns and best practices. This training explores methods to identify, comprehend, and adapt to these evolving requirements.
Audience
This course is designed for professionals who possess a foundational understanding of container technology and Kubernetes concepts but may lack extensive practical experience. Drawing from real-world use cases and lessons learned from live projects, the curriculum aims 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 sessions
Hands-on implementation within a live-lab environment
Customization Options
To arrange a customized training session for this course, please contact us.
This instructor-led, live training in Transylvania (online or onsite) is designed for engineers looking to leverage Helm to streamline the installation and management of Kubernetes applications.
Upon completion of this training, participants will be able to:
Install and configure Helm.
Create reproducible builds of Kubernetes applications.
Share applications as Helm charts.
Run third-party applications saved as Helm charts.
This instructor-led live training in Transylvania (online or onsite) targets DevOps engineers who aim to use Kubernetes and GitLab to automate their 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 Transylvania (online or onsite) is aimed at Kubernetes practitioners who wish to prepare for the CKS exam.
By the end of this training, participants will know how to secure Kubernetes environments and container-based applications throughout the different stages of an application's life cycle: build, deployment and runtime.
This instructor-led live training in Transylvania (online or onsite) is designed for 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 Transylvania (online or onsite) is tailored for engineers who wish to enhance the security of their Kubernetes cluster beyond the default security settings.
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, database, and other critical services.
Protect the cluster from both accidental and malicious intrusions.
Develop a comprehensive security policy along with a set of best practices.
This instructor-led, live training in Transylvania (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker so as to deploy applications at a larger scale while maintaining control.
By the end of this training, participants will be able to:
Build their own Docker images.
Deploy and manager large number of Docker applications .
Evaluate different container orchestration solutions and choose the most suitable one.
Set up a continuous integration process for Docker applications.
Integrate Docker applications with existing continuous tools integration processes.
This intensive 7-day program offers a comprehensive, practical exploration into the design, deployment, and operation of cloud-native applications using contemporary DevOps methodologies.
Attendees will delve into the creation of scalable microservices architectures, the optimization of containerized environments, and the management of production workloads via Kubernetes. The curriculum encompasses advanced deployment techniques, GitOps-driven automation, and observability strategies to guarantee system reliability and optimal performance.
Significant emphasis is placed on addressing real-world operational challenges, including incident response protocols, failure simulation exercises, and root cause analysis. The program concludes by integrating AI-powered tools to facilitate troubleshooting and expedite operational decision-making processes.
Upon completion, participants will possess a robust understanding of how to construct, deploy, monitor, and sustain resilient distributed systems within a Kubernetes ecosystem.
This instructor-led, live training in Transylvania (online or onsite) is designed for engineers who wish to use Docker to deploy and manage software as containers rather than as traditional standalone applications.
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.
This instructor-led, live training in Transylvania (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 Transylvania, participants will acquire the essential skills needed to build microservices using Spring Cloud and Docker. Knowledge is tested via exercises and the step-by-step construction of sample microservices.
By the end of the 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.
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 Transylvania (online or onsite) targets 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.
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Testimonials (4)
Training being interactive. He engaged us a lot by asking questions and imaginary use cases. He shifted away from his agenda to explain more of the things we are demanded.
Berk Ozdilek - Deutsche Bank
Course - Kubernetes Advanced
About the microservices and how to maintenance kubernetes
Yufri Isnaini Rochmat Maulana - Bank Indonesia
Course - Advanced Platform Engineering: Scaling with Microservices and Kubernetes
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