Containers and Virtual Machines (VMs) Training in Gaia

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

This instructor-led, live training (online or onsite) is aimed at advanced-level practitioners who wish to apply AI and machine learning techniques to optimize Kubernetes resource usage, scheduling decisions, and autoscaling strategies.

At the completion of this program, participants will be able to:

• Apply AI/ML models to improve workload scheduling decisions in Kubernetes.
• Use predictive analytics to optimize CPU, GPU, and memory allocation.
• Implement intelligent autoscaling using reinforcement learning and metric forecasting.
• Reduce infrastructure cost 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 platform setup or operational requirements, please contact us for customization.

MLOps on Kubernetes is a framework for automating the training, validation, packaging, and deployment of machine learning models using containerized pipelines and GitOps workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level practitioners who wish to build automated, scalable MLOps pipelines on Kubernetes.

After completing this training, participants will be equipped to:

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

Format of the Course

• Instructor-guided presentations and technical deep dives.
• Hands-on exercises that build real-world CI/CD workflows.
• Live-lab practice deploying ML workloads to Kubernetes.

Course Customization Options

• Organizations may request tailored content aligned with their internal MLOps tools and infrastructure.

CI/CD for AI is a structured approach to automating model packaging, testing, containerization, and deployment using continuous integration and continuous delivery pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

As the training concludes, participants will be able to:

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

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

Hybrid AI deployment is the practice of running AI inference across cloud, on-premise, and edge environments using unified container-based workflows.

This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to design and deploy distributed AI inference systems across heterogeneous environments.

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

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

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Gaia (online or onsite) is aimed at DevOps engineers and developers who wish to use 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 is a containerization platform used to build portable, isolated, and secure deployment environments for AI inference services.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to build secure, portable AI inference microservices that can be deployed consistently across local machines, servers, or cloud VMs.

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

• Build lightweight inference containers for local and cloud deployment.
• Secure containerized AI services using best-practice techniques.
• Implement portable microservice workflows for consistent environments.
• Deploy AI inference endpoints across diverse infrastructures.

Format of the Course

• Guided lectures paired 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 infrastructure or AI tooling stack, please contact us to arrange.

This instructor-led, live training in Gaia (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 Gaia (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 Gaia (online or onsite) is aimed at beginner-level developers who wish to learn the basics of Kubefirst and how it simplifies, secures, and accelerates Kubernetes and Swarm cluster management at enterprise scale.

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

• Set up a Kubefirst development environment.
• Write and run a basic Kubefirst program.
• Annotate code with Kubefirst directives and clauses.
• Use Kubefirst API and libraries.
• Profile and debug Kubefirst programs.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to use Minikube as a 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 Gaia (online or onsite) is aimed at intermediate-level system administrators who wish to effectively deploy, manage, and troubleshoot Hyper-V environments.

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

• Understand virtualization concepts and configure Hyper-V.
• Create and manage virtual machines, VM storage, and networking.
• Utilize advanced Hyper-V features and secure Hyper-V environments.
• Monitor and optimize Hyper-V performance.

In this instructor-led, live training in Gaia (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.

In this instructor-led, live training in Gaia, participants will learn how to use OpenShift Container Platform to deploy containerized applications.

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

• Create and configure an OpenShift setup.
• Quickly deploy applications on-premise, in public cloud or on a hosted cloud.

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 in Gaia (online or onsite) is aimed at engineers who wish to evaluate, select and deploy the most appropriate Kubernetes solution for their specific situation.

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

• Install and configure a Kubernetes cluster on premise and in the cloud.
• Evaluate different cloud-hosted Kubernetes solutions and understand the advantages over an self-hosted approach.
• Compare different tools for testing, managing, and monitoring a Kubernetes cluster.

In this instructor-led, live training in Gaia (onsite or remote), participants will learn how to how to install, configure, and manage OKD on-premise or in the cloud.

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

• Create, configure, manage, and troubleshoot an OKD cluster.
• Secure OKD.
• Deploy containerized applications on OKD.
• Monitor the performance of an application running in OKD.
• Manage data storage.
• Quickly deploy applications on-premise or on a public cloud such as AWS.

This instructor-led, live training in Gaia (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 Gaia (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.
• Secure their Docker applications.

Apache Karaf is an OSGi based runtime for deploying containerized applications.

In this instructor-led, live training (onsite or remote), participants will learn how to set up an OSGi based project as they step through the deployment of a modular Java application using Apache Karaf.

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

• Install and configure Apache Karaf
• Understand the essential features of the OSGi runtime environment
• Develop a containerized application using the Apache Karaf run time environment

Audience

• Architects
• Developers

Format of the Course

• Part lecture, part discussion, exercises and heavy hands-on practice.

Note

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

DC/OS (Distributed Cloud Operating System) is an open-source distributed operating system built upon the Apache Mesos project. Apache Mesos was built using the same principles as the Linux kernel, only at a different level of abstraction. The Mesos kernel runs on every machine and provides applications such as Hadoop, Spark, Kafka and Elasticsearch with API’s for resource management and scheduling across entire datacenter and cloud environments. Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual), enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.

DC/OS brings together Mesos and more than 30 applications into one coherent system, similar to how a Linux distribution packages the Linux kernel with applications to create a working operating system.

This course provides participants with an overview of Apache Mesos and DC/OS and demonstrates through hands-on practice how to deploy and manage a complete Data Center Operating System.

Audience

• System administrators
• DevOps engineers

Format of the course

• Part lecture, part discussion, heavy hands-on practice

Docker is a platform for developers and sysadmins to maintain distributed applications. It consists of a runtime to run containers and a service for sharing containers.

With docker the same app can run unchanged on laptops, dedicated servers and virtual servers.

This course, during the two first days, teaches the basic usage of Docker, useful both for developers and system administrators. The course includes a lot of hands on exercises and the participants will practice in their own Docker environment and build their own Docker images.

On the last day participants will learn about more advanced tools that supports Docker. It will be Docker Machine, Docker Compose and Docker Swarm.

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.

This instructor-led, live training in Gaia (online or onsite) is aimed at DevOps engineers and developers who wish to use Fedora CoreOS to reduce the maintenance and upgrade costs of running  containerized applications on Kubernetes.

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

• Install and configure Fedora CoreOS.
• Set up Kubernetes cluster on Fedora CoreOS.
• Run and manage Kubernetes deployments on Fedora CoreOS.
• Automatically update Fedora OS with the latest OS improvements, bug fixes, and security updates.

This instructor-led, live training Gaia (online or onsite) is aimed at DevOps engineers and developers who wish to use Java and Kubernetes (K8s) to create, build, test, debug and deploy high-performance and scalable applications.

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

• Set up the necessary development environment to build Java applications.
• Understand the features and architecture of Kubernetes.
• Learn about the key concepts and tools for DevOps.
• Get a refresher on Java programming fundamentals.
• Containerize Java microservices using Docker.
• Build, scale, and deploy Java applications on Kubernetes.

In this instructor-led, live training in Gaia (online or onsite), participants will learn how to install, configure, and manage OpenShift Container Platform v4.

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

• Undersand OCI (Open Containers Initiative) and its implications for using container enginees such as Docker in OpenShift.
• Understand the relationship between the different versions of OpenShift (OKP, OpenShift Container Platform, Red Hat OpenShift, etc.).
• Create, configure, manage, and troubleshoot an OpenShift cluster.
• Implement Openshift's self-manage capabilities to improve platform stability and consistency.
• Secure OpenShift Container Platform.
• Monitor and gather metrics.
• Manage storage.
• Upgrade an OpenShift Container Platform 3 cluster to OpenShift Container Platform 4.

This instructor-led, live training in Gaia (online or onsite) is aimed at DevOps engineers and developers who wish to use Podman to create, run, and manage containers and pods as a non-root user.

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

• Install and configure Podman in rootless mode.
• Build and run containers, container images, and pods.
• Manage container networking and lifecycle.
• Use Podman instead of Docker for creating and deploying containerized applications.

This instructor-led, live training in Gaia (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.

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

• Create Python programs to seek network vulnerabilities.
• Explore and use Kali web shells and shellcode in exploits.
• Apply various Kali tools for penetration testing.
• Exploit systems with Python.

This practical course contains topics addressed to system administrators, developers, embedded developers and ordinary desktop users (including managers) who would like to have an introduction to virtualization in general. After this course, administrators will be able to create private clouds for use in production, and developers will be able to test their code on multiple operating systems without needing a second PC or a non-x86 board.

We understand that the set of topics presented in this course covered a wide range of subjects that might not be applicable for all customers. When booking this course, please specify what you wish to achieve using QEMU or KVM, and we will customize it by reallocating time from less relevant topics to the ones that would be important for you.

This instructor-led, live training in Gaia (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.

Microsoft Azure Infrastructure and Deployment