Containers and Virtual Machines (VMs) Training in Faro

MLOps on Kubernetes provides a framework to automate the training, validation, packaging, and deployment of machine learning models through containerized pipelines and GitOps workflows.

This instructor-led live training, available online or onsite, targets intermediate-level practitioners looking to build automated and scalable MLOps pipelines on Kubernetes.

Upon completion, 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 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.

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 seeking to develop secure, portable AI inference microservices that can be consistently deployed across local machines, servers, or cloud virtual machines.

Upon completing this workshop, participants will be able to:

• Construct lightweight inference containers for both local and cloud deployment.
• Secure containerized AI services using industry best practices.
• 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.

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

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

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

• Build and operate 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 Faro (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 Faro (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 Faro (online or onsite) is designed for advanced-level platform engineers and DevOps professionals who wish 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.
• Utilize Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance in a Kubernetes environment.

This instructor-led, live training in Faro (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.

This instructor-led, live training in Faro (online or onsite) is designed for beginner to intermediate software developers and DevOps professionals seeking 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.

Training objectives: Acquire theoretical and practical skills in Docker and Kubernetes.

This hands-on course aims to equip participants with the practical tools and knowledge needed for Docker and Kubernetes, enabling them to manage these technologies effectively.

In this instructor-led, live training in Faro, participants will learn how to manage Red Hat OpenShift Container Platform.

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

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerized applications on-premise, in public cloud or on a hosted cloud.
• Secure OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

The Certified Kubernetes Application Developer (CKAD) programme was developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the organisation responsible for hosting Kubernetes.

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

Additionally, the training emphasises gaining practical experience in Kubernetes application development. Therefore, we recommend attending even if you do not plan to sit for the CKAD exam.

NobleProg has been delivering Docker and Kubernetes training since 2015. Having successfully completed over 360 training projects, we have established ourselves as one of the most recognised training providers globally in the field of containerisation. Since 2019, we have also assisted our customers in validating their performance in Kubernetes environments by preparing them to pass the CKA and CKAD exams.

Course Format

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

Course Customisation Options

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

This instructor-led, live training in Faro (online or onsite) is designed for 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 various cloud-hosted Kubernetes solutions and understand the advantages over a self-hosted approach.
• Compare different tools for testing, managing, and monitoring a Kubernetes cluster.

In this instructor-led live training held in Faro, participants will learn how to establish and manage a production-scale container environment using Kubernetes on Google Cloud.

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

• Configure and manage Kubernetes on Google Cloud.
• Deploy, manage and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Google Cloud.
• Migrate an existing Kubernetes environment from on-premise to Google 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 Faro (onsite or remote), participants will learn 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 Faro (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 Faro (online or onsite) targets developers and DevOps engineers who wish to adopt 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 begin developing with a serverless architecture.
• Understand the concepts and principles foundational to serverless environments.
• Operate toolchains necessary for serverless development and integrate them with Kubernetes components.
• Practice skills in the Python programming language and apply them to implement serverless systems.
• Secure enterprise applications deployed through a serverless framework on Kubernetes.
• Utilize modern cloud computing methods in optimizing DevOps task processing workflows.

This instructor-led live training in Faro (online or on-site) is designed for engineers who wish to enhance their Docker proficiency, enabling the large-scale deployment of applications while maintaining strict 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.

DC/OS (Distributed Cloud Operating System) is an open-source distributed operating system constructed on the Apache Mesos project. Apache Mesos was developed following the same principles as the Linux kernel, albeit at a distinct level of abstraction. The Mesos kernel operates on every machine, providing applications such as Hadoop, Spark, Kafka, and Elasticsearch with APIs for resource management and scheduling across full data centre and cloud environments. Apache Mesos abstracts CPU, memory, storage, and other compute resources away from physical or virtual machines, enabling the easy construction and effective operation of fault-tolerant and elastic distributed systems.

DC/OS unites Mesos and over 30 applications into a single coherent system, much like how a Linux distribution packages the Linux kernel with applications to create a functional operating system.

This course offers participants a comprehensive overview of Apache Mesos and DC/OS, demonstrating through practical, hands-on exercises how to deploy and manage a complete Data Centre Operating System.

Audience

• System administrators
• DevOps engineers

Course Format

• A blend of lectures, discussions, and extensive hands-on practice

Course Format

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

Options for Course Customization

• To arrange a bespoke training session for this course, please get in touch with us.

This instructor-led, live training in Faro (online or onsite) is designed for DevOps engineers and developers who want to leverage Fedora CoreOS to lower the maintenance and upgrade costs associated with running containerised applications on Kubernetes.

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

• Install and configure Fedora CoreOS.
• Set up a 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 in Faro (online or onsite) is tailored for DevOps engineers who wish to establish, deploy, and manage a Git-based software deployment workflow for their Kubernetes applications.

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

• Install and configure Spinnaker and Terraform.
• Understand the benefits of GitOps over traditional CI/CD and Infrastructure-as-Code (IAC).
• Move away from maintaining scripts. Configure and execute well-defined deployment process.
• Apply best practices for cloud-native deployment, management, and monitoring.
• Recover deployments from partial failures without manual intervention.
• Create a GitOps strategy for application development.

This instructor-led, live training Faro (online or onsite) is designed for DevOps engineers and developers who wish to leverage 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.

Kubernetes is an open-source platform designed to automate the entire lifecycle of containerized application development. Design patterns provide proven, repeatable solutions to common challenges in software design. Meanwhile, Kubernetes extensions are employed to configure and support Kubernetes clusters effectively. By leveraging these design patterns and extensions, platform users can implement CI/CD practices while ensuring their software applications remain scalable and flexible.

This instructor-led, live training (available online or onsite) is targeted at developers and DevOps engineers who aim to utilize Kubernetes design patterns and extensions to build enterprise-grade applications on Kubernetes clusters.

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

• Establish a Kubernetes cluster and configure essential DevOps tools.
• Grasp the core principles of software design patterns and Kubernetes extensions.
• Apply Kubernetes extensions and design patterns when engaging with the Kubernetes API.
• Develop bespoke Kubernetes resources and implement dynamic controllers within a cluster.
• Administer and secure Kubernetes environments using Kubernetes plugins.
• Integrate DevOps networking models into both current and future Kubernetes projects.

Course Format

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

Customization Options for the Course

• To request tailored training for this course, please contact us to make arrangements.

This instructor-led, live training in Faro (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 Faro (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 hands-on course is designed for system administrators, developers, embedded specialists, and desktop users (including managers) seeking a foundational understanding of virtualization. Upon completion, administrators will possess the skills to establish private clouds for production environments, while developers will be equipped to test their code across multiple operating systems without requiring a secondary PC or non-x86 hardware.

We recognize that the breadth of topics covered in this course may not align with every customer's needs. When booking, please specify your objectives for using QEMU or KVM so we can tailor the schedule by reallocating time from less relevant subjects to those that are most critical for you.

This instructor-led, live training in Faro (online or onsite) targets developers and DevOps engineers who wish to leverage Tekton Pipelines to support complex software development workflows and build automated CI/CD pipelines.

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

• Install and configure Tekton Pipelines and other foundational Tekton components.
• Design and create the building blocks of pipelines for software development in Tekton.
• Automate existing pipelines and development processes using Tekton framework concepts and principles.
• Run and manage Tekton Pipelines for various workload types across multiple platforms.
• Implement CI/CD systems based on the Tekton framework to enhance future software development projects.

This instructor-led, live training in Faro (online or on-site) 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