Containers and Virtual Machines (VMs) Training in Cascais

Edge AI is a paradigm focused on running machine learning inference close to data sources to achieve low-latency, efficient, and scalable processing.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level practitioners who wish to deploy, orchestrate, and optimize AI workloads on Kubernetes-based edge environments.

By completing this course, participants will be able to:

• Set up lightweight Kubernetes distributions for edge deployments.
• Deploy AI inference workloads effectively across constrained edge nodes.
• Manage connectivity challenges and 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.

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.

Kubernetes is a scalable platform for deploying, serving, and managing machine learning models in production environments.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to operationalize ML models reliably on Kubernetes.

Upon completing this training, participants will gain the skills to:

• Containerize and prepare ML models for efficient deployment.
• Serve models using modern inference frameworks.
• Optimize workloads with autoscaling, GPU configuration, and resource tuning.
• Implement model rollout strategies such as A/B testing and canary deployments.

Format of the Course

• Blended lecture, architectural analysis, and guided discussion.
• Extensive practical exercises with real-world deployment scenarios.
• Hands-on implementation using a live Kubernetes environment.

Course Customization Options

• If you need this course tailored to your environment or toolchain, please contact us to discuss customization options.

This instructor-led, live training in Cascais (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.

GPU acceleration is essential for running high-performance deep learning workloads in a scalable and efficient manner.

This instructor-led, live training (online or onsite) is aimed at intermediate-level technical professionals who wish to configure, optimize, and run GPU-enabled AI workloads inside Docker containers.

At the conclusion 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.

Format of the Course

• 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 Cascais (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 Cascais (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes.

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

• Design and implement scalable microservices architectures.
• Deploy and manage applications on Kubernetes clusters.
• Utilize Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance in a Kubernetes environment.

DO180 is an introduction to containers, Kubernetes fundamentals, and Red Hat OpenShift platform concepts focused on hands-on skills.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to learn container workflows, Kubernetes primitives, and how to deploy and operate applications on OpenShift.

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

• Build and manage container images and registries with best practices for reproducibility and security.
• Deploy and manage Kubernetes objects such as pods, deployments, and services in OpenShift.
• Use OpenShift features including routes, buildconfigs, and the web console to streamline application delivery.
• Implement persistent storage, configuration management, and secrets handling for stateful workloads.
• Apply basic security, RBAC, and monitoring practices to maintain healthy clusters and applications.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs in a live OpenShift environment every day.
• Scenario-driven exercises and troubleshooting workshops.

Course Customization Options

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

Docker is a containerization platform used to build reproducible, portable, and scalable environments for ML systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level technical professionals who wish to containerize and operationalize complete ML pipelines using Docker.

Upon completion of 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 supporting tools.
• Implement versioning, reproducibility, and CI/CD for ML components.
• Deploy, monitor, and scale ML services in containerized environments.

Format of the Course

• Interactive lectures supported by practical demonstrations.
• Hands-on exercises focused on building real 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 is a containerization platform that enables consistent, portable, and reproducible environments for AI and machine learning workloads.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to package ML codebases, dependencies, and models using Docker for reliable development-to-production workflows.

After completing this course, participants will be able to:

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

Format of the Course

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

Course Customization Options

• To customize this training for your organizational environment, please contact us to arrange.

This instructor-led, live training in Cascais (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 Cascais (online or onsite) is aimed at beginner to intermediate-level developers, system administrators, and DevOps engineers who wish to understand Kubernetes and cloud-native principles.

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

• Set up a development environment that includes Kubernetes.
• Create a microservices application using Kubernetes.
• Deploy, manage, and scale applications in Kubernetes.
• Debug common issues in Kubernetes environments.

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 Cascais provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.

This instructor-led, live training in Cascais (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 Cascais, participants will learn how to set up 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.

This instructor-led, live training in (online or onsite) is aimed at engineers who wish to evaluate each of these services to make an informed decisions about which to deploy within their organization.

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

• Set up a development environment that includes all needed libraries, packages and frameworks needed to start developing.
• Set up, configure and deploy a series of demo containers using a number of different approaches.
• Understand the architectural and design differences among different Docker/Kubernetes solutions within AWS.
• Automate the deployment of Docker containers.
• Set up a continuous integration and deployment pipeline.
• Integrate Docker and Kubernetes into an existing continuous integration system.

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.

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 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 during the 2 days.

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 Cascais (online or onsite) is aimed at DevOps engineers who wish to set up, 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.

Kubernetes is an open-source platform for automating all development stages of containerized applications. Design patterns are iterable solutions to software development problems pertinent to software design. Kubernetes extensions are utilized for configuring and supporting Kubernetes clusters. With the help of Kubernetes design patterns and extensions, users of the platform can achieve CI/CD approaches while maintaining scalability and flexibility of software applications.

This instructor-led, live training (online or onsite) is aimed at developers and DevOps engineers who wish to leverage Kubernetes design patterns and extensions to create enterprise applications on Kubernetes clusters.

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

• Set up a Kubernetes cluster and configure the necessary DevOps tools.
• Understand the fundamentals of software design patterns and Kubernetes extensions.
• Utilize Kubernetes extensions and design patterns when interacting with Kubernetes API.
• Develop customized Kubernetes resources and apply dynamic controllers to a cluster.
• Manage and secure any Kubernetes environment with the help of Kubernetes plugins.
• Integrate DevOps networking models to existing and prospective Kubernetes projects.

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 Cascais (online or onsite) is aimed at DevOps engineers and developers who wish to deploy and manage OpenStack services on cloud infrastructures using Kubernetes.

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

• Deploy, configure, and manage MOS and its components.
• Access OpenStack APIs.
• Perform common OpenStack operations tasks (backup, restore, etc.).
• Upgrade OpenStack deployments.

This instructor-led, live training in Cascais (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 Cascais (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 Cascais (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