Containers and Virtual Machines (VMs) Training in Évora

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.

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.

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.

This instructor-led, live training in Évora (online or onsite) is aimed at advanced-level Kubernetes administrators and DevOps engineers who wish to enhance their monitoring skills for Kubernetes clusters using Prometheus and Grafana.

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

• Set up Prometheus and Grafana for Kubernetes monitoring.
• Monitor key metrics for pods, nodes, and services.
• Create dynamic dashboards to visualize cluster health and performance.
• Implement alerting strategies for proactive issue resolution.
• Apply best practices for scaling monitoring solutions in Kubernetes environments.

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 Évora (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.

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.

This instructor-led, live training in Évora (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 Évora (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 Évora (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training goes on to more advanced topics, walking participants through the process of securing, scaling and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage a clustered web application.
• Secure, scale and monitor a Kubernetes cluster.

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

The evolution of microservices and containers in recent years has significantly changed how we design, develop, deploy and run software. Modern applications must be optimized for scalability, elasticity, failure, and change. Driven by these new demands, modern architectures require a different set of patterns and practices. In this training, we examine ways to identify, understand and adjust to these new requirements.

Audience
This training is intended for people who are somewhat familiar with container technology and with Kubernetes concepts but are perhaps lacking the real world experience. It is based on use cases, and lessons learnt from real life projects with the intention of making people inspired to create and manage even better cloud native applications.

• Developers
• Operations
• DevOps
• QA Engineers
• IT Project Managers

Format of the Course

• Interactive lecture and discussion
• Lots of exercises and practice
• Handson 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 Évora (online or onsite) is aimed at system administrators and developers who wish to use Prometheus to monitor Kubernetes clusters.

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

• Install and configure Prometheus.
• Monitor dynamic cloud environments.
• Gain better insight into their Kubernetes clusters.
• Set up alerts that are precise and insightful.

This instructor-led, live training in Évora (online or onsite) is aimed at engineers who wish to optimize networking for Kubernetes clusters.

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

• Install and configure Calico.
• Understand how Calico differs from traditional overlay networks.
• Understand how Calico combines internet routing protocols with consensus-based data stores.
• Use Calico to create a container networking solution for Kubernetes clusters.
• Use Calico to provide network policy for Kubernetes.

This instructor-led, live training in Évora (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 Évora (online or onsite) is aimed at 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:

• Setup 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.

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

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 Évora (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.

This instructor-led, live training Évora (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.

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 Évora (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 Évora (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 Évora (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 (online or onsite) is aimed at DevOps engineers who wish to use Selenium to execute Selenium tests inside of Docker containers.

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

• Create test automation infrastructure for on-demand testing.
• Develop a test automation framework using Java.
• Build a CI/CD pipeline from scratch with Jenkins and Docker.

This instructor-led, live training in Évora (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