Containers and Virtual Machines (VMs) Training in Braga

Edge AI represents a paradigm dedicated to executing machine learning inference near data sources, thereby achieving low-latency, efficient, and scalable processing.

This instructor-led live training (available online or onsite) targets intermediate to advanced practitioners seeking to deploy, orchestrate, and optimize AI workloads within Kubernetes-based edge environments.

Upon completing this course, participants will be able to:

• Configure lightweight Kubernetes distributions tailored for edge deployments.
• Effectively deploy AI inference workloads across resource-constrained edge nodes.
• Address connectivity challenges and implement synchronization patterns.
• Optimize performance, storage, and networking for real-world edge scenarios.

Course Format

• Guided presentations reinforced by real-world examples.
• Scenario-based labs and practical edge deployment exercises.
• Hands-on experience with Kubernetes edge frameworks.

Customization Options

• To request training customized to your specific edge platform requirements, please contact us to arrange.

Kubernetes serves as a container orchestration platform extensively utilized for managing distributed applications at scale.

This instructor-led, live training (available online or onsite) targets advanced practitioners aiming to leverage AI and machine learning techniques to enhance Kubernetes resource usage, scheduling choices, and autoscaling strategies.

Upon completing this program, participants will be able to:

• Apply AI/ML models to refine workload scheduling decisions 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.

Format of the Course

• Instructor-guided technical presentations and in-depth discussions.
• Hands-on lab work utilizing real Kubernetes clusters.
• Practical exercises applying AI models to actual operational scenarios.

Course Customization Options

• To tailor this course to your specific platform setup or operational needs, please contact us for customization.

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 structured methodology for automating model packaging, testing, containerisation, and deployment through continuous integration and continuous delivery pipelines.

This instructor-led, live training (available online or onsite) is designed for intermediate-level professionals seeking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completing the training, participants will be able to:

• Establish automated pipelines for constructing and testing AI model containers.
• Implement version control and reproducibility measures throughout the model lifecycle.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically tailored to machine learning operations.

Course Format

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations within a controlled environment.

Course Customisation Options

• If your organisation requires tailored pipeline workflows or platform integrations, please contact us to customise this course.

Hybrid AI deployment involves executing AI inference across cloud, on-premise, and edge environments using unified container-based workflows.

This instructor-led, live training (available online or onsite) is designed for advanced professionals aiming to design and deploy distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will be able to:

• Construct secure and scalable containerized AI services for multi-location environments.
• 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 within a controlled live-lab environment.

Course Customization Options

• To tailor this course to your organization’s specific infrastructure or use cases, please contact us to arrange customization.

Kubernetes is an open-source platform designed for the automated deployment, scaling, and management of containerized applications.

This instructor-led live training (available online or onsite) targets beginner to intermediate IT professionals eager to grasp the core concepts and components of Kubernetes and apply them to manage containerized applications at scale.

Upon completion of this training, participants will be capable of:

• Understanding Kubernetes architecture and its components.
• Deploying and managing containers within a Kubernetes cluster.
• Configuring networking, storage, and scaling for workloads.
• Troubleshooting common issues and adhering to best practices for cluster operations.

Course Format

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

Course Customization Options

• To arrange customized training for this course, please contact us directly.

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 Braga (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 Braga (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.

Docker serves as a containerization platform designed to build reproducible, portable, and scalable environments for machine learning systems.

This instructor-led, live training, available online or onsite, targets intermediate to advanced technical professionals seeking to containerize and operationalize complete ML pipelines using Docker.

Upon completing 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 complementary tools.
• Implement versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerized environments.

Course Format

• Interactive lectures supported by practical demonstrations.
• Hands-on exercises focused on constructing real-world ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Course Customization Options

• For customized training tailored to specific ML infrastructure requirements, please contact us to discuss available options.

Docker serves as a containerization platform that facilitates consistent, portable, and reproducible environments for artificial intelligence and machine learning workloads.

This instructor-led training session (available online or onsite) targets intermediate professionals seeking to package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development to production.

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

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

Course Format

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

Customization Options

• To tailor this training to your organizational needs, please contact us to arrange.

This instructor-led, live training in Braga (online or onsite) is tailored for beginner-level developers who wish to understand the fundamentals of Kubefirst and how it streamlines, secures, and accelerates Kubernetes and Swarm cluster management at an 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 the Kubefirst API and libraries.
• Profile and debug Kubefirst programs.

This instructor-led, live training in Braga (online or onsite) is designed for intermediate-level developers and DevOps engineers who want to incorporate Minikube into their development workflow.

Upon completion 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 by leveraging Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led, live training in Braga (online or onsite) is designed for intermediate developers and DevOps engineers aiming to build, deploy, and manage microservices using Spring Cloud and Docker.

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

• Create microservices leveraging Spring Boot and Spring Cloud.
• Containerize applications using Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices within production environments.
• Deploy and orchestrate microservices via Kubernetes.

This instructor-led, live training in Braga (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.

This instructor-led live training in Braga (online or onsite) is tailored for developers and others interested in learning how to use Skupper to create secure communication within a hybrid multi-cloud environment.

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

• Learn and understand the fundamentals of Skupper.
• Setup and configure Skupper in multiple namespaces.
• Configure Skupper security and allow multi-cloud communication for applications.

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

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 Braga (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 Braga (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.

This intensive 7-day programme offers a thorough, practical exploration of designing, deploying, and managing cloud-native applications through contemporary DevOps methodologies.

Attendees will investigate techniques for architecting scalable microservices infrastructures, refining container environments, and handling production workloads via Kubernetes. The curriculum encompasses sophisticated deployment tactics, GitOps-driven automation, and observability strategies to guarantee system dependability and efficiency.

Significant emphasis is placed on addressing practical operational difficulties, such as incident handling, failure simulation, and root cause analysis. The programme finishes by integrating AI-powered tools to facilitate troubleshooting and expedite operational decision-making.

Upon completion, participants will possess a robust comprehension of how to construct, deploy, monitor, and sustain resilient distributed systems within a Kubernetes ecosystem.

This instructor-led, live training in Braga (online or on-site) is aimed at engineers who wish to use Docker to deploy and manage software as containers instead of as traditional stand-alone software.

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

• Install and configure Docker.
• Understand and implement software containerization.
• Managing Docker based applications.
• Network different Docker applications and systems.
• Understand and edit Docker registries.

This instructor-led, live training in Braga (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 Braga (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.

In this instructor-led live training held in Braga, participants will learn the basics of building microservices using Spring Cloud and Docker. Participants' knowledge will be tested through exercises and the incremental development of sample microservices.

By the end of this 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.

This instructor-led, live training in Braga (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.

OpenShift Container Platform v4 is an enterprise-grade Kubernetes platform created by Red Hat, designed to automate the deployment, scaling, and management of containerised applications.

This instructor-led, live training (available online or onsite) targets system administrators and DevOps engineers who want to deploy, manage, and operate OpenShift clusters in production environments.

The course offers a practical approach to installing and managing OpenShift 4 clusters, working with Operators, securing workloads, and running applications at scale.

This instructor-led, live training in Braga (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.