Containers and Virtual Machines (VMs) Training in Setúbal

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.

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.

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.

This instructor-led, live training in Setúbal (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 visualise cluster health and performance.
• Implement alerting strategies for proactive issue resolution.
• Apply best practices for scaling monitoring solutions in Kubernetes environments.

This instructor-led live training in Setúbal (online or onsite) is tailored for DevOps engineers and developers who intend to utilize Kubernetes for building, deploying, and managing containers and cluster components in a secure and scalable setting.

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

• Comprehend the architecture, core concepts, and components of the Kubernetes ecosystem.
• Establish, install, and configure a Kubernetes cluster for container orchestration.
• Learn how to perform Kubernetes operations using command-line tools.
• Gain hands-on experience covering both basic and advanced Kubernetes operations and administration.

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.

In this instructor-led, live training in Setúbal (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking participants through the process of securing, networking and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy containerized databases and servers.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage different environments under the same cluster.
• Secure, scale and monitor a Kubernetes cluster.

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

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

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

This instructor-led live training (available online or onsite) is designed for engineers looking to automate, secure, and monitor containerized applications within a large-scale Kubernetes cluster.

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

• Utilize Kubernetes to deploy and manage diverse environments within a single cluster
• Secure, scale, and monitor a Kubernetes cluster effectively

Course Format

• Interactive lectures and discussions
• Numerous exercises and practical sessions
• Hands-on implementation in a live lab environment

Course Customization Options

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

This instructor-led, live course provides participants with an overview of Rancher and demonstrates, through hands-on practice, how to deploy and manage a Kubernetes cluster with Rancher.

The rapid evolution of microservices and container technologies in recent years has fundamentally transformed how we design, develop, deploy, and operate software. Modern applications must be engineered for scalability, elasticity, resilience, and adaptability to change. To meet these new demands, contemporary architectures require a distinct set of patterns and best practices. This training explores methods to identify, comprehend, and adapt to these evolving requirements.

Target Audience
This course is designed for individuals who possess a foundational understanding of container technology and Kubernetes concepts but may lack practical, real-world experience. Drawing on use cases and lessons learned from actual projects, the goal is to inspire participants to create and manage superior cloud-native applications.

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

Course Format

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

Course Customization Options

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

This instructor-led, live training in Setúbal (online or onsite) is designed for engineers who want to utilize Helm to streamline the installation and management of Kubernetes applications.

Upon completing this training, participants will be able to:

• Install and configure Helm.
• Create reproducible builds for Kubernetes applications.
• Distribute applications as Helm charts.
• Operate third-party applications packaged as Helm charts.
• Manage Helm package releases.

This instructor-led live training in Setúbal (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 Setúbal (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 Setúbal (online or onsite) is designed for engineers who want to secure a Kubernetes cluster beyond the default security settings.

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

• Identify vulnerabilities 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.
• Develop a comprehensive security policy and set of best practices.

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 Setúbal (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.

In this instructor-led live training held in Setúbal, 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 Setúbal (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.

In this instructor-led, live training in Setúbal (online or on-site), participants will learn how to create, update, and maintain applications using OpenShift Container Platform.

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

• Understand OCI (Open Containers Initiative) and its implications for using container engines like Docker in OpenShift.
• Grasp the relationships between different versions of OpenShift (OKP, OpenShift Container Platform, Red Hat OpenShift, etc.).
• Automate the software delivery pipeline.
• Apply DevOps principles to deliver software continuously.

This instructor-led, live training in Setúbal (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.