Containers and Virtual Machines (VMs) Training in Gaia

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.

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 Gaia (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 Gaia (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.

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

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 Gaia (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 Gaia (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.

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.

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

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

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

Discover how to build, deploy, and administer containerized environments utilising Docker, Kubernetes, and OpenShift. This five-day, hands-on training encompasses container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants will acquire the skills necessary to operate modern container platforms and troubleshoot applications across both development and production environments.

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.

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 course 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 Gaia (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 Gaia (online or onsite) is designed for DevOps engineers who wish to employ Kubernetes and GitLab to automate the DevOps lifecycle.

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

• Automate application builds, tests, and deployments.
• Create an automated build infrastructure.
• Deploy an application to a containerized cloud environment.

This instructor-led, live training in Gaia (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 Gaia (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 instructor-led live training in Gaia (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 comprehensive, hands-on exploration into the design, deployment, and operation of cloud-native applications through modern DevOps methodologies.

Participants will learn to architect scalable microservice systems, optimise containerised environments, and manage production workloads using Kubernetes. The curriculum encompasses advanced deployment techniques, GitOps-driven automation, and observability frameworks to guarantee system reliability and high performance.

Significant emphasis is placed on addressing real-world operational hurdles, such as incident management, failure simulation, and root cause analysis. The programme concludes with the integration of AI-powered tools designed to aid in troubleshooting and expedite operational decision-making processes.

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

This instructor-led, live training in Gaia (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.

OpenShift is one of the leading Kubernetes-based platforms for deploying and managing containerized applications in cloud, hybrid and on-premises environments.

This hands-on training teaches participants how to install, administer and troubleshoot OpenShift clusters while applying security, networking and storage best practices. Through practical exercises, participants gain the skills needed to confidently manage production-ready OpenShift environments.

Learn how to develop, deploy, and manage containerized applications with OpenShift, one of the leading Kubernetes-based platforms for cloud-native development. This practical training covers application deployment, containers, networking, CI/CD, and DevOps workflows, providing participants with the skills to build and maintain modern applications in production environments.

This instructor-led, live training in Gaia (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.