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.

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.

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.

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.

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.

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 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.

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 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 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 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.

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

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

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.

Istio is an open-source service mesh that operates on Kubernetes to deliver secure, observable, and manageable connectivity between microservices. By utilising Istio’s Envoy-based sidecar proxies, teams can enforce policies, secure communications via mTLS, gain deep visibility into traffic patterns, and enhance reliability at scale.

This instructor-led, live training (available online or onsite) is designed for intermediate-level engineers looking to deploy, secure, and manage microservices applications using Istio on Kubernetes.

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

• Install and configure Istio on Kubernetes clusters.
• Understand and apply service mesh concepts, including traffic management, security, and observability.
• Deploy microservices applications within an Istio service mesh.
• Secure service-to-service communications using mutual TLS (mTLS) and Zero Trust principles.
• Monitor, trace, and troubleshoot microservices using Prometheus, Grafana, and Jaeger.
• Integrate Istio with Calico for advanced network policies and security.

Format of the Course

• Interactive lecture and discussion.
• Extensive 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.

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 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 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 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.

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