Kubeflow Essentials: Build, Train & Serve with Kubernetes Training Course

This instructor-led, live training in the UAE (online or onsite) is designed for advanced platform engineers and DevOps professionals seeking to master application scaling via microservices and Kubernetes.

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

• Designing and implementing scalable microservices architectures.
• Deploying and managing applications on Kubernetes clusters.
• Leveraging Helm charts for streamlined service deployment.
• Monitoring and ensuring the operational health of microservices in production.
• Applying industry best practices for security and compliance within Kubernetes.

This instructor-led, live training in the UAE (available online or onsite) is designed for Kubernetes practitioners looking to prepare for the CKS exam.

By the end of this training, participants will be equipped to secure Kubernetes environments and container-based applications throughout the various stages of an application's lifecycle: build, deployment, and runtime.

This 7-day programme provides a comprehensive, hands-on journey into designing, deploying, and operating cloud-native applications using modern DevOps practices.

Participants will explore how to design scalable microservices architectures, optimise container environments, and manage production workloads using Kubernetes. The course covers advanced deployment strategies, GitOps-based automation, and observability practices to ensure system reliability and performance.

A strong focus is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme concludes with the use of AI-powered tools to support troubleshooting and accelerate operational decision-making.

By the end of the training, participants will have a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems in a Kubernetes-based environment.

Learn the fundamentals of containers, Kubernetes and OpenShift in a practical, hands-on training designed for developers, DevOps engineers and IT professionals. Participants will learn how to build containerized applications, deploy workloads, manage Kubernetes resources and use OpenShift to streamline modern application delivery in cloud and hybrid environments.

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

In this instructor-led live training at the UAE (onsite or remote), participants will learn how to create and manage Docker containers, followed by deploying a sample application within a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training progresses to advanced topics, guiding 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.

Training Objectives: Gain theoretical and practical skills in Docker and Kubernetes.

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

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

• Install and configure Helm.
• Build reproducible Kubernetes application configurations.
• Distribute applications as Helm charts.
• Execute third-party applications packaged as Helm charts.
• Manage Helm package releases.

This live, instructor-led training in the UAE (available online or on-site) is designed for developers and data scientists who aim to build, deploy, and manage machine learning workflows on Kubernetes.

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

• Install and configure Kubeflow in both on-premise and cloud settings.
• Create, deploy, and manage ML workflows based on Docker containers and Kubernetes.
• Run complete machine learning pipelines across diverse architectures and cloud environments.
• Use Kubeflow to spawn and manage Jupyter notebooks.
• Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This instructor-led, live training in the UAE (online or onsite) is designed for beginner to intermediate-level software developers and DevOps professionals seeking to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local machines.
• Gain a clear understanding of the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Establish persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for developing, testing, and debugging applications.

This instructor-led, live training in the UAE (online or onsite) targets intermediate-level developers and DevOps engineers seeking to use Minikube as part of their development workflow.

By the end 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 using Minikube's advanced features.
• Apply best practices for local Kubernetes development.