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

This instructor-led, live training in Brazil (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish to master scaling applications 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.

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

By the conclusion of this course, participants will be equipped to protect Kubernetes environments and container-based applications throughout the various phases of an application's lifecycle: build, deployment, and runtime.

This intensive 7-day program offers a comprehensive, hands-on exploration into the design, deployment, and operation of cloud-native applications using contemporary DevOps methodologies.

Participants will delve into creating scalable microservices architectures, optimizing containerized environments, and managing production workloads with Kubernetes. The curriculum encompasses advanced deployment strategies, GitOps-driven automation, and observability techniques to guarantee system reliability and peak performance.

Emphasis is placed on addressing real-world operational hurdles, including incident response protocols, failure simulation exercises, and root cause analysis. The program culminates in leveraging AI-powered tools to enhance troubleshooting capabilities and expedite operational decision-making processes.

Upon completion of the training, participants will possess a solid grasp of how to construct, deploy, monitor, and sustain resilient distributed systems within a Kubernetes-based infrastructure.

Master the fundamentals of containers, Kubernetes, and OpenShift through practical, hands-on training designed specifically for developers, DevOps engineers, and IT professionals. Participants will learn how to build containerized applications, deploy workloads, manage Kubernetes resources, and leverage OpenShift to streamline modern application delivery across 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 gain the skills needed to operate modern container platforms and troubleshoot applications across development and production environments.

This instructor-led live training, located in Brazil (onsite or remote), will teach participants how to create and manage Docker containers and deploy a sample application within one. Participants will also learn to automate, scale, and manage their containerized applications inside a Kubernetes cluster. Furthermore, the training covers 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 Brazil (online or onsite) is designed for engineers who want to use Helm to streamline the installation and management of Kubernetes applications.

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

• Install and configure Helm.
• Create reproducible builds of Kubernetes applications.
• Share applications as Helm charts.
• Run third-party applications saved as Helm charts.
• Manage releases of Helm packages.

This live, instructor-led training in Brazil, offered online or onsite, is designed for developers and data scientists looking to build, deploy, and manage machine learning workflows on Kubernetes.

By the conclusion of this program, participants will possess the ability to:

• Install and configure Kubeflow in both on-premise and cloud settings.
• Construct, deploy, and oversee ML workflows utilizing Docker containers and Kubernetes.
• Execute full machine learning pipelines on diverse architectures and cloud environments.
• Use Kubeflow to spawn and control Jupyter notebooks.
• Create ML training, hyperparameter tuning, and serving workloads across various platforms.

This instructor-led, live training in Brazil (online or on-site) is targeted at beginner to intermediate software developers and DevOps professionals who want 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.
• Grasp the fundamental 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 Brazil (online or onsite) is designed for intermediate-level developers and DevOps engineers aiming 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.