Kubeflow is a framework for running Machine Learning workloads on Kubernetes. TensorFlow is one of the most popular machine learning libraries. Kubernetes is an orchestration platform for managing containerized applications. OpenShift is an cloud application development platform that uses Docker containers, orchestrated and managed by Kubernetes, on a foundation of Red Hat Enterprise Linux.
This instructor-led, live training (online or onsite) is aimed at engineers who wish to deploy Machine Learning workloads to an OpenShift on-premise or hybrid cloud.
- By the end of this training, participants will be able to: - Install and configure Kubernetes and Kubeflow on an OpenShift cluster. - Use OpenShift to simplify the work of initializing a Kubernetes cluster. - Create and deploy a Kubernetes pipeline for automating and managing ML models in production. - Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel. - Call public cloud services (e.g., AWS services) from within OpenShift to extend an ML application.
Format of the Course
- Interactive lecture and discussion. - Lots of 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.
OKD is an application development platform for deploying containerized applications using Docker and Kubernetes. OKD is the upstream code base upon which Red Hat OpenShift Online and Red Hat OpenShift Container Platform are built.
In this instructor-led, live training (onsite or remote), participants will learn how to how to install, configure, and manage OKD on-premise or in the cloud.
By the end of this training, participants will be able to:
- Create, configure, manage, and troubleshoot an OKD cluster. - Secure OKD. - Deploy containerized applications on OKD. - Monitor the performance of an application running in OKD. - Manage data storage. - Quickly deploy applications on-premise or on a public cloud such as AWS.
Format of the Course
- Interactive lecture and discussion. - Lots of 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.
OKD is an application development platform for deploying containerized applications using Docker and Kubernetes. OKD is the the upstream code base upon which Red Hat OpenShift Online and Red Hat OpenShift Container Platform are built.
In this instructor-led, live training (onsite or remote), participants will learn learn to create, update, and maintain containerized applications using OKD.
By the end of this training, participants will be able to:
- Deploy a containerized web application to an OKD cluster on-premise or in the cloud. - Automate part of the software delivery pipeline. - Apply the principles of the DevOps philosophy to ensure continuous delivery of an application.
Format of the Course
- Interactive lecture and discussion. - Lots of 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.
Jenkins is an open sourced automation server for continuous integration and continuous delivery (CI/CD). OpenShift is a containerization platform for managing infrastructures on the cloud or on-premise.
This instructor-led, live training (online or onsite) is aimed at DevOps engineers who wish to use OpenShift and Jenkins to build, deploy, and manage container-based applications.
By the end of this training, participants will be able to:
- Build Jenkins pipelines in OpenShift. - Automate the lifecycle management for containerized applications and cluster infrastructures. - Orchestrate the deployment of CI/CD pipelines.
Format of the Course
- Interactive lecture and discussion. - Lots of 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.