AWS Orbit Workbench is a framework for building data analytics workbenchs on AWS. You can build a workbench that gives you access to the right tools for your use cases, either through the out-of-the-box in integrations or through the extensible architecture. You also have control over the underlying infrastructure, whether your work needs extra GPUs, extra memory or could save money by running on the newest Graviton2 processors. AWS Orbit Workbench is built on Kubernetes, making it easy to deploy, scale and rapidly iterate.
This introduction to AWS Orbit Workbench provides a detailed summary. After reading this section, you should have a good idea of what it offers and how it can fit into your business.
AWS Orbit Workbench has been built to let you build a secure workbench on AWS while giving you control over the services you use and the infrastructure you run on. Advantages of using AWS Orbit Workbench are:
This section describes the key concepts and terminology you need to understand to use AWS Orbit Workbench effectively.
AWS Orbit Workbench creates a team space for each team. A team space consists of:
Teams can launch Apps on containers in their Kubernetes cluster. An App could provide an integrated development environment (IDE) such as Jupyter or Visual Code. It could also provide a service, for example Voila can turn a Jupyter notebook into a stand alone web application, so you can easily share your work with the rest of your organisation.
Contributing Guidelines: ./CONTRIBUTING.md
This project is licensed under the Apache-2.0 License.
**: for detailed feature list by release, please see our release page in the wiki tab