Читать книгу Data Science For Dummies - Lillian Pierson - Страница 39

Kubernetes is an open-source software suite that manages, orchestrates, and coordinates the deployment, scaling, and management of containerized applications across clusters of worker nodes. One particularly attractive feature about Kubernetes is that you can run it on data that sits in on-premise clusters, in the cloud, or in a hybrid cloud environment.

Kubernetes’ chief focus is helping software developers build and scale apps quickly. Though it does provide a fault-tolerant, extensible environment for deploying and scaling predictive applications in the cloud, it also requires quite a bit of data engineering expertise to set them up correctly.

A system is fault tolerant if it is built to continue successful operations despite the failure of one or more of its subcomponents. This requires redundancy in computing nodes. A system is described as extensible if it is flexible enough to be extended or shrunk in size without disrupting its operations.

To overcome this obstacle, Kubernetes released its KubeFlow product, a machine learning toolkit that makes it simple for data scientists to directly deploy predictive models within Kubernetes containers, without the need for outside data engineering support.