yegor maksymchuk - open shift as a cloud for data science
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This document discusses using OpenShift as a cloud platform for data science. It provides an overview of Kubernetes and OpenShift, comparing their key differences. It then discusses how Apache Spark can be used for data science in the cloud and integrated with OpenShift using Oshinko, which provides tools to deploy and manage Spark clusters on OpenShift. It demonstrates running a sample workflow of deploying a Spark cluster, Zeppelin notebook, and running an example notebook on the Spark cluster using Oshinko on OpenShift.
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This document discusses Docker Containers as a Service (CaaS). It begins by showing how Docker can be used to build a software layer on top of the internet hardware layer. It then discusses how Docker can be used with different cloud platforms and orchestration tools. It presents Docker CaaS as addressing the needs of both developers and IT operations by supporting the full application lifecycle across any infrastructure or operating system. Key characteristics of Docker CaaS include open APIs, pluggable architecture, and broad ecosystem support.
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- 1. OpenShift as a cloud for Data Science Yegor Maksymchuk, Soft Serve, Ukraine
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- 3. whoami Yegor Maksymchuk Software engineer, Soft Serve Ukraine Telegram: @QAStudy.online GitHub: YegorMaksymchuk LinkedIn:ymaksymchuk
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