![]() Using popular container runtime environments (e.g., Docker), containers can be an efficient way for individual users to deploy and manage software applications. This post characterizes a container as a “self-contained environment with all the programs, configuration, initial data, and other supporting pieces to run applications.” The nice thing for data scientists is that this environment can be treated as a stand-alone unit, to turn on and run at any time – sort of a “portable machine.” It provides a complete virtual system configured to run your targeted application. With the new containerized cloud-native deployment option for SAS Analytics Pro, this raises the question of why data scientists should care about cloud and containers? This question was addressed in a SAS Users blog post by SAS R&D director Brent Laster. Why data scientists should care about cloud and containers? ![]() ![]()
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