<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>deployment on DataScience.LA</title><link>https://datasciencela.github.io/tag/deployment/</link><description>Recent content in deployment on DataScience.LA</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>DataScience.LA, 2014–2021 · Read-only archive: comments are closed.</copyright><lastBuildDate>Fri, 26 Sep 2014 11:25:44 -0700</lastBuildDate><atom:link href="https://datasciencela.github.io/tag/deployment/index.xml" rel="self" type="application/rss+xml"/><item><title>Packrat presentation at useR! 2014</title><link>https://datasciencela.github.io/packrat-presentation-at-user-2014/</link><pubDate>Fri, 26 Sep 2014 11:25:44 -0700</pubDate><guid>https://datasciencela.github.io/packrat-presentation-at-user-2014/</guid><description>&lt;p&gt;There comes a time in a software toolchain’s lifecycle where the focus shifts from developer productivity and preference to the ability to deploy solutions in production which coexist gracefully in the enterprise. &lt;a href="http://en.wikipedia.org/wiki/Configuration_management"&gt;Configuration management&lt;/a&gt; and dependency management are two of the first points of friction in this transition, as the free-wheeling methods preferred by developers are at odds with the structured methods and isolation desired by administrators, who serve as gatekeepers to enterprise deployment. R is currently at this very point in the transition, in the midst of transformation from a language and environment used primarily in academic research to its growing place in the enterprise. At &lt;a href="http://user2014.stat.ucla.edu/"&gt;useR! 2014&lt;/a&gt; there were a &lt;a href="http://user2014.stat.ucla.edu/abstracts/talks/223_Smith.pdf"&gt;series&lt;/a&gt; &lt;a href="http://user2014.stat.ucla.edu/abstracts/talks/901_Allaire.pdf"&gt;of&lt;/a&gt; &lt;a href="http://user2014.stat.ucla.edu/abstracts/talks/61_Elprin.pdf"&gt;presentations&lt;/a&gt; on how dependency management can be addressed within the R ecosystem, ranging from “provider” side options (e.g. freezing CRAN and private repositories) to the client side options, where a project maintains its own dependencies as part of its codebase.&lt;/p&gt;</description></item></channel></rss>