BigDataFR recommends: The O’Reilly Data Show Podcast – Erich Nachbar

<p><a title="@radar.oreilly.com - Ben Lorica - Erich Nachbar - Redefining power distribution using big data" href="http://radar.oreilly.com/2015/03/redefining-power-distribution-using-big-data.html" target="_blank">BigDataFR recommends: The O’Reilly Data Show Podcast – Erich Nachbar, founder and CTO of Virtual Power Systems

Erich Nachbar on testing & deploying open source, distributed computing components

Redefining power distribution using big data

‘When I first hear of a new open source project that might help me solve a problem, the first thing I do is ask around to see if any of my friends have tested it. Sometimes, however, the early descriptions sound so promising that I just jump right in and try it myself — and in a few cases, I transition immediately (this was certainly the case for Spark).

I recently had a conversation with Erich Nachbar, founder and CTO of Virtual Power Systems, and one of the earliest adopters of Spark. In the early days of Spark, Nachbar was CTO of Quantifind, a startup often cited by the creators of Spark as one of the first “production deployments.” On the latest episode of the O’Reilly Data Show Podcast, we talk about the ease with which Nachbar integrates new open source components into existing infrastructure, his contributions to Mesos, and his new “software-defined power distribution” startup.

Ecosystem of open source big data technologies

When evaluating a new software component, nothing beats testing it against workloads that mimic your own. Nachbar has had the luxury of working in organizations where introducing new components isn’t subject to multiple levels of decision-making. But, as he notes, everything starts with testing things for yourself:

“I have sort of my mini test suite…If it’s a data store, I would just essentially hook it up to something that’s readily available, some feed like a Twitter fire hose, and then just let it be bombarded with data, and by now, it’s my simple benchmark to know what is acceptable and what isn’t for the machine…I think if more people, instead of reading papers and paying people to tell them how good or bad things are, would actually set aside a day and try it, I think they would learn a lot more about the system than just reading about it and theorizing about the system.’

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Ben Lorica, Chief Data Scientist & Director of Content Strategy for Data at O’Reilly Media, Inc
Source: radar.oreilly.com

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