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Top 5 articles for the week of November 24, 2017
Top 5: Learning Python, analyzing Linux performance with bcc/BPF, and more
Take a look back at the week's top articles.
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This week we take a look at seven tools for analyzing performance in Linux, an introduction to machine learning with Apache Solr, how Linux Vendor Firmware Service makes updates easier, 10 things that Jen Krieger learned making LEGO blocks glow, and five approaches to learning Python.
Top 5 posts
Brendan Gregg, a senior performance architect at Netflix, explains how the Berkley Packet Filter Compiler Collection Tools can provide sysadmins and developers with a large number of new tools and dashboards for performance analysis and troubleshooting. These enhancements weren't developed in Berkeley, operate on much more than just packets, and do much more than just filtering. In the article, Brendan explains how all this works.
Michael A. Alcorn, a machine learning engineer at Red Hat, is always looking for ways to ways to use the latest and greatest machine learning technology. In this article, he provides a step-by-step guide to setting up and using Apache Solr. If you have zero Solr experience but are comfortable with machine learning and information retrieval concepts, then this is tailor-made for you.
Richard Hughes of Red Hat brings us this a great article about Linux Vendor Firmware Service, how it got started, and why it makes sense for end users and hardware vendors. LVFS allows vendors of any size to create an account for free and upload re-distributable firmware with standard metadata. LVFS now supports more than 70 different devices, and every month more than 165,000 devices are updated.
By day, Jen Krieger is chief agile architect at Red Hat, but by night she architects stunning LEGO creations. In a recent lightning talk at All Things Open, she shared the expected and unexpected obstacles she overcame in adding LED lighting to her LEGO model.
Sophie Polson is a senior at Duke University studying computer science. Whatever your learning style, whether beginner or expert, Sophie has an approach that is sure to work for you. Be sure to share your own favorite Python learning tool in the comments.