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As heavy users of PostgreSQL since 2012, we’ve learned quite a bit about operating PostgreSQL at scale. Our Manta object storage system uses a large fleet of sharded, highly-available, replicated PostgreSQL clusters at the heart of the metadata tier. When an end user requests their object, say http://us-east.manta.joyent.com/dap/public/kartlytics/videos/2012-09-06_0000-00.mov, Manta winds up looki
(For returning readers, this is basically a “tl;dr” version of my previous post on Node.js performance. The post below also appears on the Node.js blog.) It’s incredibly easy to visualize where your Node program spends its time using DTrace and node-stackvis (a Node port of Brendan Gregg’s FlameGraph tool): Run your Node.js program as usual. In another terminal, run: $ dtrace -n 'profile-97/execna
2016 Update: The commands and output in this post are pretty dated now, but you can find an up-to-date docs (including a tutorial) in the mdb_v8 user guide. Photo by Auntie P (flickr) I recently wrote an article for ACM Queue discussing postmortem debugging for dynamic environments. I argued that while native environments for years have provided rich tools for understanding software failures postm
We’ve been talking for several weeks now about our work on Cloud Analytics. Today, we’re showing the world what we’ve put together. Now available on Joyent’s Node.js Service: a first look at Cloud Analytics in action – on your very own Node.js application. Cloud Analytics (CA for short) is a tool for real-time performance analysis of production systems and applications deployed in the cloud. If yo
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