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For years a war has been fought in the software architecture trenches between the ideal of decentralized services and the power and practicality of centralized services. Centralized architectures, at least at the management and control plane level, are winning. And Google not only agrees, they are enthusiastic adopters of this
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In a recent thread on Hacker News one of the commenters mentioned that they use Digital Ocean for personal stuff, but use AWS for business. This DO for personal and AWS for business split has become popular enough that we can now give it a name: the Mullet Cloud Selection
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Caching is not new of course, but I don't think I've heard of caching store procedure results before. It's like memoization in the database. Brent Ozar covers this idea in How to Cache Stored Procedure Results. The benefits are the usual for doing work
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Facebook has been teasing us. While many of their recent acquisitions have been surprising, shocking is the only word adequately describing Facebook's 5 day whirlwind acquisition of Oculus, immersive virtual reality visionaries, for a now paltry sounding $2 billion. The backlash is a pandemic, jumping across social networks
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Matthew Might, as a first responder to a surprise traffic surge on his inexpensive linode hosted blog, took emergency steps that you might find useful in a similar situation: 1. Find the bottleneck. Reloading the page in firebug showed the first page took 24 seconds to load and after that
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Guest post by Asya Kamsky, Principal Solutions Architect at MongoDB. This post outlines ten things you need to know for operating MongoDB at scale based on my experience working with MongoDB customers and open source users: 1. MongoDB requires DevOps, too. MongoDB is a database. Like any other data store,
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This is a guest post by Patrick Eaton, Software Engineer and Distributed Systems Architect at Stackdriver. Stackdriver provides intelligent monitoring-as-a-service for cloud hosted applications. Behind this easy-to-use service is a large distributed system for collecting and storing metrics and events, monitoring and alerting on them, analyzing them, and serving up
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Inspired by a xkcd comic, Peter Norvig, Director of Research at Google and all around interesting and nice guy, has created an above par code kata involving a regex program that demonstrates the core inner loop of many successful systems profiled on HighScalability. The original code is at xkcd 1313:
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HackerEarth is a coding skill practice and testing service that in a series of well written articles describes the trials and tribulations of building their site and how they overcame them: Scaling Python/Django application with Apache and mod_wsgi, Programming challenges, uptime, and mistakes in 2013, Post-mortem: The big
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Monitor, monitor, monitor. That's the advice every startup gives once they reach a certain size. But can you ever monitor enough? If you are Bitly and everyone will complain when you are down, probably not. Here are 10 Things We Forgot to Monitor from Bitly, along with good
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Stardog makes a commercial graph database that is a great example of what can be accomplished with a scale-up strategy on BigIron. In a recent article StarDog described how they made their new 2.1 release insanely scalable, improving query scalability by about 3 orders of magnitude and it can
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There's a deep similarity between how long running systems like our brains and computers accumulate errors and repair themselves. Reboot it. Isn’t that the common treatment for most computer ailments? And you may have noticed now that your iPhone supports background processing it reboots a lot more