We don't have a lot of details on how Google pulled off their technically very impressive Google Instant release, but in Google Instant behind the scenes, they did share some interesting facts: * Google was serving more than a billion searches per day. * With Google Instant they served 5-7X
Strategy
Jesper Söderlund not only put together a few interesting scalability patterns, he also came up with a few interesting scalability lessons: * Lesson #1. Put Smarty compile and template caches on an active-active DRBD cluster with high load and your servers will DIE! * Lesson #2. Don't use out-of-the-box configurations.
Strategy
Jesper Söderlund put together an excellent list of four general scalability patterns and four subpatterns in his post Scalability patterns and an interesting story: * Load distribution - Spread the system load across multiple processing units * Load balancing / load sharing - Spreading the load across many components with equal properties for
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humor
This is so funny I laughed until I cried! Definitely NSFW. OMG it's hilarious, but it's also not a bad overview of the issues. Especially loved: You read the latest post on HighScalability.com and think you are a f*cking Google and architect and parrot
hot links
With summer almost gone, it's time to fall into some good links... * Hibari - distributed, fault tolerant, highly available key-value store written in Erlang. In this video Scott Lystig Fritchie gives a very good overview of the newest key-value store. * Tweets of Gold * lenidot: with 12 staff, @tumblr
The need for IT consolidation is most evident in two types of organizations. In the first group, IT grew organically with business over the decades, and survived changes of strategy, management, staff and vendor orientation. The second group of businesses capital groups are characterized by rapid growth through acquisitions (followed
Consistent Hashing is a specific implementation of hashing that is well suited for many of today’s web-scale load balancing problems. Specifically, it can be seen in use in various caching solutions like Memcached and is applicable to NoSQL solutions as well. Consistent Hashing is used particularly because it provides
In this post I'll cover the difference between multi-core concurrency that is often referred to as Scale-Up and distributed computing that is often referred to as Scale-Out mode. more..
Paper
Can you have your ACID cake and eat your distributed database too? Yes explains Daniel Abadi, Assistant Professor of Computer Science at Yale University, in an epic post, The problems with ACID, and how to fix them without going NoSQL, coauthored with Alexander Thomson, on their paper The Case for
key-value store
Pomegranate is a novel distributed file system built over distributed tabular storage that acts an awful lot like a NoSQL system. It's targeted at increasing the performance of tiny object access in order to support applications like online photo and micro-blog services, which require high concurrency, high throughput,
Product
The Silicon Valley Cloud Computing Group had a meetup Wednesday on OpenStack, whose tag line is the open source, open standards cloud. I was shocked at the large turnout. 287 people registered and it looked like a large percentage of them actually showed up. I wonder, was it the gourmet