It's HighScalability Time:

• Yottabytes : What NSA knows about US; 214ms : ping between San Jose and Fez; $42M : MongoDB is funding scale!; 20K : lines of THX sound code
• @adrianco: My takeaway from the MongoDB talk at ‪#gluecon‬ is that Mongo is implementing eventual scalability in the next version
• The death of the general purpose computer is causing strange events like Facebook making their own smart phone. Adam Smith said we all benefit when our neighbors get richer, it creates a bigger pie. We are heading back to the mercantalist notion of a zero sum game. Google is also racing to the bottom Google Product Search To Become Google Shopping, Use Pay-To-Play Model. Zero sum thinking always leads to war. Just sayin.
• Stuxnet, sometimes you just can't keep it in your pants and Pandora always complained that lid was never on very tight. Bad Prometheus.

Edward Capriolo has a really interesting article on his dramatic performance expanding experience of turning on compression for Cassandra. The idea:

• Enabling compression shrunk 71GB of data down to  31GB, which caused more data to fit in RAM, which reduced disk IO to nearly nothing.
• Compression means more data can be stored, which is like buying more machines without having to spend more money.
• Compression means serving more data out of RAM, which means clients are happier because of the performance improvements.
• The cost is higher CPU usage to perform the encrypt/decrypt. But disk IO is orders of magnitude slower than decompression and most servers have CPU to burn.

Edward's article is well written, has the specifics on how to turn on compression for Cassandra, pretty graphs, and lots more details.

This is the second guest post (part 1) of a series by Greg Lindahl, CTO of blekko, the spam free search engine. Previously, Greg was Founder and Distinguished Engineer at PathScale, at which he was the architect of the InfiniPath low-latency InfiniBand HCA, used to build tightly-coupled supercomputing clusters.

What's so hard about crawling the web?

Web crawlers have been around as long as the Web has -- and before the web, there were crawlers for gopher and ftp. You would think that 25 years of experience would render crawling a solved problem, but the vast growth of the web and new inventions in the technology of webspam and other unsavory content results in a constant supply of new challenges. The general difficulty of tightly-coupled parallel programming also rears its head, as the web has scaled from millions to 100s of billions of pages.

Existing Open-Source Crawlers and Crawls

It's HighScalability Time:

• 15 million 64 GB iPods every day: IBM on the Big Bang; Billions of msgs/day, 75Bn ops/day, 1.5M ops/sec peak. 250TB new data/mo and growing: Facebook HBase stats; 72 hours of video uploaded every minute: YouTube
• Quotable Quotes:
  • @ammeep: Great discussion on data scalability and caching approaches at ‪#yellowcamp‬ "a cache is like your best mate you can never trust"
  • @adrianco: Why do OpenStack talks I go to always focus on the story of how they did it rather than how it works and what it does for me? ‪#Gluecon‬.
  • Cliff Moon: Incuriosity killed the infrastructure.
  • @seldo2: "NoSQL is a land grab against the DBAs the prevent you from doing shit" - @monkchips ‪#gluecon‬
  • @mjasay: Netflix's @atseitlin: Build for fail, not for scale. Focus on service-level metrics, not individual servers, when monitoring system health
  • @peakscale: I liked the part about "graph DBs are a niche data model... that only covers 95% of situations" ‪#gluecon‬
  • joshfraser: I personally prefer using the 95th or 99th percentiles because they force you to keep the mindset that you need to be fast for everyone
• In the best laid plans of mice and men department: Nasdaq's Facebook Glitch Came From Race Conditions. Seems as if all the bidding action starved the price calculator of enough time to do the actual calculation.

In this example we have taken the same Twitter/Facebook-like blueprint, and made it simple enough for developers to implement. We have taken the following approach in our implementation: 

1. Use In Memory Data Grid (XAP) for handling the real time stream data-processing.
2. BigData data-base (Cassandra) for storing the historical data and manage the trend analytics 
3. Use Cloudify (cloudifysource.org)  for managing and automating the deployment on private or pubic cloud

The example demonstrate a simple case of word count analytics. It uses Spring Social to plug-in to real twitter feeds. The solution is designed to efficiently cope with getting and processing the large volume of tweets. First, we partition the tweets so that we can process them in parallel, but we have to decide on how to partition them efficiently. Partitioning by user might not be sufficiently balanced, therefore we decided to partition by the tweet ID, which we assume to be globally unique. Then we need persist and process the data with low latency, and for this we store the tweets in memory.

This guest post is written by Josh Fraser, co-founder and CEO of Torbit. Torbit creates tools for measuring, analyzing and optimizing web performance.  

Did you know that 5% of the pageviews on Walmart.com take over 20 seconds to load? Walmart discovered this recently after adding real user measurement (RUM) to analyze their web performance for every single visitor to their site. Walmart used JavaScript to measure their median load time as well as key metrics like their 95th percentile. While 20 seconds is a long time to wait for a website to load, the Walmart story is actually not that uncommon. Remember, this is the worst 5% of their pageviews, not the typical experience.

Who's Hiring? 

• Torbit is hiring! Care about performance? Care about making the internet faster and better? At Torbit we use lots of Golang, Node.js, JavaScript and PHP to solve big challenges.

Fun and Informative Events

• The DevOps PaaS Infusion Meetup NYC - Taking Mission-Critical Apps to the Cloud. You’ll hear real world use cases from Microsoft, Aditi, Cisco, GigaSpaces, and C24. Register here:  http://bit.ly/IpgpaN. 
• O'Reilly Velocity, the Web Performance and Operations conference, is happening in Santa Clara, CA from June 25-27. Learn from your peers, exchange ideas with experts, and share best practices and lessons learned. Register here.
• Sign up for this free 30-minute webinar exploring how new technology can determine which ads have been seen by users and will discuss the C3 Metrics Labs analysis of over 2 billion impressions. 

Cool Products and Services

• Reality Check Network offers powerful hosting solutions and managed servers for high traffic/bandwidth websites backed by unlimited network, server and application support.
• When you’re looking for the fastest, lightest, most complete toolset for rapidly building high performance Web 2.0 applications, you want NetAdvantage for ASP.NET.
• Create your most stunning, highly performant, and completely mobile HTML5 applications and dashboards on any browser, platform or device – only with NetAdvantage for jQuery.
• aiCache creates a better user experience by increasing the speed scale and stability of your web-site. Test aiCache acceleration for free.  No sign-up required. http://aicache.com/deploy
• LogicMonitor - Hosted monitoring of your entire technology stack. Dashboards, trending graphs, alerting. Try it free and be up and running in just 15 minutes.
• New Relic - real user monitoring optimize for humans, not bots. Live application stats, SQL/NoSQL performance, web transactions, proactive notifications. Take 2 minutes to sign up for a free trial.
• AppDynamics is the very first free product designed for troubleshooting Java performance while getting full visibility in production environments. Visit http://www.appdynamics.com/free.
• CloudSigma. Utility style high performance cloud servers in the US and Europe delivered on all 10GigE networking. Run any OS, take advantage of SSD storage and tailored infrastructure options.
• ManageEngine Applications Manager : Monitor physical, virtual and Cloud Applications.
• www.site24x7.com : Monitor End User Experience from a global monitoring network.

For a longer description of each sponsor, please read more below...

There has been an update on Pinterest: Pinterest growth driven by Amazon cloud scalability since our last post: A Short on the Pinterest Stack for Handling 3+ Million Users.

With Pinterest we see a story very similar to that of Instagram. Huge growth, lots of users, lots of data, with remarkably few employees, all on the cloud.

While it's true that both Pinterest and Instagram are not making great advances in science and technology, that is more indicator of the easy power of today's commodity environments rather than a sign of Silicon Valley's lack of innovation. The numbers are so huge and the valuations are so high we naturally want some sort of fundamental technological revolution to underlie their growth. The revolution is more subtle. It really is just that easy to attain such growth these days, if you can execute on the right idea. Get used to it. This is the new normal.

Here's what Pinterest looks like today: 

It's HighScalability Time:

• 42 Billion: Netflix API Requests/Month
• Quotable quotes:
  • @commonlisp: Ideas from the talk: In Haskell laziness + thunks + garbage collection (GC) impede multicore scalability. Parallel GC is crucial.
  • @Bulldozer0: Global state is the enemy of scalability; not only in software, but in governance.
• If you've ever, as I have, felt the terror of a misplaced "rm -rf /", you'll love this story: Did Pixar accidentally delete Toy Story 2 during production? It did, the reconstruction was heroic, and parts of Toy Story 2 were lost forever.

In Zen And The Art Of Scaling - A Koan And Epigram Approach, Russell Sullivan offered an interesting conjecture: there are 20 classic bottlenecks. This sounds suspiciously like the idea that there only 20 basic story plots. And depending on how you chunkify things, it may be true, but in practice we all know bottlenecks come in infinite flavors, all tasting of sour and ash.

One day Aurelien Broszniowski from Terracotta emailed me his list of bottlenecks, we cc’ed Russell in on the conversation, he gave me his list, I have a list, and here’s the resulting stone soup.

Russell said this is his “I wish I knew when I was younger" list and I think that’s an enriching way to look at it. The more experience you have, the more different types of projects you tackle, the more lessons you’ll be able add to a list like this. So when you read this list, and when you make your own, you are stepping through years of accumulated experience and more than a little frustration, but in each there is a story worth grokking.

• Database: