“Now let us take a step back and summarize a few important developments:

1. The web is a dominant and ubiquitous computing technology. It will replace many traditional desktop application environments and provide ubiquitous information access.
2. Web applications have to cope with increasing demand and scale to larger user bases. Applications that incorporate features such as collaboration and web real-time interaction are facing new challenges as compared to traditional web applications.
3. Multi-core and multiprocessor architectures will dominate the processor landscape. At least for the next decades, performance gains of processors will mostly be attributed to increasing numbers of cores or processors and not to increased clock cycle frequencies.
4. Large, scalable systems can only be designed when taking into account the essence of distributed and concurrent systems. Appropriate programming languages, frameworks and libraries are necessary to implement such systems.

In this thesis, we will bring together these individual developments to have a comprehensive analysis of a particular challenge: How can we tackle concurrency when programming scalable web architectures?…”

http://berb.github.com/diploma-thesis/community/

“We’ve learned to keep things simple. The original backend for Draw Something was designed as a simple key/value store with versioning. The service was built into our existing ruby API (using the merb framework and thin web server). Our initial idea was why not use our existing API for all the stuff we’ve done before, like users, signup/login, virtual currency, inventory; and write some new key/value stuff for Draw Something? Since we design for scale, we initially chose Amazon S3 as our data store for all this key/value data. The idea behind this was why not sacrifice some latency but gain unlimited scalability and storage.
The rest of our stack is pretty standard. Anyone who wants to build scalable systems will attempt to make every layer of the system scale independently from the rest. As the web frontend we use NGINX web server, which points to HAProxy software load balancer, which then hits our ruby API running on a thin web server. The main datastore behind this is MySQL – sharded when absolutely necessary. We use memcached heavily and redis for our asynchronous queueing, using the awesome ruby library called resque…”

http://www.gamasutra.com/view/news/168799/Scale_Something_How_Draw_Something_rode_its_rocket_ship_of_growth.php

“While it’s difficult domain to penetrate — hard numbers are few and far between — we know for a fact that porn sites are some of the most trafficked parts of the internet. According to Google’s DoubleClick Ad Planner, which tracks users across the web with a cookie, dozens of adult destinations populate the top 500 websites. Xvideos, the largest porn site on the web with 4.4 billion page views per month, is three times the size of CNN or ESPN, and twice the size of Reddit. LiveJasmin isn’t much smaller. YouPorn, Tube8, and Pornhub — they’re all vast, vast sites that dwarf almost everything except the Googles and Facebooks of the internet…”

http://www.extremetech.com/computing/123929-just-how-big-are-porn-sites

“One of the questions we always get asked at meet-ups and conversations with other engineers is, “what’s your stack?” We thought it would be fun to give a sense of all the systems that power Instagram, at a high-level; you can look forward to more in-depth descriptions of some of these systems in the future. This is how our system has evolved in the just-over-1-year that we’ve been live, and while there are parts we’re always re-working, this is a glimpse of how a startup with a small engineering team can scale to our 14 million+ users in a little over a year. Our core principles when choosing a system are…”

http://instagram-engineering.tumblr.com/post/13649370142/what-powers-instagram-hundreds-of-instances-dozens-of