Between love and madness lies HighScalability:

• Google now 10x better: MapReduce sorts 1 petabyte of data using 8000 computers in 33 minutes; 1 Billion on Social Networks; Tumblr at 10 Billion Posts; Twitter at 100 Million Users; Testing at Google Scale: 1800 builds, 120 million test suites, 60 million tests run daily.
• From the Dash Memo on Google's Plan: Go is a very promising systems-programming language in the vein of C++. We fully hope and expect that Go becomes the standard back-end language at Google over the next few years. On GAE Go can load from a cold start in 100ms and the typical instance size is 4MB. Is it any wonder Go is a go? Should we expect to see Java and Python deprecated because Go is so much cheaper to run at scale?
• Walmart uses Muppet labor to power their real-time social shopping systems: You can’t do MapReduce computing every time (with every Tweet). You’ll die. How do you do it in real-time? We built MapUpdate, or what we call Muppet. We could map a huge amount of data and handle a huge firehose with little latency across millions of entities… We can monitor 100 million (items) at scale. That could be products, stores, anything. It’s the equivalent of MapReduce for fast data.
• Like humans, this AI software is always seeking relations. TextRunner produces facts by digesting 500 million web pages and billions of lines of text. Peter Norvig, director of research at Google: "The significance of TextRunner is that it is scalable because it is unsupervised. It can discover and learn millions of relations, not just one at a time. With TextRunner, there is no human in the loop: it just finds relations on its own."