Google's systems send out alerts when they are down to their last few petabytes

Google’s system provides a central brain for controlling tasks across the company’s data centers. Rather than building a separate cluster of servers for each software system — one for Google Search, one for Gmail, one for Google Maps, etc. — Google can erect a cluster that does several different types of work at the same time. All this work is divided into tiny tasks, and Borg sends these tasks wherever it can find free computing resources, such as processing power or computer memory or storage space.

Wilkes says it’s like taking a massive pile of wooden blocks — blocks of all different shapes and sizes — and finding a way to pack all those blocks into buckets. The blocks are the computer tasks. And the buckets are the servers. The trick is to make sure you never waste any of the extra space in the buckets.

“If you just throw the blocks in the buckets, you’ll either have a lot of building blocks left over — because they didn’t fit very well — or you’ll have a bunch of buckets that are full and a bunch that are empty, and that’s wasteful,” Wilkes says.
...

At UC Berkeley, Ben Hindman’s aim was to spread computing tasks across these chips as efficiently as possible. Intel would send him chips. He would wire them together, creating machines that spanned 64 or even 128 cores. And then he worked to build a system that could take multiple software applications and run them evenly across all those cores, sending each task wherever it could locate free processing power.

In March 2010, about a year into the Mesos project, Hindman and his Berkeley colleagues gave a talk at Twitter. Mesos seemed like the perfect way to rebuild Google's Borg.

Google’s new version of Borg — Omega, which Wilkes has publicly discussed — is even closer to the Mesos model.

These are known as “server cluster management systems,” following in the footsteps of similar tools built in years past to run supercomputers and services like the Sun Grid Engine. Both Omega and Mesos let you run multiple distributed systems atop the same cluster of servers. Rather than run one cluster for Hadoop and one for Storm — a tool for process massive streams of data in real-time — you can move them both onto one collection of machines. “This is the way to go,” Wilkes says. “It can increase efficiency — which is why we do it.”

http://www.wired.com/wiredenterprise/2013/03/google-borg-twitter-mesos/…