Skype's 220 millions users lost service for a stunning two days. The primary cause for Skype's nightmare (can you imagine the beeper storm that went off?) was a massive global roll-out of a Window's patch triggering the simultaneous reboot of millions of machines across the globe. The secondary cause was a bug in Skype's software that prevented "self-healing" in the face of such attacks. The flood of log-in requests and a lack of "peer-to-peer resources" melted their system.
Who's fault is it? Is Skype to blame? Is Microsoft to blame? Or is the peer-to-peer model itself fundamentally flawed in some way?
Let's be real, how could Skype possibly test booting 220 million servers over a random configuration of resources? Answer: they can't. Yes, it's Skype's responsibility, but they are in a bit of a pickle on this one.
The boot scenario is one of the most basic and one of the most difficult scalability scenarios to plan for and test. You can't simulate the viciousness of real-life conditions in a lab because only real-life has the variety of configurations and the massive resources needed to simulate itself. It's like simulating the universe. How do you simulate the universe if the computational matrix you need is the universe itself? You can't. You end up building smaller models and those models sometimes fail.
I worked at set-top company for a while and our big boot scenario was the restart of entire neighbor hoods after a power failure. To make an easy upgrade path, each set-top downloaded their image from the head-end on boot, only a boot image was in EEPROM.
This is a very stressful scenario for the system. How do you test it? How do you test thousands of booting set-tops when they don't even exist yet? How do you test the network characteristics of a cable system in the lab? How do you design a system not to croak under the load?
Cleverness. One part of the solution was really cool. The boot images were continually broadcast over the network so each set-top would pick up blocks of the boot image. The image would be stitched together from blocks rather than having thousands of boxes individually download images, which would never work. This massively reduced the traffic over the network. Clever tricks like this can get you a long ways.
Work. Great pools of workstations were used simulate set-tops and software was made to insert drops and simulate asymmetric network communications. But how could we ever simulate 220 million different users? Then, no way. Maybe now you could use grid services like Amazon's EC2.
Help from your friends. Microsoft is not being a good neighbor. They should roll out updates at a much more gradual rate so these problems don't happen. Booting loads networks, taxes CPUs, fills queues, drops connections, stresses services, increases process switching, drops packets, encourages dead lock, steals RAM and file descriptors and other resources. So it would be nice if MS was smarter about their updates. But since you can't rely on such consideration, you always have to handle the load.
I assume they used exponential backoff algorithms to limit login attempts, but with so many people this probably didn't matter. Perhaps they could insert a random wait to smooth out login traffic. But again, with so many people it probably won't matter. Perhaps they could stop automatic logins on boot? That would solve the problem at the expense of user convenience. No go. Perhaps their servers could be tuned to accept connections at a fast rate yet condition how quickly they respond to the rest of the login process? Not good enough I suppose.
So how did Skype fix their problem? They explain it here :
The parameters of the P2P network have been tuned to be smarter about how similar situations should be handled. Once we found the algorithmic fix to ensure continued operation in the face of high numbers of client reboots, the efforts focused squarely on stabilizing the P2P core. The fix means that we’ve tuned Skype’s P2P core so that it can cope with simultaneous P2P network load and core size changes similar to those that occurred on August 16.
Whenever I see the word "tune" I get the premonition shivers. Tuning means you are just one unexpected problem away from being out of tune and your perfectly functioning symphony sounding like a band of percussion happy monkeys. Tuned things break under change. Tweak the cosmological constant just a little and wham, there's no human life. It needs to work by design. Or it needs to be self-adaptive and not finessed by human hands for each new disaster scenario.
And this is where we get into the nature of P2P. Would the same problem have happened in a centralized architecture with resources spread strategically throughout the globe and automatic load balancing between different data centers? In a centralized model would it have been easier to bring more resources on line to handle the load? Would the outage have been easier to diagnose and last a much shorter amount of time?
There are of course no definitive answers to these questions. But many of the web's most successful systems like YouTube, Amazon, Ebay, Google, GoogleTalk, and Flickr use a centralized model. They handle millions of users and massive amounts of content and have pretty good reliability records.
Does P2P bring enough to the architecture that you should build a system around it? That to me is the interesting question that arises out of this incident.