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by sophacles 5715 days ago
Thanks! My app was in that datacenter too. I mean, it had replicated mongodb instances, and well balanced app servers, and nodes going away have no discernable affect on users. Turns out tho, that with all that distributed engineering, I didn't find out that the hosting company doesn't put your nodes in various data-centers. That tornado would have taken down my service during peak hours.

I know you will try to write that off as a "you get what you diserve" but I challenge you to go ask people if their apps would survive a tornado to the data-center. Many of them will say "sure its in the cloud!" Then drop the killer question on them... "How many different data centers are your nodes running on right now". Most will say "i dont know". Some will say "My host has many data centers" (note this doesn't answer the question). A few will actually have done the footwork.

Also, the scenario you describe is as easily mitigated with hot failovers and offsite backups. This probably qualifies as distributed engineering, but only is only the same as the above discussions in the most pedantic senses.

1 comments

As MongoDB did not exist at the time, it seems unlikely. Such things happen more than we might like, of course!

"Also, the scenario you describe is as easily mitigated with hot failovers and offsite backups."

This is a sadly wrong, though common, belief. There is exactly one way to know that a component in your infrastructure is working: you are using it. There is no such thing as a "hot failover": there are powered on machines you hope will work when you need them. Off-site backups? Definitely a good idea. Ever tested restore of a petabyte?

Here's a simple test. If you believe either of the following are true, with extremely high probability you have never done large-scale operations:

1) There exists a simple solution to a distributed systems problem.

2) "Failover", "standby", etc. infrastructure can be relied upon to work as expected.

Extreme suffering for extended periods burns away any trust one might ever have had in either of those two notions.

First and foremost, the opposite of simple is not hard, it's complicated. There is not a correlation between the simple-complicated spectrum and easy-hard spectrum.

If you don't regularly press the button swapping your hot failovers and live systems, you don't have hot failovers, you have cargo-cult redundancy. It's like taking backups and not testing them. If you don't test them, you have cargo cult sysadmining.

Distributed is complicated, but not that hard, there are well understood patterns in most cases. Sure, the details are a bit of a pain to get right, but the same is true of alot of programming. I have done distributed systems. Maybe not google scale, but bigger than a lot, hundreds of nodes geographically distributed all over the place, and each of these nodes was itself a distributed system. I've dealt with thundering herds (and other statistical clustering issues), can't-happen bottlenecks, and plenty more. But each and every one of these problems had a solution waiting for me on google. Further, each and every one of these problems was instantly graspable.

A lot of distributed stuff just isn't that hard. Sure, things like MPI and distributed agents/algorithms can get pretty hard, but this isn't the same as multi-node programs, which isn't the same as redundancy.

Keep the smug attitude, I'm sure it helps you convince your clients that you are "really good" or some crap.

You're talking to the guy who invented EC2. I think he knows what's hard.

http://blog.layer8.net/ec2_origins.html

Im not intimidated. If anything, he should be more far, far more understanding of the point then: A simple fail-over model for a smallish database is completely different than a full blown EC2. In fact given that EC2 is a freakishly large example of distributed system, I would put it in a totally different class of product than the average "big distributed system".