As seen today on Google Reader. A strip is a strip is a strip is a strip:
What to do when the meteor strikes
There’s nothing quite like a good Single Point of Failure (SPOF) during a holiday dinner.
says John Farmer on his blog, and I couldn’t agree more. Start with a meteor strike scenario for a change, just imagine a giant rock crushing your measly SPOF-ridden infrastructure in one unlucky data center. Waiting for the black swan to appear learn to keep calm and react normally using the tips from a triple post about incidents, outages and systems maintenance:
Simple problems can easily become large complicated problems after a few bad decisions made in haste. Take a breath before continuing. This is especially important with a page at 3AM or if a panicky client is in your office. Tell the client you’ll handle the problem and run through your normal procedure.
[...]
Remember the prime directive – your job is to restore service as quickly as possible. You are not there to debug interesting problems with your service.
Recommended reading!
Linkdump: leaner meaner MySQL, gulping from the data buffet and lessons learned at Reddit
The Percona guys are pleading for a MySQL strongly optimized for a single type of storage engine:
We could save a lot of CPU cycles by having storage format same as processing format. We could tune Optimizer to handle Innodb specifics well. We could get rid of SQL level table locks and using Innodb internal data dictionary instead of Innodb files. We would use Innodb transactional log for replication (which could be extended a bit for this purpose). Finally backup can be done in truly hot way without nasty “FLUSH TABLE WITH READLOCK” and hoping nobody is touching “mysql” database any more. Single Storage Engine server would be also a lot easier to test and operate.
This also would not mean one has to give up flexibility completely, for example one can imagine having Innodb tables which do not log the changes, hence being faster for update operations.
Looks like Twitter data buffet is back in business. Some of the data is free. Enjoy it with moderation: too much data can make you slow.
Reddit’s Steve Huffman gives a talk at Web Apps Miami 2010. Self-healing, separation of services, be stateless and cache like crazy, redundancy and yes, a little bit of Hadoop (Amazon’s Hadoop is Elastic Map Reduce). Read the full transcript on Carsonified:
We’ve actually been using Hadoop, Amazon’s Hadoop implementation to compute awards. If we need to do a complicated query like that, we store the data, we dump our database, or at the right time we store it in a way that will make those joins possible down the road. That being said; we’ve tried to avoid doing joins as much as possible, and when the data comes in we store it in the way we’re going to need it. That’s worked much better than trying to do it at run time.
And now for something a little different: graphviz candy
No self-respecting geek can resist either of these incredible temptations:
- Correct something wrong on “the internets”
- Produce a little bit of graphviz candy (what a fantastic tool)
Linkdump: Coop, HBase performance and a bit of Warcraft
Riptano is to Cassandra what Cloudera is to Hadoop or Percona to MySQL. Mmmkey?
A great, insightful post from Pingdom (as usual) allows us to take a peek behind the doors at largest web sites in the world, just by reading selected stuff from their respective developer blogs.
Yahoo decreased data-center cooling costs compared to power costs from 50 cents/dollar to only one cent/dollar. This is obtained on their most recent Yahoo Computing Coop data-center built in Lockport, New York.
The data center operates with no chillers, and will require water for only a handful of days each year. Yahoo projects that the new facility will operate at a Power Usage Effectiveness (PUE) of 1.1, placing it among the most efficient in the industry. [...]
If it looks like a chicken coop, it’s because some of the design principles were adapted from …. well, chicken coops. “Tyson Foods has done research involving facilities with the heat source in the center of the facility, looking at how to evacuate the hot air,” said Noteboom. “We applied a lot of similar thought to our data center.”
The Lockport site is ideal for fresh air cooling, with a climate that allows Yahoo to operate for nearly the entire year without using air conditioning for its servers.
High Scalability blog dissects a paper describing Dapper, Google’s tracing system used to instrument all the components of a software system in order to understand its behavior. Immensely interesting:
As you might expect Google has produced and elegant and well thought out tracing system. In many ways it is similar to other tracing systems, but it has that unique Google twist. A tree structure, probabilistically unique keys, sampling, emphasising common infrastructure insertion points, technically minded data exploration tools, a global system perspective, MapReduce integration, sensitivity to index size, enforcement of system wide invariants, an open API—all seem very Googlish.
On my favorite blog 
HStack.org Andrei wrote a great post about real-life performance testing of HBase:
The numbers are the tip of the iceberg; things become really interesting once we start looking under the hood, and interpreting the results.
When investigating performance issues you have to assume that “everybody lies”. It is crucial that you don’t stop at a simple capacity or latency result; you need to investigate every layer: the performance tool, your code, their code, third-party libraries, the OS and the hardware. Here’s how we went about it:
The first potential liar is your test, then your test tool – they could both have bugs so you need to double-check.
But the most interesting distributed system of the week is World of Warcraft. Ars Technica describes a tour of the Blizzard campus and here’s a peek at the best NOC screen ever:
For the hooorde!