Further thoughts on Azure instance start times

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My post from the other day about slow instance starts on Azure caused some commentary (mainly on reddit) that prompted me to think more about all this. In the end, there were a few more experiments I wanted to run to see if I could squeeze more performance out of Azure. First off, looking at the logs from my initial testing it looks like resource groups are slow. The original terraform creates a resource group as part of the test and then cleans it up at the end. What if instead we had a single permanent resource group and created instances within that? Here is a series of instance starts and deletes using the terraform from the last post: You'll notice that there's no delete value for the last instance. That's because terraform crashed and never deleted the instance. You can also see that instance starts are somewhat consistent, except for being slower in the second half of the test than the first, and occasionally spiking out to very very slow. Oh, and deletes are almost always really slow. What happens if we use a permanent resource group and network? This means that all the "instance start terraform" is doing…

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Why is Azure so slow to start instances?

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I've been playing with terraform recently, and decided to see how different the terraform for launching a simple Ubuntu instance in various clouds is. There are two big questions there for me -- how big is the variation between OpenStack derived clouds; and how painful is it to move between the proprietary clouds? Part of this is because terraform doesn't present a standardised layer of cloud functionality, it has a provider per cloud. (Although, I suspect there's nothing stopping someone from writing a libcloud provider or something like that. It is an interesting idea which requires some additional thought.) My terraform implementations for each cloud are on github if you're interested. I don't want to spend a lot of analysis on the actual terraform, because I think the really interesting thing I found isn't where I expected it to be (there's a hint in the title for this post). That said, the OpenStack clouds vary mostly by capabilities. vexxhost for example seems to only offer flavors that require boot-from-volume. The proprietary clouds are complete re-writes, but are generally relatively simple and well documented. However, that interesting accidental thing -- as best as I can tell, Microsoft Azure is really really slow to…

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Python effective TLD library update

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The effective TLD library is now being used for a couple of projects of mine, but I've had some troubles with it being almost unusable slow. I ended up waking up this morning with the revelation that the problem is that I use regexps to match domain names, but the failure of a match occurs at the end of a string. That means that the FSA has to scan the entire string before it gets to decide that it isn't a match. That's expensive. I ran some tests on tweaks to try and fix this. Without any changes, scanning 1,000 semi-random domain names took 6.941666 seconds. I then tweaked the implementation to reverse the strings it was scanning, and that halved the run time of the test to 3.212203 seconds. That's a big improvement, but still way too slow. The next thing I tried was then adding buckets of rules on top of those reverse matches.... In other words, the code now assumes that anything after the last dot is some for of TLD approximation, and only executes rules which also have that string after the last dot. This was a massive improvement, with 1,000 domains taking only 0.026120 seconds.…

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MySQL Tech Talks

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Three intrepid MySQLers came to Google after the user conference to give internal tech talks. They were kind enough to agree to us hosting them for other people to see. The first two are up, so I'll mention those now, and put a link to the last one when it's available... Click on the thumbnail to be taken to the video. Jay Pipes is a co-author of the recently published Pro MySQL (Apress, 2005), which covers all of the newest MySQL 5 features, as well as in-depth discussion and analysis of the MySQL server architecture, storage engines, transaction processing, benchmarking, and advanced SQL scenarios. You can also see his name on articles appearing in Linux Magazine and can read more articles about MySQL at his website. Jay Pipes is MySQL's Community Relations Manager for North America. Learn where to best focus your attention when tuning the performance of your applications and database servers, and how to effectively find the "low hanging fruit" on the tree of bottlenecks. It's not rocket science, but with a bit of acquired skill and experience, and of course good habits, you too can do this magic! Timour Katchaounov The first part of this talk describes…

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