Category: optimization

Coffee A/B testing

Post author By Yoav Aner
Post date 19 June, 2014

I do quite a bit of A/B testing and find it to be a great tool for experimenting and ultimately improving things.

But what’s “Coffee A/B testing”?

The idea came to me when I was visiting my wife’s family in Japan. We went to a restaurant and my father and brother in-law ordered two types of Sake. They let me taste both and decide which one I liked the most. It was a simple task, but an interesting one. The tastes were subtly different, but enough that I could clearly pick my personal favourite.

It then occurred to me that as much as I love coffee, and tend to pick some beans over others, I don’t quite know what makes me like a certain type, or what it is that I’m looking for for my “ultimate” coffee.

What if I could A/B test coffees? Try two types of beans (or blends), and pick the one I like. Then repeating the process I could gradually find the one I like the most. And in doing that, I can also figure out what it is that I like, and pay more attention to the difference. I rarely compare coffees. Well, not any more!

Matryoshka Fragment Caching in Rails

Post author By Yoav Aner
Post date 16 July, 2013

“Russian doll Caching” gained some popularity recently, I suspect in part due to its catchy (or cachie?) name and how easy it is to visualize the concept. Rails 4 should have this improved caching available by default. With Rails 3 you need to install the cache-digests gem. It’s pretty easy to get started with it, and the documentation is clear. It makes a lot of sense to start using it in your Rails app. I won’t attempt to cover the basics and will assume you are already familiar with it. I want to talk about a specific aspect of fragment caching surrounding the generation of the cache keys.

optimization Technology wordpress

How much (cache) is too much?

Post author By Yoav Aner
Post date 17 March, 2012

One of the best rules of thumb I know is the 80/20 rule. I can’t think of a more practical rule in almost any situation. Combined with the law of diminishing returns, it pretty much sums up how the universe works. One case-study that hopes to illustrate both of these, if only a little, is a short experiment in optimization I carried out recently. I was reading so many posts about optimizing wordpress using nginx, varnish, W3-Total-Cache and php-fpm. The results on some of them were staggering in terms of improvements, and I was inspired to try to come up with a similar setup that will really push the boundary of how fast I can serve a wordpress site.

Spoiler – Conclusion

So I know there isn’t such a thing as too much cash, but does the same apply to cache?

django optimization python Security

Keep your hands off my tastypie

Post author By Yoav Aner
Post date 26 January, 2012

Update

Please note that since Tastypie v0.9.12 the authorization framework was rewritten. Lots of information on this post no longer applies. I’m hoping to write a follow-up post at some stage.

Original Post

I’ve been using tastypie, the very awesome django REST API framework for a little while now (btw, that’s not the official title, but it might as well be). I’m not going to write yet another comparison between tastypie and django-piston. My reasons for choosing tastypie were that its code looked nicer, and it seemed a much more active project.

One of the things that I immediately liked about tastypie, being a security-geek and all, was the security framework built into it. Primarily the authentication and authorization classes. They make it very easy to extend, and almost a no-brainer to apply to any resource. This means that providing resource-level authorization is also very easy and clean.

However, whilst working with tastypie and applying some authorization rules to my resources, I noticed a couple of pitfalls. Those are quite easy to miss if you’re not very familiar with the tastypie codebase. I wouldn’t say it’s a vulnerability or a bug as such, perhaps more of a (sub-optimal) design choice from a security-perspective. That said, if you use tastypie incorrectly, or unaware of those pitfalls, you might create a security vulnerability on your otherwise delicious API.

django monitoring optimization python Technology

django memory leaks, part II

Post author By Yoav Aner
Post date 16 December, 2011

On my previous post I talked about django memory management, the little-known maxrequests parameter in particular, and how it can help ‘pop’ some balloons, i.e. kill and restart some django processes in order to release some memory. On this post I’m going to cover some of the things to do or avoid in order to keep memory usage low from within your code. In addition, I am going to show at least one method to monitor (and act automatically!) when memory usage shoots through the roof.

django monitoring optimization python Technology

django memory leaks, part I

Post author By Yoav Aner
Post date 11 December, 2011

A while ago I was working on optimizing memory use for some django instances. During that process, I managed to better understand memory management within django, and thought it would be nice to share some of those insights. This is by no means a definitive guide. It’s likely to have some mistakes, but I think it helped me grasp the configuration options better, and allowed easier optimization.

Does django leak memory?

In actual fact, No. It doesn’t. The title is therefore misleading. I know. However, if you’re not careful, your memory usage or configuration can easily lead to exhausting all memory and crashing django. So whilst django itself doesn’t leak memory, the end result is very similar.

Memory management in Django – with (bad) illustrations

Lets start with the basics. Lets look at a django process. A django process is a basic unit that handles requests from users. We have several of those on the server, to allow handling more than one request at the time. Each process however handles one request at any given time.

But lets look at just one.

cute, isn’t it? it’s a little like a balloon actually (and balloons are generally cute). The balloon has a certain initial size to allow the process to do all the stuff it needs to. Lets say this is balloon size 1.

monitoring optimization python Technology

cron woes – file timsetamp monitoring plugin for munin

Post author By Yoav Aner
Post date 2 July, 2008

I don’t like being late. It runs in the family. My dad is so obsessed with being late that he’s always early. How embarrassing. Unfortunately I seemed to have inherited it from him. I do however try to compensate. I am deliberately late on-time. I usually plan to be a bit late.

Anyway, enough about me.