The other side of the moon

FOSS.IN runs in Bangalore from the 1st to the 5th of December this year. During the conference, I'll be organising a BoF meet on performance titled Websites on Speed.

In this BoF we'll each bring up a ideas and research that we've been playing with. It's expected to be fairly technical, but how detailed we get depends on what people are interested in. We'll try and cover all layers of the stack that contribute to performance problems, and get into depth on one or two areas chosen on the spot.

This isn't limited to frontend performance.

There's a lot of experimentation, tweaking and understanding of the system involved in web performance, so let's find out what's state of the art today.

In my last post, I mentioned the factors that affect web performance. Now that we know what we need to measure, we come to the harder problem of figuring out how to measure each of them. There are different methods depending on how much control you have over the system and the environment it runs in. Additionally, measuring performance in a test setup may not show you what real users experience, however it does give you a good baseline to compare subsequent tests against.

Web, application and database servers

Back end servers are the easiest to measure because we generally have full control over the system and the environment it runs in. The set up is also largely the same in a test and production environment, and by replaying HTTP logs, it's possible to simulate real user interactions with the server.

Some of the tools one can use to measure server performance are:

• ab - Apache Benchmark. Despite its name, it can be used to test any kind of HTTP server and not just apache. Nixcraft has a good tutorial on using ab.
• httperf from HP labs is also a good tool to generate HTTP load on a server. There's an article on Techrepublic about using it. I prefer httperf because it can be configured to simulate real user load
• Log replaying is a good way to simulate real-user load, and a few people have developed scripts to replay an apache log file. The first one uses httperf under the hood.
• To measure database performance, we could either put profiling code into our application itself, and measure how long it takes for our queries to return under real load conditions, or run benchmarks with the actual queries that we use. For mysql, the mysql benchmarking suite is useful.
• MySQL Tuner is another tool that can tell you how your live production server has been performing though it doesn't give you numbers to quantify perceived performance. I find it useful to tell me if my server needs retuning or not.

The above methods can also be used to measure the performance of remote web service calls, though you may want to talk to your remote web service provider before doing that.

I won't write any more about these because there are a lot of articles about server side performance measurement on the web.

DNS, CDNs and ISP networks

Measuring the performance of DNS, CDNs and your user's ISP network is much harder because you have control over neither the systems nor the environment. Now I mentioned earlier that DNS is something you can control. I was referring to your own DNS set up, ie, the hostnames you have and how they're set up. This is not something we need to measure since no user will use your DNS server. All users use their ISP's DNS server or something like OpenDNS and it's the performance of these servers that we care about.

DNS

DNS is the hardest of the lot since the only way to measure it is to actually put a client application on your users' machines and have that do the measurement. Unless you have really friendly users, this isn't possible. It is an important measurement though. A paper on DNS Performance [Jung et al., 2002] shows that around 20% of all DNS requests fail. This in turn adds to the overall perceived latency of a website. In the absence of an easy way to measure this performance from within a web page, we'll try and figure it out as a side-effect of other measurements.

One possible method is to request the same resource from a host, the first time using the hostname and the second time using its IP address. The difference should give you the DNS lookup time. The problem with this is that it sort of breaks DNS rotations where you may have multiple physical hosts behind a single hostname. It's even worse with a CDN because the hostname may map onto a server that's geographically closer to the user than the IP address you use. In short, you'd better know what you're doing if you try this.

ISP bandwidth

With ISP networks, the number we really care about is the user's effective bandwidth, and it isn't hard to measure this. We use the following procedure:

1. Place resources of known fixed sizes on a CDN
2. Make sure these resources are served with no-cache headers
3. Using javascript, download these resources from the client machine and measure the time it takes
4. Discard the first resource since it also pays the price of a DNS lookup and TCP slowstart
5. Use resources of different sizes to handle very slow and very fast connections.

The number we get will be affected by other things the user is using the network for. For example, if they're streaming video at the same time, then bandwidth measured will be lower than it should be, but we take what we can get.

CDNs

Now to measure bandwidth, we need to get that resource relatively close to the user so that the bandwidth of the whole internet doesn't affect it. That's where CDNs come in, and measuring a CDN's performance is somewhat similar.

We could always use a tool like Gomez or Keynote to do this measurement for you, or you can hack up a solution yourself in Javascript. You need to figure out three things:

1. The IP of the CDN closest to the user
2. The user's geo-location which you can figure out from their IP address
3. The time it takes to download a resource of known size from this CDN

It's that first one that's a toughie, but the simplest way to figure it out is to just ask your CDN provider. Most CDNs also provide you with their own performance reports.

Page content and user interaction

YSlow, Show Slow, Page Speed and Wep Page Test are good tools for measuring and analysing the performance of your page content. They can measure and analyse your page from your development environment and suggest improvements. They do not, however, measure real user perceived performance, however this is something we can do with Javascript.

We primarily need to measure the time it takes to download a page and all its components. Additionally we may want to time how long certain user interactions with the page took. All of these can be accomplished by reading the Date() object in javascript at the correct start and end times. What those start and end times are depend on your application, but we'll look at one possible implementation in a later post. Once you have the timing information that you need, it can be sent back to your server using a javascript beacon. We'll go into more detail about this as well in a later post.

This post has already run longer than I'd hoped for, so I'm going to stop here and will continue next time.

I currently work with the performance team at Yahoo!. This is the team that did the research behind our performance best practices and built YSlow. Most of our past members write and speak about performance, and while I've done a few talks, I've never actually written a public post about web performance. I'm going to try and change that today.

Note, however, that this blog is about many technical topics that interest me and web performance is just a part of that.

I'm never sure how to start a new series, especially one that's been spoken about by others, but since these blog posts also serve as a script for the talks that I do, I thought I'd start with the last performance talk that I did.

Improving a website's performance starts with measuring its current performance. We need a baseline measurement that will help us determine if the changes we make cause an improvement or a regression in performance. Before we start with measurement, however, we need to know what to measure, and for that we need to look at all the factors that contribute to the time it takes for a website to get to the user.

User perceived web app time is spent in looking up stuff, building stuff, downloading stuff, rendering stuff and interacting with stuff.

It's this perceived time that we need to reduce, and consequently measure. All of the above fall into two basic categories:

1. Infrastructure
2. Content structure

Each of these in turn is made up of components that we as developers can control, and those that we cannot. We'd like to be able to measure everything and fix whatever we have control over. I've split the components that I see into this table so we know what can be looked at and who should do the looking.

	Infrastructure	Content
Can control	Web server & App server Database server Web service calls CDNs DNS	HTTP headers HTML Images, Flash CSS Javascript Fonts
Cannot control	ISP's DNS servers ISP's network User's bandwidth User's browser & plugins Other apps using the user's network The internet	Advertisements Third party content included as badges/feeds Third party sites that link to your page

If you have more items to add to this table, leave a comment and I'll add it in.

This is where we can jump to Yahoo!'s performance rules. At the time of this post, there are 34 of them divided into 7 categories. I'll go into more details and refer to these rules in later posts. That's all for this introductory post though.