However, for many sites that reference dozens of external objects, the majority of the page load time is spent in separate HTTP requests for images, javascript, and stylesheets. AJAX probably could help, but speeding up or eliminating these separate HTTP requests might help more, yet there isn't a common body of knowledge about how to do so.
While working on optimizing page load times for a high-profile AJAX application, I had a chance to investigate how much I could reduce latency due to external objects. Specifically, I looked into how the HTTP client implementation in common browsers and characteristics of common Internet connections affect page load time for pages with many small objects.
Try some of the following:Turn on HTTP keepalives for external objects. Otherwise you add an extra round-trip for every HTTP request. If you are worried about hitting global server connection limits, set the keepalive timeout to something short, like 5-10 seconds. Also look into serving your static content from a different webserver than your dynamic content. Having thousands of connections open to a stripped down static file webserver can happen in like 10 megs of RAM total, whereas your main webserver might easily eat 10 megs of RAM per connection.
Load fewer external objects. Due to lower request overhead, one bigger file just loads faster than two smaller ones half its size. Figure out how to globally reference the same one or two javascript files and one or two external stylesheets instead of many; if you have more, try preprocessing them when you publish them. If your UI uses dozens of tiny GIFs all over the place, consider switching to a much cleaner CSS-based design which probably won't need so many images. Or load all of your common UI images in one request using a technique called "CSS sprites".
If your users regularly load a dozen or more uncached or uncacheable objects per page, consider evenly spreading those objects over four hostnames. This usually means your users can have 4x as many outstanding connections to you. Without HTTP pipelining, this results in their average request latency dropping to about 1/4 of what it was before.
When you generate a page, evenly spreading your images over four hostnames is most easily done with a hash function, like MD5. Rather than having all
tags load objects from http://static.example.com/, create four hostnames (e.g. static0.example.com, static1.example.com, static2.example.com, static3.example.com) and use two bits from an MD5 of the image path to choose which of the four hosts you reference in the
tag. Make sure all pages consistently reference the same hostname for the same image URL, or you'll end up defeating caching.
Beware that each additional hostname adds the overhead of an extra DNS lookup and an extra TCP three-way handshake. If your users have pipelining enabled or a given page loads fewer than around a dozen objects, they will see no benefit from the increased concurrency and the site may actually load more slowly. The benefits only become apparent on pages with larger numbers of objects. Be sure to measure the difference seen by your users if you implement this.
Possibly the best thing you can do to speed up pages for repeat visitors is to allow static images, stylesheets, and javascript to be unconditionally cached by the browser. This won't help the first page load for a new user, but can substantially speed up subsequent ones.
Set an Expires header on everything you can, with a date days or even months into the future. This tells the browser it is okay to not revalidate on every request, which can add latency of at least one round-trip per object per page load for no reason.
Instead of relying on the browser to revalidate its cache, if you change an object, change its URL. One simple way to do this for static objects if you have staged pushes is to have the push process create a new directory named by the build number, and teach your site to always reference objects out of the current build's base URL. (Instead of
you'd use 
. When you do another build next week, all references change to 
.) This also nicely solves problems with browsers sometimes caching things longer than they should -- since the URL changed, they think it is a completely different object.If you conditionally gzip HTML, javascript, or CSS, you probably want to add a "Cache-Control: private" if you set an Expires header. This will prevent problems with caching by proxies that won't understand that your gzipped content can't be served to everyone. (The Vary header was designed to do this more elegantly, but you can't use it because of IE brokenness.)
For anything where you always serve the exact same content when given the same URL (e.g. static images), add "Cache-Control: public" to give proxies explicit permission to cache the result and serve it to different users. If a local cache has the content, it is likely to have much less latency than you; why not let it serve your static objects if it can?
Avoid the use of query params in image URLs, etc. At least the Squid cache refuses to cache any URL containing a question mark by default. I've heard rumors that other things won't cache those URLs at all, but I don't have more information.
On pages where your users are often sent the exact same content over and over, such as your home page or RSS feeds, implementing conditional GETs can substantially improve response time and save server load and bandwidth in cases where the page hasn't changed.
When serving a static files (including HTML) off of disk, most webservers will generate Last-Modified and/or ETag reply headers for you and make use of the corresponding If-Modified-Since and/or If-None-Match mechanisms on requests. But as soon as you add server-side includes, dynamic templating, or have code generating your content as it is served, you are usually on your own to implement these.
The idea is pretty simple: When you generate a page, you give the browser a little extra information about exactly what was on the page you sent. When the browser asks for the same page again, it gives you this information back. If it matches what you were going to send, you know that the browser already has a copy and send a much smaller 304 (Not Modified) reply instead of the contents of the page again. And if you are clever about what information you include in an ETag, you can usually skip the most expensive database queries that would've gone into generating the page.
Minimize HTTP request size. Often cookies are set domain-wide, which means they are also unnecessarily sent by the browser with every image request from within that domain. What might've been a 400 byte request for an image could easily turn into 1000 bytes or more once you add the cookie headers. If you have a lot of uncached or uncacheable objects per page and big, domain-wide cookies, consider using a separate domain to host static content, and be sure to never set any cookies in it.
Minimize HTTP response size by enabling gzip compression for HTML and XML for browsers that support it. For example, the 17k document you are reading takes 90ms of the full downstream bandwidth of a user on 1.5Mbit DSL. Or it will take 37ms when compressed to 6.8k. That's 53ms off of the full page load time for a simple change. If your HTML is bigger and more redundant, you'll see an even greater improvement.
If you are brave, you could also try to figure out which set of browsers will handle compressed Javascript properly. (Hint: IE4 through IE6 asks for its javascript compressed, then breaks badly if you send it that way.) Or look into Javascript obfuscators that strip out whitespace, comments, etc and usually get it down to 1/3 to 1/2 its original size.
Consider locating your small objects (or a mirror or cache of them) closer to your users in terms of network latency. For larger sites with a global reach, either use a commercial Content Delivery Network, or add a colo within 50ms of 80% of your users and use one of the many available methods for routing user requests to your colo nearest them.
Regularly use your site from a realistic net connection. Convincing the web developers on my project to use a "slow proxy" that simulates bad DSL in New Zealand (768Kbit down, 128Kbit up, 250ms RTT, 1% packet loss) rather than the gig ethernet a few milliseconds from the servers in the U.S. was a huge win. We found and fixed a number of usability and functional problems very quickly.
To implement the slow proxy, I used the netem and HTB kernel modules available in the Linux 2.6 kernel, both of which are set up with the tc command line tool. These offer the most accurate simulation I could find, but are definitely not for the faint of heart. I've not used them, but supposedly Tamper Data for Firefox, Fiddler for Windows, and Charles for OSX can all rate-limit and are probably easier to set up, but they may not simulate latency properly.
Use Google's Load Time Analyzer extension for Firefox from a realistic net connection to see a graphical timeline of what it is doing during a page load. This shows where Firefox has to wait for one HTTP request to complete before starting the next one and how page load time increases with each object loaded. The Tamper Data extension can offer similar data in less easy to interpret form. And the Safari team offers a tip on a hidden feature in their browser that offers some timing data too.
Or if you are familiar with the HTTP protocol and TCP/IP at the packet level, you can watch what is going on using tcpdump, ngrep, or ethereal. These tools are indispensible for all sorts of network debugging.
Try benchmarking common pages on your site from a local network with ab, which comes with the Apache webserver. If your server is taking longer than 5 or 10 milliseconds to generate a page, you should make sure you have a good understanding of where it is spending its time.
If your latencies are high and your webserver process (or CGI if you are using that) is eating a lot of CPU during this test, it is often a result of using a scripting language that needs to recompile your scripts with every request. Software like eAccelerator for PHP, mod_perl for perl, mod_python for python, etc can cache your scripts in a compiled state, dramatically speeding up your site. Beyond that, look at finding a profiler for your language that can tell you where you are spending your CPU. If you fix that, your pages will load faster and you'll be able to handle more traffic with fewer machines.
If your site relies on doing a lot of database work or some other time-consuming task to generate the page, consider adding server-side caching of the slow operation. Most people start with writing a cache to local memory or local disk, but that starts to fall down if you expand to more than a few web server machines. Look into using memcached, which essentially creates an extremely fast shared cache that's the combined size of the spare RAM you give it off of all of your machines. It has clients available in most common languages.
(Optional) Petition browser vendors to turn on HTTP pipelining by default on new browsers. Doing so will remove some of the need for these tricks and make much of the web feel much faster for the average user. (Firefox has this disabled supposedly because some proxies, some load balancers, and some versions of IIS choke on pipelined requests. But Opera has found sufficient workarounds to enable pipelining by default. Why can't other browsers do similarly?)
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