There is much more to the web service than writing the code, and firing the server to crunch this code. But before you specify a set of questions that will lead you to the coverage of the whole mechanism and not just a few of its components, it is hard to know what issues are to be checked, what components are to be watched, and what software is to be monitored. The better questions you ask, the better coverage you should have.
Let's raise a few questions and look at some possible answers.
Q: How long does it take to process each request? What is the request distribution?
A: Obviously you will have more than one script and handler, and each one might be called in different modes; the amount of processing to be done may be different in every case. Therefore, you should attempt to benchmark your code, using all the modes in which it can be executed. It is good to learn the average case, as well as to learn the edges—the worst and best cases.
It is also very important to find out the distribution of different requests relative to the total number of requests. You might have only two handlers: one very slow and the other very fast. If you optimize for the average case without finding out the request distribution, you might end up under-optimizing your server, if in fact the slow request handler has a much higher call rate than the fast one. Or you might have your server over-optimized, if the slow handler is used much less frequently than the fast handler.
Remember that users can never be trusted not to do unexpected things such as uploading huge core dump files, messing with HTML forms, and supplying parameters and values you didn't consider. Which leads us to two things. First, it is not enough to test the code with automatic offline benchmarking, because chances are you will forget a few possible scenarios. You should try to log the requests and their execution times on the live server and watch the real picture. Secondly, after everything has been optimized, you should add a safety margin so your server won't be rendered unusable when heavily hit by the worst-case usage load.
Q: How many requests can the server process simultaneously?
A: The number of simultaneous requests you can handle is equal to the number of web server processes you can afford to run. This all translates to the amount of main memory (RAM) available to the web server. Note that we are not talking about the amount of RAM installed on your machine, since this number is misleading. Each machine is running many processes in addition to the web server processes. Most of these don't consume a lot of memory, but some do. It is possible that your web servers share the available RAM with big memory consumers such as SQL engines or proxy servers. The first step is to figure out what is the real amount of memory dedicated to your web server.
Q: How many simultaneous requests is the site expected to service? What is the expected request rate?
A: This question sounds similar to the previous one, but it is different in essence. You should know your server's abilities, but you also need to have a realistic estimate of the expected request rate.
Are you really expecting eight million hits per day? What is the expected peak load, and what kind of response time do you need to guarantee? Doing market research would probably help to identify the potential request rates, and the code you develop should be written in a scalable way, to allow you to add a few more machines to accommodate the possibility of rising demand.
Remember that whatever statistics you gathered during your last service analysis might change drastically when your site gains popularity. When you get a very high hit rate, in most cases the resource requirements grow exponentially, not linearly!
Also remember that whenever you apply code changes it is possible that the new code will be more resource-hungry than the previous code. The best case is when the new code requires fewer resources, but generally this is not the case.
If you machine runs the service perfectly well under normal loads, but the load is subject to occasional peaks—e.g., a product announcement or a special offer—it is possible to maintain performance without changing the web service at all. For example, some services can be switched off temporarily to cope with a peak. Also avoid running heavy, non-urgent processes (backups, cron jobs, etc.) during the peak times.
Q: Who are the users?
A: Just as it is important for a public speaker to know her audience in order to provide a successful presentation and deliver the right points, it is important to know who your users are and what can be expected from them.
If you are administering an Intranet web service (internal to a company, publicly inaccessible), you can tell what connection speed most of your users have, the number of possible users, and therefore the maximum request rate. You can be sure that the service will not gain a sudden popularity that will drive the demand rate up exponentially. Since there are a known number of users in your company, you know the expected limit. You can optimize the Intranet web service for high-speed connections, but don't forget that some users might connect to the Intranet with a slower dial-up connection. Also, you probably know at what hours your users will use the service (unless your company has branches all over the world, which requires 24-hour server availability) and can optimize service during those hours.
If you are administering an Internet web service, your knowledge of your audience is very limited. Depending on your target audience, it can be possible to learn about usage patterns and obtain some numerical estimates of the possible demands. You can either attempt to do the research by yourself or hire professionals to do this work for you. There are companies who release various survey reports available for purchase.
Once your service is running in the ideal way, know what to expect by keeping up with the server statistics. This will allow you to identify possible growth trends. Certainly, most web services cannot stand the so-called Slashdot Effect, which happens when some very popular news service (Slashdot, for instance) releases an exotic report on your service and suddenly all readers of this news service are trying to hit your site. The effect can be a double-edged sword: on one side you gain free advertising, but on the other side your server may not be able to withstand the suddenly increased load. If that's the case, most clients may not succeed in getting through.
Just as with the Intranet server, it is possible that your users are all located in a given time zone (e.g., for a particular country-specific service), in which case you know that hardly any users will be hitting your service in the early morning. The peak will probably occur during late evening and early night hours, and you can optimize your service during these times.
Q: How can we protect ourselves from the Slashdot Effect?
A: Use mod_throttle. mod_throttle allows you to limit the use of your server based on different metrics, configurable per vhost/location/file. For example, you can limit requests for the URL /old_content to a maximum of four connections per second. Using mod_throttle will help you prioritize different parts of your server, allowing smart use of limited bandwidth and limiting the effect of spikes.
Q: Does load balancing help in this area?
A: Yes. Load balancing, using mod_backhand, Cisco LocalDirector, or similar products, lets you wring the most performance out of your servers by spreading the load across a group of servers.
Q: How can we deal with the situation where we can afford only a limited amount of bandwidth but some of the service's content is large (e.g., streaming media or large files)?
A: mod_bandwidth is a module for the Apache web server that enables the setting of server-wide or per-connection bandwidth limits, based on the directory, size of files, and remote IP/domain.
Also see Akamai, which allows you to cache large content in regionally specific areas (e.g., east/west coast in the U.S.).
The given list of questions is in no way complete, and each specific project will have a different set of questions and answers. Some will be retained from project to project; others will be replaced by new ones. Remember that this is not a one-size-fits-all glove. While partial functionality can generally be optimized using the same method, you will have to go through this question-and-answer process each time from scratch if you want to achieve the best performance.
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