Large-Scale Web Site Infrastructure and Drupal
When Twitter experiences an outage, users see the infamous “fail whale” error message, an illustration of twit-birds struggling to hoist a sleeping cartoon whale into the air along with the words “Too many tweets! Please wait a moment and try again.” It happens so often, Twitter has a much-heralded illustration for it. Not too long ago, many readers may remember Facebook going down for days at a time. True, those sites are dealing with extraordinary levels of traffic, but smaller sites often face the same problems. How come? First, Web sites are no longer a collection of static pages. Nowadays, Web sites combine social-networking features with highly customized content for individual users, meaning most pages have to be assembled on the fly. Second, content is changing—rich media, on-line advertising, video, telephony. There's more than text forcing its way through the pipe, and network traffic only continues to grow. Addressing this tandem of complexity and load is the bane of many growing social-media Web sites' existence. What follows are some clever ways to address this whale of a problem.
Surprisingly, the solutions to most scaling problems are frequently the same, regardless of the technology upon which the site was built. Lullabot (the parent company of this article's authors) is a Drupal development company, meaning that most of our experience is centered around the typical LAMP stack (Linux, Apache, MySQL and PHP), although most techniques are universal, and some of the most advanced performance software is platform-neutral.
One of the main factors in scaling a Web site is, of course, the hardware (Figure 1). System administrators always can throw more hardware at a problem and solve it at least temporarily, if they have the resources to do so. Quite a few services can be put in place before this needs to be done, and developers can selectively optimize the application by reducing or optimizing queries. Nevertheless, when it comes to sheer numbers of users and bandwidth over a short amount of time, there almost always comes a point where it's necessary to include hardware in the mix. That's why it is important to have your hardware infrastructure planned in a way that it rapidly can scale upward on a traffic spike, and back down when your traffic recedes.
A typical setup, whether virtual or dedicated, usually includes multiple Web servers, multiple database servers and sometimes even separate caching servers, all behind a load balancer that distributes traffic between machines. Depending on its processor speed and the amount of available memory, a Web server or database often can double as the caching server, because caching services usually require less resources than Apache or MySQL.
Although distributing traffic across multiple Web servers, or Web heads, can be a quick win, it can introduce problems with managing file uploads. If requests are being distributed round-robin by the load balancer, a user may upload a file on one server but then be switched to a different Web server after the upload, which doesn't have the newly uploaded file. To solve this problem, a file server also is added into the mix. The file server is usually some form of NAS (Network Attached Storage) or an NFS (Network File System) mount that allows the application to share files between machines. Each Web head will have a copy of the application stored in the Web root, but when it comes to the files that are uploaded or changed often by the users of the application, an NFS mount connects all the servers to a shared file location.
The other main factor in scaling a Web site is, of course, the software (Figure 2). To scale effectively, high-traffic Web sites require some flavor or flavors of caching. Caching mechanisms are not mutually exclusive, and most high-profile sites combine several. Most types of caching seek to reduce the amount of disk access necessary to render a page or compile higher-level languages into bytecode so they're faster to run—the closer to machine language the better.
APC (Alternative PHP Cache) and other opcode caches save the Web server from having to read, parse and compile PHP files on every request. APC is a free, open-source opcode cache and is pretty much the standard. It will come built in with PHP 6, but there are many different ones that perform differently.
Modern content management systems, like Drupal, can make a plethora of database calls on every page request. Because calls to the database hit the disk, it is often a bottleneck. Memcached is a service that allows entire database tables to be stored in memory, dramatically speeding up queries to those tables and alleviating strain on the database. It behaves as though it were a giant hash table and serves this data out of memory. Memcached is free, open source and in use by a ton of high-traffic sites. Memcached is installed alongside MySQL on the database server in most typical setups. However, the database server needs to have a lot of RAM available if Memcached and MySQL are sharing this critical resource. There are occasions when Memcached is actually placed on its own server, completely decoupled from the database server, which precludes Memcached from using too much of the database server's memory.
Varnish is an excellent high-performance, HTTP accelerator. The technical term for Varnish is a “reverse proxy cache”, meaning that it handles the requests when you visit a Web site. If Apache were a physician, Varnish would be the triage nurse. After each anonymous page request is made, Varnish makes a copy of the page in an ultra-fast storage so that the next time the page is requested, it returns it immediately, circumventing a bootstrap of Apache, PHP, MySQL, Memcached or any other technologies your Web site may require to serve pages. If Varnish doesn't have a copy of the file or page being requested, it will send the request on to Apache. And, it's really a huge win if you're going to be serving static content.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
This ebook takes a look at some of the practical applications of the Linux on Power platform and ways you might bring all the performance power of this open architecture to bear for your organization. There are no smoke and mirrors here—just hard, cold, empirical evidence provided by independent sources. I also consider some innovative ways Linux on Power will be used in the future.Get the Guide