High Scalability Building bigger, faster, more reliable websites.

This is an interesting and still relevant research paper by Jim Gray, Prashant Shenoy at Microsoft Research that examines the rules of thumb for the design of data storage systems. It looks at storage, processing, and networking costs, ratios, and trends with a particular focus on performance and price/performance.

Jim Gray has an updated presentation on this interesting topic: Long Term Storage Trends and You. Robin Harris has a great post that reflects on the Rules of Thumb whitepaper on his StorageMojo blog: Architecting the Internet Data Center - Parts I-IV.

With the explosive growth of the Internet, increasing complexity of user requirements, and wide choice of hardware, operating systems, and middleware, IT executives are facing new challenges in their application infrastructures. Rapid expansion of the application tier has resulted in significant cost and complexity, and many organizations are simply running out of datacenter space, power, and cooling.

Microsoft SQL Server 2008 incorporates the tools and technologies that are necessary to implement relational databases, reporting systems, and data warehouses of enterprise scale, and provides optimal performance and responsiveness.
With SQL Server 2008, you can take advantage of the latest hardware technologies while scaling up your servers to support server consolidation. SQL Server 2008 also enables you to scale out your largest data solutions.

This white paper describes the performance and scalability capabilities of Microsoft® SQL Server® 2008 and explains how you can use these capabilities to:

* Optimize performance for any size of database with the tools and features that are available for the database engine, analysis services, reporting services, and integration services.

* Scale out your database environment to optimize responsiveness and to move your data closer to your users.

Read the entire article about SQL Server 2008 Database Performance and Scalability at MyTestBox.com - web software reviews, news, tips & tricks.

An unstated assumption is that clouds are scalable. But are they? Stick thousands upon thousands of machines together and there are a lot of potential bottlenecks just waiting to choke off your scalability supply. And if the cloud is scalable what are the chances that your application is really linearly scalable? At 10 machines all may be well. Even at 50 machines the seas look calm. But at 100, 200, or 500 machines all hell might break loose. How do you know?

You know through real life testing. These kinds of tests are brutally hard and complicated. who wants to do all the incredibly precise and difficult work of producing cloud scalability tests? GridDynamics has stepped up to the challenge and has just released their Cloud Performance Reports.

The report is quite detailed so I'll just cover what I found most interesting. GridDynamics in this report test three configurations:

80-90% of the end-user response time is spent on the frontend, so it makes sense to concentrate efforts there before heroically rewriting the backend. Take a shower before buying a Porsche, if you know what I mean. Steve Souders, author of High Performance Websites and Yslow, has ten more best practices to speed up your website:

What have bunch of applications which run on Debian servers, which processes huge amount of data stored in a shared NFS drive.

we have 3 applications working as a pipeline, which process data stored in the NFS drive. The first application processes the data and store the output in some folder in the NFS drive, the second app in the pipeline process the data from the previous step and so on.

The data load to the pipeline is like 1 GBytes per minute. I think the NFS drive is the bottleneck here.

Would buying a specialized file server improve the performance of data read write from the disk ?

It is fairly obvious that web site performance can be increased by making the code run faster and optimising the response time. But that only scales up to a point. To really take our web sites to the next level, we need to look at the performance problem from a different angle.

Update: Nice explanation in The importance of bandwidth versus latency of how long latencies cause cascading delays in resource loading. Doloto tries to optimize how resources are loaded.

Twenty new rules have been added to the original 14 rules for sizzling web performance. Part of scalability is worrying about performance too. The front-end is where 80-90% of end-user response time is spent and following these best practices improved the performance of Yahoo! properties by 25-50%. The rules are divided into server, content, cookie, JavaScript, CSS, images, and mobile categories. The new rules are:

Cal Henderson writes at thinkvitamin.com: "With our so-called "Web 2.0' applications and their rich content and interaction, we expect our applications to increasingly make use of CSS and JavaScript. To make sure these applications are nice and snappy to use, we need to optimize the size and nature of content required to render the page, making sure we’re delivering the optimum experience. In practice, this means a combination of making our content as small and fast to download as possible, while avoiding unnecessarily refetching unmodified resources." A lot of good comments too.

This is what Mike Peters says he can do: make your site run 10 times faster. His test bed is "half a dozen servers parsing 200,000 pages per hour over 40 IP addresses, 24 hours a day." Before optimization CPU spiked to 90% with 50 concurrent connections. After optimization each machine "was effectively handling 500 concurrent connections per second with CPU at 8% and no degradation in performance."

Mike identifies six major bottlenecks:

In The Architectures You've Always Wondered About track at the Qcon conference, Second Life, eBay, Yahoo, LinkedIn and Orbitz presented how they dealt with different aspects of their applications, such as scalability. There were quite a few lessons that I learned that day that I thought were worth sharing.

The details are provided below:

Lessons from Yahoo, eBay, Orbitz, LinkedIn architecture

Cacti is a network statistics graphing tool designed as a frontend to RRDtool's data storage and graphing functionality. It is intended to be intuitive and easy to use, as well as robust and scalable. It is generally used to graph time-series data like CPU load and bandwidth use.

The frontend is written in PHP; it can handle multiple users, each with their own graph sets, so it is sometimes used by web hosting providers (especially dedicated server, virtual private server, and colocation providers) to display bandwidth statistics for their customers. It can be used to configure the data collection itself, allowing certain setups to be monitored without any manual configuration of RRDtool.

Update: Speed up Apache - how I went from F to A in YSlow. Good example of using YSlow to speed up a website with solid code examples.

Every layer in the multi-layer cake that is your website contributes to how long a page takes to display. YSlow, from Yahoo, is a cool tool for discovering how the ingredients of your site's top layer contribute to performance.