High Scalability Building bigger, faster, more reliable websites.

Misusing HTTP sessions is probably the number one obstacle to building scalable web sites today. Here are some tips how to consume HTTP sessions responsibly.

Recently, Google announced Google App Engine, another announcement in the rapidly growing world of cloud computing. This brings up some very serious questions:

1. If we want to take advantage of one of the clouds, are we doomed to be locked-in for life?
2. Must we re-write our existing applications to use the cloud?
3. Do we need to learn a brand new technology or language for the cloud?

This post presents a pattern that will enable us to abstract our application code from the underlying cloud provider infrastructure. This will enable us to easily migrate our EXISTING applications to cloud based environment thus avoiding the need for a complete re-write.

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.

This post covers two main options for scaling-out MySql and compare between them. The first is based on data-base clustering and the second is based on In Memory clustering a.k.a Data Grid. A special emphasis is given to a pattern which shows how to scale our existing data base without changing it through a combination of Data Grid and data base as a background service. This pattern is referred to as Persistency as a Service (PaaS). It also address many of the fequently asked question related to how performance, reliability and scalability is achieved with this pattern.

The Exceptional Performance group at Yahoo! has identified 14 best practices for making web pages faster. These best practices have proven to reduce response times of Yahoo! properties by 25-50%. They focus on the front-end, for example, why it's bad to use "@import" for including stylesheets and why ETags disable browser caching.

This google tech talk features these best practices and demonstrate YSlow.

Relevant links:
14 Rules for Exceptional Web Performance: http://developer.yahoo.com/performance/rules.html
YSlow: http://developer.yahoo.com/yslow/

Check out the book for details: High Performance Web Sites: Essential Knowledge for Front-End Engineers

Large scale distributed instant messaging, presence based protocol are a real challenge. With big players adopting the standard, the XMPP (eXtensible Messaging and Presence Protocol) community is facing the need to validate protocol and implementations to even larger scale.

GigaSpaces launched OpenSpaces.org, a community web site for developers who wish to utilize and contribute to the open source OpenSpaces development framework.

OpenSpaces extends the Spring Framework for enterprise Java development, and leverages the GigaSpaces eXtreme Application Platform (XAP) for data caching, messaging and as the container for application business logic. It is designed for building highly-available, scale-out applications in distributed environments, such as SOA, cloud computing, grids and commodity servers. OpenSpaces is widely used in a variety of industries, including financial services, telecommunications, manufacturing and retail -- and across the web in e-commerce, Web 2.0 applications such as social networking sites, search and more.

What is the future of EJB3 in the industry , given the current trends ?
There are a lot of arguments regarding EJB3 being heavy weighted .....
Also, what could be the alternatives of EJB3 ?
How about the scalability, persistence, performance and other factors ?

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

There is a lot of information in the blogosphere describing the architecture of many popular sites, such as Google, Amazon, eBay, LinkedIn, TypePad, WikiPedia and others.

I've summarized this issue in a blog post here

I would really appreciate your opinion on this matter.

Hi there,

what do you think is crucial in the code designing of a scalable site? How does one prepare for webfarms and clusters (e.g. in PHP)?

Thanks,
Stephan