Monday, April 20, 2009 at 5:14AM Memcached is generally treated as a black box. But what if you really need to know what's in there? Not for runtime purposes, but for optimization and capacity planning?
Read more on Evan Weaver, a software developer working for Twitter (a contributor for Rails core and Mongrel).
Friday, January 16, 2009 at 6:54AM The most important aspect of a scalable web architecture is data partitioning. Most components in a modern data center are completely stateless, meaning they just do batches of work that is handed to them, but don't store any data long-term. This is true of most web application servers, caches like memcached, and all of the network infrastructure that connects them. Data storage is becoming a specialized function, delegated most often to relational databases. This makes sense, because stateless servers are easiest to scale - you just keep adding more. Since they don't store anything, failures are easy to handle too - just take it out of rotation.
Stateful servers require more careful attention. If you are storing all of your data in a relational database, and the load on that database exceeds its capacity, there is no automatic solution that allows you to simply add more hardware and scale up. (One day, there will be, but that's for another post). In the meantime, most websites are building their own scalable clusters using sharding.
Read more on LessonLearned blog.
Friday, January 16, 2009 at 4:07AM In this article Jeff Atwood (a rockstar programmer and one of StackOverflow website founders) discusses the measures of how you can reduce you bandwidth usage and refers specifically on high trafficked websites for which bandwidth is more costly than for an average website.
This is his experience and you can read more on his post on CodingHorror.com.
Monday, October 27, 2008 at 8:16PM Summary
In this presentation, a three steps approach for turning your existing stateful tier-based/Spring-application into a dynamically scalable services application using OpenSpaces is demonstrated. The existing programming model is kept the same while focusing on abstracting and replacing the underlying implementations of the middleware stack in a way that will fit the scale-out model.
Bio
Nati Shalom is the CTO and Founder of GigaSpaces and responsible for the technology roadmap. He has 10 years of experience with distributed technology and architecture namely CORBA, Jini, J2EE, Grid and SOA. Nati is the Head of the Israeli Grid consortium and an evangelist of Space Based Architecture and Data Grid patterns. Blog: Gigaspaces Blog
Read the rest of the article here on InfoQ.
Wednesday, October 22, 2008 at 6:42AM At eBay, one of the primary architectural forces we contend with every day is scalability. It colors and drives every architectural and design decision we make. With hundreds of millions of users worldwide, over two billion page views a day, and petabytes of data in our systems, this is not a choice - it is a necessity.
In a scalable architecture, resource usage should increase linearly (or better) with load, where load may be measured in user traffic, data volume, etc. Where performance is about the resource usage associated with a single unit of work, scalability is about how resource usage changes as units of work grow in number or size. Said another way, scalability is the shape of the price-performance curve, as opposed to its value at one point in that curve.
There are many facets to scalability - transactional, operational, development effort. In this article, I will outline several of the key best practices we have learned over time to scale the transactional throughput of a web-based system. Most of these best practices will be familiar to you. Some may not. All come from the collective experience of the people who develop and operate the eBay site.
Read the rest of the article on InfoQ.
Wednesday, October 22, 2008 at 6:38AM The transport-level server load balancing architectures described in the first half of this article are more than adequate for many Web sites, but more complex and dynamic sites can't depend on them. Applications that rely on cache or session data must be able to handle a sequence of requests from the same client accurately and efficiently, without failing. In this follow up to his introduction to server load balancing, Gregor Roth discusses various application-level load balancing architectures, helping you decide which one will best meet the business requirements of your Web site.
The first half of this article describes transport-level server load balancing solutions, such as TCP/IP-based load balancers, and analyzes their benefits and disadvantages. Load balancing on the TCP/IP level spreads incoming TCP connections over the real servers in a server farm. It is sufficient in most cases, especially for static Web sites. However, support for dynamic Web sites often requires higher-level load balancing techniques. For instance, if the server-side application must deal with caching or application session data, effective support for client affinity becomes an important consideration.
Here in Part 2, I'll discuss techniques for implementing server load balancing at the application level to address the needs of many dynamic Web sites.
Read the rest of the article on JavaWorld.
Wednesday, October 22, 2008 at 6:34AM Server farms achieve high scalability and high availability through server load balancing, a technique that makes the server farm appear to clients as a single server. In this two-part article, Gregor Roth explores server load balancing architectures, with a focus on open source solutions. Part 1 covers server load balancing basics and discusses the pros and cons of transport-level server load balancing.
The barrier to entry for many Internet companies is low. Anyone with a good idea can develop a small application, purchase a domain name, and set up a few PC-based servers to handle incoming traffic. The initial investment is small, so the start-up risk is minimal. But a successful low-cost infrastructure can become a serious problem quickly. A single server that handles all the incoming requests may not have the capacity to handle high traffic volumes once the business becomes popular. In such a situations companies often start to scale up: they upgrade the existing infrastructure by buying a larger box with more processors or add more memory to run the applications.
Read the rest of the article on JavaWorld.
Wednesday, October 15, 2008 at 8:05AM A group of top Silicon Valley engineers (ex-Yahoo, Facebook, Google) have come together to launch a new startup called Cloudera.
Not yet launched, it intends to help other companies adopt a promising software platform called Hadoop.
Hadoop is an open-source software project (written in Java) designed to let developers write and run applications that process huge amounts of data. While it could potentially improve a wide range of other software, the ecosystem supporting its implementation is still developing. Which is where Cloudera hopes to make a place for itself.
More on Hadoop: It uses the Google-introduced MapReduce systems framework that divides applications into small blocks of work, creating multiple replicas of data blocks that it places on various computer nodes.
It is already in use at large companies like Yahoo.
Read more about Cloudera here.
Wednesday, October 15, 2008 at 7:51AM This article explains how Outside.in, the local social network and aggregator, scaled up its service and moved from PHP to Ruby on Rails (they moved maybe because Ruby code seemed to be more maintanable that PHP code?).
The whole article is here on EngineYard blog.
Monday, October 13, 2008 at 2:08AM 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 up your servers to take full advantage of new hardware capabilities.
* 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.
