Yahoo today debuted an open source version of Traffic Server, a high performance application server for builders of cloud services.
Traffic Server enables the session management, authentication, configuration management, load balancing, and routing for an entire cloud computing stack. Yahoo has donated the Traffic Server code to The Apache Software Foundation through the Apache Incubator, and intends to build a community of developers around the open source Traffic Server. Shelton Shugar, senior vice president of Cloud Computing at Yahoo!, will be discussing the new technology tomorrow at the Cloud Computing Expo.
"We see Traffic Server as an essential building block for cloud computing, and at Yahoo, it's integral to our edge services, on-line storage and cloud serving. The open-sourcing of Traffic Server is representative of our company-wide commitment to sharing technology innovation with the open source community, as well as our broader intention to continue to open source our cloud technologies as they mature," said Shugar. "By releasing an open source version of Traffic Server, we are sharing a core piece of technology with the open-source world, while also signaling our intention to build a community of developers to take it to the next level."
With the open source version of Traffic Server, organizations can benefit from fast and scalable access to cached online content. In addition, Traffic Server enables speeded responses to requests for stored Web objects, such as files, news articles or images, reducing bandwidth usage and costs.
The low-latency, extensible framework of Traffic Server makes it ideal for delivering Web traffic at high rates, and its "plug-in" architecture makes it customizable to fit different system needs.
Yahoo is also announcing an update to the Yahoo Distribution of Hadoop, now deployed in Yahoo data centers worldwide. Since the initial Yahoo Distribution of Hadoop was announced in June 2009, Yahoo has published multiple updates to the code. These include new features and bug fixes that continue to improve robustness, security, performance, and operability of Hadoop for ongoing large scale deployments.