Hyperscale Computing Driving Small-Scale Designs 大規模計算機運算正朝向小規模的設計邁進

http://cloudcomputing.sys-con.com/node/2191762 Cloud Expo: Article Hyperscale Computing Driving Small-Scale Designs Are mid-scale offerings soon to be obsolete?

BY LEE THOMPSON ARTICLE RATING: Select ratingGive it 1/5Give it 2/5Give it 3/5Give it 4/5Give it 5/5 GIVE IT 1/5 GIVE IT 2/5 GIVE IT 3/5 GIVE IT 4/5 GIVE IT 5/5 MARCH 5, 2012 11:27 AM EST READS: 477 Multi-million user social networks, cloud hosting, Internet search and Big Data problems such as meteorology, complex physics and business informatics, all share one basic need - they each require incredibly large, complex and varied computer platforms. However, a common requirement across these systems is to "optimize the unit cost of computing." At this degree of hyperscale computing, the network, system, software, facility, and maintenance all add up to 10s or 100s of millions of dollars per project, and optimizations of a single element or the coordination of multiple elements can save the business millions. A good example of this holistic approach is Facebook's OpenCompute project, which saved the company 38% in efficiency and costs 24% less in build expense. Similar to the automobile industry, where the racing technology from Indy, F1, and NASCAR end up in passenger vehicles, the hyperscale compute innovations we're seeing in juggernauts like Facebook will end up as line-item part numbers from vendors that are available to everyone. The timing couldn't be better, as solid state hard drives are becoming affordable and most enterprises are ramping up private cloud initiatives within their firms. In a hyperscale design, premium computing constructs (like those seen in blade systems) are normally abandoned, favoring stripped down commodity designs that do the job at a fraction of the price. Because of the size of the deployment, rewriting an application to take advantage of the commodity compute fabric, or moving a task that was done in purpose-built hardware into custom software (e.g., disaster fault recovery), becomes cost-effective. Essentially, the decreased investment in hardware funds the software investments with ease. So what design elements are being abandoned in favor of hyperscale computing? An example of the complex monolithic system that is being abandoned Premium storage array networks with expensive optical connectivity and recovery features are being replaced with a mix of locally attached and network-attached storage, eliminating the heavy burden on the storage network Dedicated compute, manage and storage networks are being replaced, favoring virtual LANs that reduce cabling and network costs High cost per port network switching is being replaced, favoring commodity network components High cost per socket blade systems are being replaced, favoring commodity compute components Devices for monitoring and management are being replaced, favoring software tools and thoughtfully architected applications Hot-swappable devices for high availability are being replaced, favoring streamlined hardware configuration Redundant power supplies are being eliminated The best visualization for this kind of unit cost of computing design is the Google Platformfrom 1998 that integrated individual parts without the purchase of machine cases. Previously, creating the best optimized hyperscale compute fabric meant that a full staff of hardware/network/applications/systems/facilities engineers was needed to drive out the costs. Today, there are firms that are using hyperscale designs to create private cloud solutions affordable for small to medium-sized business markets or for business units in large firms. Companies working in this space aim to create the highest performance per IOP private cloud solution, delivering highly scalable infrastructure solutions.