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22 Apr, 2013
New Thinking and Best Practices for Scaling Big Data Storage
by Stefan Bernbo, Founder and CEO of Compuverde
Editor’s note: In this two part series the author discusses the impact of data storage on unified communications (UC) service providers. Part 1 (http://tinyurl.com/bsmx4vn) describes the background and need for a different solution and in part 2 he gives his recommendation. [caption id="" align="alignright" width="144"]
Stefan Bernbo
Founder and CEO of Compuverde[/caption] To achieve the best of all storage worlds, unified communications service providers must find the ideal combination of performance, scalability and cost-effectiveness – a trifecta. Below are three best practices to attain this: 1. Avoid bottlenecking A single point of entry can become a single point of failure by creating a performance bottleneck, especially with the demands of cloud computing on Big Data storage. Adding caches to mitigate the bottleneck, as most service providers presently do, increases cost and complexity in a system almost immediately. Alternatively, a horizontally-scalable system that distributes data among all nodes makes it possible to choose low-cost, lower-energy hardware. 2. Decentralize storage Despite the data center trend toward centralization, distributed storage presents the leading way to build at scale. There are now ways to upgrade performance at the software level that negate the performance benefit of a centralized data storage approach. 3. Use low-energy hardware Low-energy hardware can make good business sense. Commodity-component servers are not only economical, but they also use significantly less energy, which considerably reduces both setup and operating costs simultaneously. Conclusion The current Big Data storage architectures can only scale to a single petabyte and are expensive. They consist of high performance, vertically scaled storage systems that are not sustainable in the long run because of the performance limitations and costs. By following the best practices above, unified communications service providers can seamlessly move to a horizontally-scaled data storage model that evenly distributes data onto low-energy hardware. The new system will reduce costs while addressing the performance challenges of the current architectures. These steps to upgrade cloud storage will allow service providers to improve the performance, scalability and efficiency of their data centers. About the Author: Stefan Bernbo is the founder and CEO of Compuverde. For 20 years, Stefan has designed and built numerous enterprise scale data storage solutions designed to be cost effective for storing huge data sets. From 2004 to 2010 Stefan worked within this field for Storegate, the wide-reaching Internet based storage solution for consumer and business markets, with the highest possible availability and scalability requirements. Previously, Stefan has worked with system and software architecture on several projects with Swedish giant Ericsson, the world-leading provider of telecommunications equipment and services to mobile and fixed network operators.
by Stefan Bernbo, Founder and CEO of Compuverde
Editor’s note: In this two part series the author discusses the impact of data storage on unified communications (UC) service providers. Part 1 (http://tinyurl.com/bsmx4vn) describes the background and need for a different solution and in part 2 he gives his recommendation. [caption id="" align="alignright" width="144"]
Stefan Bernbo
Founder and CEO of Compuverde[/caption] To achieve the best of all storage worlds, unified communications service providers must find the ideal combination of performance, scalability and cost-effectiveness – a trifecta. Below are three best practices to attain this: 1. Avoid bottlenecking A single point of entry can become a single point of failure by creating a performance bottleneck, especially with the demands of cloud computing on Big Data storage. Adding caches to mitigate the bottleneck, as most service providers presently do, increases cost and complexity in a system almost immediately. Alternatively, a horizontally-scalable system that distributes data among all nodes makes it possible to choose low-cost, lower-energy hardware. 2. Decentralize storage Despite the data center trend toward centralization, distributed storage presents the leading way to build at scale. There are now ways to upgrade performance at the software level that negate the performance benefit of a centralized data storage approach. 3. Use low-energy hardware Low-energy hardware can make good business sense. Commodity-component servers are not only economical, but they also use significantly less energy, which considerably reduces both setup and operating costs simultaneously. Conclusion The current Big Data storage architectures can only scale to a single petabyte and are expensive. They consist of high performance, vertically scaled storage systems that are not sustainable in the long run because of the performance limitations and costs. By following the best practices above, unified communications service providers can seamlessly move to a horizontally-scaled data storage model that evenly distributes data onto low-energy hardware. The new system will reduce costs while addressing the performance challenges of the current architectures. These steps to upgrade cloud storage will allow service providers to improve the performance, scalability and efficiency of their data centers. About the Author: Stefan Bernbo is the founder and CEO of Compuverde. For 20 years, Stefan has designed and built numerous enterprise scale data storage solutions designed to be cost effective for storing huge data sets. From 2004 to 2010 Stefan worked within this field for Storegate, the wide-reaching Internet based storage solution for consumer and business markets, with the highest possible availability and scalability requirements. Previously, Stefan has worked with system and software architecture on several projects with Swedish giant Ericsson, the world-leading provider of telecommunications equipment and services to mobile and fixed network operators.
