By Ping Li, in Gigaom.com
While when it comes to cloud computing, no one has entirely sorted out what's hype and what isn't, nor exactly how it will be used by the enterprise, what is becoming increasingly clear is that Big Data is the future of IT. To that end, tackling Big Data will determine the winners and losers in the next wave of cloud computing innovation.
Data is everywhere (be it from users, applications or machines) and as we get propelled into the "Exabyte Era" (PDF), is growing exponentially; no vertical or industry is being spared. The result is that IT organizations everywhere are being forced to grapple with storing, managing and extracting value from every piece of it -- as cheaply as possible. And so the race to cloud computing has begun.
This isn't the first time IT architectures have been reinvented in order to remain competitive. The shift from mainframe to client-server was fueled by disruptive innovation in computing horsepower that enabled distributed microprocessing environments. The subsequent shift to web applications/web services during the last decade was enabled by the open networking of applications and services through the Internet buildout. While cloud computing will leverage these prior waves of technology -- computing and networking -- it will also embrace deep innovations in storage/data management to tackle Big Data.
While when it comes to cloud computing, no one has entirely sorted out what's hype and what isn't, nor exactly how it will be used by the enterprise, what is becoming increasingly clear is that Big Data is the future of IT. To that end, tackling Big Data will determine the winners and losers in the next wave of cloud computing innovation.
Data is everywhere (be it from users, applications or machines) and as we get propelled into the "Exabyte Era" (PDF), is growing exponentially; no vertical or industry is being spared. The result is that IT organizations everywhere are being forced to grapple with storing, managing and extracting value from every piece of it -- as cheaply as possible. And so the race to cloud computing has begun.
This isn't the first time IT architectures have been reinvented in order to remain competitive. The shift from mainframe to client-server was fueled by disruptive innovation in computing horsepower that enabled distributed microprocessing environments. The subsequent shift to web applications/web services during the last decade was enabled by the open networking of applications and services through the Internet buildout. While cloud computing will leverage these prior waves of technology -- computing and networking -- it will also embrace deep innovations in storage/data management to tackle Big Data.
A Big Data stack
But as with prior data center platform shifts, a new "stack" (like mainframe and OSI) will also need to emerge before cloud computing will be broadly embraced by the enterprise. Basic platform capabilities, such as security, access control, application management, virtualization, systems management, provisioning, availability, etc. will have to be standard before IT organizations are able to adopt the cloud completely. In particular, this new cloud framework needs the ability to process data in increasingly real-time and greater orders of magnitude -- and do it at a fraction of what it would typically cost -- by leveraging commodity servers for storage and computing. Maybe cloud computing is all about creating a new "Big Data stack."
In many ways, this cloud stack has already been implemented, albeit in primitive form, at large-scale Internet data centers, which quickly encountered the scaling limitations of traditional SQL databases as the volume of data exploded. Instead, high-performance, scalable/distributed, object-orientated data stores are being developed internally and implemented at scale. At first, many solved this problem by sharding vast MySQL instances, in essence using them more as data stores than true relational databases (no complex table joins, etc.). As Internet data centers scaled, however, sharding MySQL obviously didn't.
Read full article at Gigaom.com
But as with prior data center platform shifts, a new "stack" (like mainframe and OSI) will also need to emerge before cloud computing will be broadly embraced by the enterprise. Basic platform capabilities, such as security, access control, application management, virtualization, systems management, provisioning, availability, etc. will have to be standard before IT organizations are able to adopt the cloud completely. In particular, this new cloud framework needs the ability to process data in increasingly real-time and greater orders of magnitude -- and do it at a fraction of what it would typically cost -- by leveraging commodity servers for storage and computing. Maybe cloud computing is all about creating a new "Big Data stack."
In many ways, this cloud stack has already been implemented, albeit in primitive form, at large-scale Internet data centers, which quickly encountered the scaling limitations of traditional SQL databases as the volume of data exploded. Instead, high-performance, scalable/distributed, object-orientated data stores are being developed internally and implemented at scale. At first, many solved this problem by sharding vast MySQL instances, in essence using them more as data stores than true relational databases (no complex table joins, etc.). As Internet data centers scaled, however, sharding MySQL obviously didn't.
Read full article at Gigaom.com
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