Karthik Ranganathan, Member of Technical Staff for Nutanix, takes a seat inside theCUBE at Hadoop 2013, along with John Furrier of SiliconAngle and Dave Vellante of Wikibon, to discuss the advantages and benefits to the enterprise of converged infrastructure for Hadoop.
Asked about the differences between the hyperscale market and the enterprise, and how Nutanix addressed it, Ranganathan said that "the idea is that's a device, that encompasses all your performance needs at the ratio you need so that you can configure a distributed cluster," allowing companies to grow as needed. "The magic sauce is a continuum over time," he added, "you see new use cases, you adapt, you see more data, you scale out."
DevOps: Know your own scale
John Furrier pointed out that companies look at what Facebook has done with DevOps as a modern way to deploy quickly and scale out and asked what is the mindset of these businesses, and how they should address Hadoop. Ranganathan said that "the most important thing I feel is understanding your own scale. If you're going to build something that will scale," scale should be at the core right from the start.
Performance is next, but "as long as the fundamental architecture will scale, that's the first step," Ranganathan says. The second step is to make sure you have manageability. Will the system fix itself? What to do when something fails? "Performance is ongoing, but try to build upfront for scalability and manageability."
Initially, such a way of thinking might be a shock, but slowly, while working through the mindset and talking to companies, "people usually turn and try and play with the software," Ranganathan says, then they begin to understand and ask questions. People usually see the benefits of scale out and distributed architectures.
Why converged infrastructure works for Hadoop in the enterprise
Asked why converged infrastructure for Hadoop was a good choice, Ranganathan said that in the typical enterprise, there are two potential scenarios -- either they are trying to figure out their Big Data needs and how to put it to good use, or they have a bunch of data, and are trying to get some meaning out of it.
The alternative to converged infrastructures would be determining what hardware they need, getting a team to implement and manage it, all becoming a rather complicated and consuming process. With convergence, you don't give up much performance, "but the big story is the manageability aspect," says Ranganathan. When you run Hadooop in a virtual machine, your admins know how to run it, as they are already familiar with virtualization.
Asked why he specifically chose Nutanix after having worked at Facebook, Ranganathan said "they're bringing all the principles that I was passionate about at Facebook to the enterprise," the distributed system, the failure management, the scale out.
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Karthik Ranganathan, Member of Technical Staff for Nutanix, takes a seat inside theCUBE at Hadoop 2013, along with John Furrier of SiliconAngle and Dave Vellante of Wikibon, to discuss the advantages and benefits to the enterprise of converged infrastructure for Hadoop.
Asked about the differences between the hyperscale market and the enterprise, and how Nutanix addressed it, Ranganathan said that "the idea is that's a device, that encompasses all your performance needs at the ratio you need so that you can configure a distributed cluster," allowing companies to grow as needed. "The magic sauce is a continuum over time," he added, "you see new use cases, you adapt, you see more data, you scale out."
DevOps: Know your own scale
John Furrier pointed out that companies look at what Facebook has done with DevOps as a modern way to deploy quickly and scale out and asked what is the mindset of these businesses, and how they should address Hadoop. Ranganathan said that "the most important thing I feel is understanding your own scale. If you're going to build something that will scale," scale should be at the core right from the start.
Performance is next, but "as long as the fundamental architecture will scale, that's the first step," Ranganathan says. The second step is to make sure you have manageability. Will the system fix itself? What to do when something fails? "Performance is ongoing, but try to build upfront for scalability and manageability."
Initially, such a way of thinking might be a shock, but slowly, while working through the mindset and talking to companies, "people usually turn and try and play with the software," Ranganathan says, then they begin to understand and ask questions. People usually see the benefits of scale out and distributed architectures.
Why converged infrastructure works for Hadoop in the enterprise
Asked why converged infrastructure for Hadoop was a good choice, Ranganathan said that in the typical enterprise, there are two potential scenarios -- either they are trying to figure out their Big Data needs and how to put it to good use, or they have a bunch of data, and are trying to get some meaning out of it.
The alternative to converged infrastructures would be determining what hardware they need, getting a team to implement and manage it, all becoming a rather complicated and consuming process. With convergence, you don't give up much performance, "but the big story is the manageability aspect," says Ranganathan. When you run Hadooop in a virtual machine, your admins know how to run it, as they are already familiar with virtualization.
Asked why he specifically chose Nutanix after having worked at Facebook, Ranganathan said "they're bringing all the principles that I was passionate about at Facebook to the enterprise," the distributed system, the failure management, the scale out.
