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Big data workloads live on-premises
Seven years after its birth, the frenzy around cloud is beginning to subside. IT organizations have embraced public cloud for some workloads, and built private clouds for others.
IT is having productive discussions about which applications to leave where they are, and which applications to re-platform. They're considering the pros and cons of renting shared infrastructure rather than buying dedicated on-premises resources.
You may not get the raw performance from a virtualized cloud instance that you could from dedicated bare-metal hardware -- you need to weigh that against the cost of hiring data center operations staff.
Meanwhile, the hype around big data and social media has just begun. The technology for doing this kind of analytics exists today. You can build a Hadoop-based repository to store the untold amounts of raw data that can later be used to discover unimagined relationships and patterns. It all sounds very promising, but for now, the jury's still out about the value of these initiatives.
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Features in this issue
Compute- and I/O-intensive big data workloads won't stray to the cloud yet as security and existing infrastructure keep analytics in the data center.
Enterprise big data workloads demand a lot from storage and network bandwidth. Storage, cloud and as-a-service vendors are developing the infrastructure to support them.
The future of hard disks grows bleaker by the day, with giant SSD storage densities, outdated RAID algorithms and faster interconnects ushering in flash domination.
First we had data. Then we had big data. Now we have data lakes. Will the murky depths prove bountiful?
While VMware is the reigning private cloud king, performance and costs issues are driving some enterprise users into the arms of OpenStack.
Despite backing from major industry players like IBM and HP, OpenStack hasn't met expectations. So what's holding it back?
Columns in this issue
The third platform is a broad term for social, mobile, cloud and other applications, united in the need for a scalable IT back end.
Desktop virtualization vendors don't need to be able to manage images or provisioning anymore because shops can take care of that on their own. Vendors just need to focus on managing users and apps.