Blog Archives

New Paper: The Post-Virtualization Refresh: Is Hyperconvergence the Answer?

Posted on February 25, 2016 by George Crump

With the move to virtualization well underway, the data center faces its most pivotal technology refresh in its history. The current architecture was designed before the introduction of virtualization, but virtualization has been adopted into that legacy architecture at an…

Tagged with: Cloud, Hyper-convergence, Hyperconvergence, Infrastructure, SAN, SimpliVity, Virtualization
Posted in Blog

Getting Software-Defined Storage Enterprise Ready

Posted on February 19, 2016 by George Crump

Briefing Note – Red Hat Storage Despite its potential to increase storage performance, capacity and flexibility while decreasing acquisition and operational costs, software-defined storage (SDS) has limited success in the enterprise. The problem is that enterprise data centers are “in…

Tagged with: Archive, Big data, Flexibility, Open Source, Red Hat, Scale-Out, SDS
Posted in Briefing Note

NAS vs. Object Storage – Why Legacy NAS isn’t keeping Pace

Posted on February 18, 2016 by George Crump

When it comes to managing unstructured data the data center has problems. The legacy network attached storage (NAS) systems that it uses to store this data are no longer keeping pace with the demands of the modern data center. As…

Tagged with: Caringo, Cloud, Data Protection, Metadata, NAS, Object Storage, RAID, Unstructured data, Web Object Scaler
Posted in Blog

Is the Three-Tier Architecture needed?

Posted on February 17, 2016 by George Crump

The traditional three-tier architecture – compute, networking and storage – has served IT well for decades. It was born in an era where the availability of these resources were in short supply and the cost to acquire them was very…

Tagged with: Cloud, Hyperconvergence, Infrastructure, SAN, SimpliVity, Virtualization, VM
Posted in Blog

Webinar: Improving Time to Value for Enterprise Big Data Analytics

Posted on February 16, 2016 by George Crump

Embracing and taking full advantage of big data analytics can provide tremendous returns to organizations willing to invest. The problem is that while we understand the value of analytics, how to get started is confusing. Most big data analytic projects…

Tagged with: Analytics, Big data, Brocade, HDS, Hyper-converged
Posted in Webinar

Webinar: NAS vs. Object Storage: 10 Reasons Why Object Storage Will Win

Posted on February 11, 2016 by George Crump

Network Attached Storage (NAS) systems and file servers were the foundation of collaboration in the 90’s. These storage systems primarily served the needs of users that needed to share files for projects. In the 2000’s NAS systems found a lease…

Tagged with: Caringo, File server, NAS, Object Storage, Unstructured data, Virtualization
Posted in Webinar

Filling the Provider Backup Gateway Gap

Posted on February 9, 2016 by George Crump

Artisan Infrastructure Briefing Note Artisan Infrastructure is a leading cloud infrastructure, management, and business continuity solutions provider. Its solutions enable cloud and hosting providers to migrate, manage and deliver continuously available cloud applications for their customers and suppliers. Artisan provides…

Tagged with: Artisan Infrastructure, Backup, Cloud, CSP, Deduplication, Infrastructure, LAN, MSP, Object Storage, VM
Posted in Briefing Note

Addressing VDI’s Fork in The Road

Posted on February 4, 2016 by George Crump

Organizations embark on Virtual Desktop Infrastructure (VDI) projects to drive down end-user operational costs and to enhance infrastructure security. These projects often evaluate well. During “test mode” there are a limited number of users, making it easy to meet their…

Tagged with: AFA, All-Flash, Caching, Cloudistics, Hard disk, I/O, NAS, Performance Sprawl, VDI, Virtualization
Posted in Article

Hitachi’s HSP Hyper-Converged Appliance makes Big Data Analytics fit the Enterprise

Posted on February 3, 2016 by George Crump

Big Data Analytics uses distributed computing architectures, on platforms like Hadoop, to run large processing jobs on even larger datasets. Since data being processed in a Hadoop environment usually needs to be resident on the compute nodes themselves, this can…