UPDATED 16:30 EDT / APRIL 08 2019

INFRA

IBM’s multicloud storage refresh puts data all over the place

Companies are increasingly spread out across distributed information technology environments. Different applications dispersed across multicloud computing structures may require storage with multiple personalities to optimize performance and operations … and manage cost.

“It’s not the fancy windows; it’s not the fancy paint. But if that foundation isn’t right, what happens? The whole building falls down,” said Eric Herzog (pictured), chief marketing officer and vice president of worldwide storage channels at IBM storage systems and software-defined infrastructure.

Most companies are adopting multicloud strategies. This means they have multiple types of workloads — legacy, monolithic, cloud-native and microservices-based, to name a few. They may run in on-premises data centers, virtualized environments, or in public cloud. One storage type might provide that solid foundation in one environment but not another.

A storage misfit could result in poor application performance and overspending. IBM has refreshed its broad storage portfolio to meet the needs of workloads on-prem, in the cloud, and everywhere in between.

In a two-part video series, Herzog spoke with Peter Burris, host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at theCUBE’s studio in Palo Alto, California. They discussed the storage needs of today’s diverse workloads and IBM’s latest enhancements to its storage portfolio (watch complete video interviews with transcripts here and here). (* Disclosure below.)

Watch Herzog’s first interview with theCUBE below:

To cloud or not to cloud? A cost question

When profiling data for a good storage fit, companies need to look at performance needs, cost, security and usage. Data that is going to move around a lot may cost a company a bundle if they put it in the cloud, according to Herzog.

“Going to a public cloud provider, which charge both for in and out of the data, that actually may cost more than buying an array on-prem,” he said. 

However, many companies may not want any dataset to be permanently bound on-prem. IBM has made compatibility with all cloud providers a main goal of its storage refresh. Its cloud tiering allows users to tier their on-prem storage arrays to their cloud instances.

We can tier to the cloud. We can backup to the cloud. With object storage, we can place [data] in the cloud. We’ve made the cloud, if you will, a seamless tier to the storage infrastructure for our customers,” he said. 

Watch Herzog’s second interview with theCUBE below:

Data flies round trip to cloud and back

Also in the bang-for-your-buck category are IBM’s new non-volatile memory express offerings. Its Storwize portfolio now includes the V7000, V5100, and other models with NVMe both inside the array and support for NVMe over fabric.

“These solutions all deliver dramatic performance gains but incredible price discounts as well,” Herzog said. “For example, the 5010E is not only twice as fast as the older 5010, but it happens to be up to 25% less expensive,” he said. The V7000 and V5100 bring NVMe to market at a much lower price than competitors offer, he added. 

Storewize arrays also come with award-winning Spectrum Virtualize software that offers enterprise-class data services. These include snapshot, replication, data-at-rest encryption, transparent tiering to cloud, migration, etc.

Another recent addition is Spectrum Virtualize for Public Cloud. It sits in a VMware Inc. virtualized instantiation out at the public cloud provider, giving enterprise-class functionalities. It allows data to migrate or replicate between heterogeneous on-prem storage systems and IBM Cloud or Amazon Web Services Inc. IBM plans to extend it to more clouds in the future. 

Be sure to check out more of SiliconANGLE’s and theCUBE’s CUBE Conversations.  (* Disclosure: IBM Corp. sponsored this segment of theCUBE. Neither IBM nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
Photo: SiliconANGLE

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