Managing critical data pipelines across a hybrid computing environment, from on-premises to edge, is one of the biggest challenges modern businesses face. Cobbling together solutions creates problems with application lock-in, accessing data, and — most critical — the ability to apply artificial intelligence and machine learning to gain value from the data.

Riding in to help solve these problems is Hewlett Packard Enterprise Co.’s Ezmeral edge-to-cloud software portfolio.

“The idea here is to give [the customer] a platform by which they can bridge both the public and private environment for when they’re doing application development, specifically in the data side,” said Robert Christiansen (pictured, right), vice president of strategy, office of the chief technical officer, at HPE. “Nobody brings together the silicon, the hardware, the platform, and all of that stack together where it can combine like Ezmeral does.”

Christiansen and Kumar Sreekanti (pictured, left), chief technology officer and head of software at HPE, spoke with Dave Vellante, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during the HPE Ezmeral\\Analytics Unleashed event. They discussed the impact of HPE Ezmeral to the data workflow of enterprise customers. (* Disclosure below.)

Speed and efficiency without lock-in

Ezmeral can bring up to “90, 92, 93% utilization out of AI/ML workloads,” according to Christiansen, who spoke about the platform’s competitive advantage over a public cloud offering.

Along with fulfilling the customer’s need for reduced costs and increased performance, Ezmeral brings three fundamental benefits, Christiansen added. The first is the ability to maintain an open architecture, with low or no application lock-in. Number two is the ability to access data regardless of location via a data fabric or a data mesh. The third perk is the ability to harness the power of data through artificial intelligence and machine learning.

“We are bringing compute or cloud to the data [rather] than taking the data to the cloud,” Sreekanti said, pointing out that implementing AI in the workflow is “not much value to us if we don’t harness the data.”

The platform is a culmination of HPE’s investments in companies such as BlueData Software Inc, MapR Technologies Inc. and Nimble Storage Inc. “All these pieces are coming together and providing a modern digitization platform for the customers,” Sreekanti stated.

Splunk Operator and Spark workloads

A powerful use case scenario for Ezmeral comes from its combination with Splunk Operator for Kubernetes. “It’s going to be at five nines for that same Splunk operator on-premises, on the Kubernetes open source, which is, as far as I’m concerned, a very, very high-end computer science work,” Christiansen said.

Apache Spark is another use case where Ezmeral excels. “Nobody handles Spark workloads like we do,” Christiansen added. One benefit is that HPE’s Ezmeral Data Fabric doesn’t have to be bolted with the Ezmeral container platform but can be deployed underneath competitor platforms that “don’t handle data well,” he stated.

“We get lots and lots of calls for people saying, ‘Hey, can you take your Ezmeral data fabric and solve my large-scale, highly challenging data problems?'” Christiansen explained. “We say, ‘Yeah, and then when you’re ready for a real-world, full-time, enterprise-ready container platform, we’d be happy to provide that to you too.’”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the HPE Ezmeral\\Analytics Unleashed event. (* Disclosure: TheCUBE is a paid media partner for the HPE Ezmeral\\Analytics Unleashed event. Neither Hewlett Packard Enterprise Co., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE