The multicloud environment can present a bounty of challenges for enterprises. It is not just about moving legacy applications to modern storage appliances; it is also about how to match one’s workload to the right cloud.

Data-driven analytics can help companies to make informed and better workload placement decisions, according to Bobby Allen (pictured, left), chief technology officer and chief marketing evangelist of CloudGenera Inc., a cloud decision engine that provides vendor-agnostic information technology analysis.

“Sometimes it is not just about lower cost. Sometimes it’s about agility, flexibility, deploying to different regions,” Allen said. “So, what we often start with is ‘what does better look like to you’? And based on that, we analyze the applications with an objective data-driven framework, and then make sure the apps land where they’re supposed to go.”

This process in business cannot start with an IT objective, according to William Giard (pictured, right), chief technology officer — digital transformation and scale solutions — Data Center Group at Intel Corp, which partnered with CloudGenera. “The first thing really is what is the core company strategy and imperatives of the business objective, and then how IT can help them achieve that.”

Allen and Giard spoke with Lisa Martin (@LisaMartinTV) and John Walls (@JohnWalls21), hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the AWS re:Invent event in Las Vegas. They discussed how CloudGenera evaluates customer workloads for cloud migration, the challenges enterprises face on this journey, and the opportunities this process can create for businesses. (* Disclosure below.)

Evaluating technical characteristics of workloads

After much research with their customers, Intel and CloudGenera have found that many technical characteristics of workloads need to be analyzed before deciding to migrate them to the cloud.

First, it is necessary to evaluate the size of the data, where it is created, and where it is used. “Second is the performance, not only to other systems around it or the end user, but the performance of the infrastructure,” Giard explained.

Other characteristics are workload integration with other systems and security. “Regulatory needs, what are we having from top-secret data to companies’ sensitive data, and really get that type of information to drive those workload placement decisions,” Giard said.

Consulting clients in this process also involves adjusting expectations to be more realistic. “You’re not going to put your ERP system in the cloud and drop 30% cost in a month, and so that’s where we need to have a conversation,” Allen pointed out. “It’s not a cloud capability problem; it’s an expectation problem.”

To help companies gain more insight into the results of technology change, CloudGenera and Intel simulate what workload migration would look like.

“We are going to take those legacy workloads, and let’s model containers, let’s model microservices,” Allen said. “So before you have to invest in transformation that may not make sense, let’s see what the outcomes look like through simulation, through AI, through ML.”

By training customers to better allocate resources in workload placement decisions, CloudGenera guides companies to consider five factors: location, service, configuration, licensing model, and pricing model. “So even if you decide on AWS as your strategic partner, we are not done yet,” Allen stated. “Let’s take advantage of what AWS does well and improve it for your business.”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the AWS re:Invent event. (* Disclosure: Intel Corp. sponsored this segment of theCUBE. Neither Intel nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE