Device42 unveils AI recommendation engine to support cloud migration

Device42, a cloud-based software solution provider, has unveiled a multi-cloud migration and recommendation engine designed to figure out the most cost-effective way to help businesses to migrate to the cloud.

As per the company, its service will use machine learning (ML) to drive its suggestions. Furthermore, it can perform real-time discovery of IT resources to develop an inventory and will utilize dependency mapping to display the impact and relationship of resources on business units.

Currently, organizations face the risk of business outages and disruptions while migrating to the cloud. A report states that more than one-third of businesses face difficulty in taking benefits from their cloud computing projects.

However, with its new recommendation engine, Device42 aims to help businesses with cloud migration using AI-driven analysis. The service initially performs discovery of all IT resources and apps, eventually creating a directory. Once done, the engine then delivers a cost analysis to prioritize apps to move to the cloud such as AWS (Amazon Web Services) or VMWare on AWS, GCP, Microsoft Azure, or Oracle.

The recommendation engine can also provide data about resources cost and their performance impact, as well guidelines to support the best practices. It recommends the most efficient course of action, which includes factors like whether to re-architect apps, and commence work to identify the right sizes for cloud instances.

Raj Jalan, Device42 Founder and CEO, claims that the company considers cloud migration to be a big challenge for numerous organizations, and have received grievances from its customers regarding the same. With that said, Device42 has built this recommendation engine to help its customers automate the processes as well as reduce associated risk.

Mr. Jalan further added that the engine matches operating systems from on-premises solutions to the cloud to enable apps to function after being migrated. Meanwhile, savings are given to reservation purchase options and algorithms that consider storage and networking costs, along with memory and CPU.

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