Software Development

JFrog publicizes partnership with AWS to streamline safe ML mannequin deployment

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JFrog launched a brand new integration between JFrog Artifactory and Amazon SageMaker to streamline the method of constructing, coaching, and deploying machine studying (ML) fashions. This integration will enable corporations to handle their ML fashions with the identical effectivity and safety as different software program elements in a DevSecOps workflow. 

Within the new integration, ML fashions are immutable, traceable, safe, and validated. Moreover, JFrog has enhanced its ML Mannequin administration answer with new versioning capabilities, making certain that compliance and safety are integral components of the ML mannequin improvement course of.

“As extra corporations start managing massive knowledge within the cloud, DevOps crew leaders are asking how they’ll scale knowledge science and ML capabilities to speed up software program supply with out introducing danger and complexity,” stated Kelly Hartman, SVP of worldwide channels and alliances at JFrog. “The mixture of Artifactory and Amazon SageMaker creates a single supply of reality that indoctrinates DevSecOps finest practices to ML mannequin improvement within the cloud – delivering flexibility, velocity, safety, and peace of thoughts – breaking into a brand new frontier of MLSecOps.”

A Forrester survey discovered that half of the info decision-makers see the applying of governance insurance policies inside AI/ML as a serious problem for its widespread use, and 45% view knowledge and mannequin safety as a key difficulty. 

JFrog’s integration with Amazon SageMaker addresses these issues by making use of DevSecOps finest practices to ML mannequin administration. This permits builders and knowledge scientists to reinforce and velocity up the event of ML initiatives whereas making certain enterprise-grade safety and compliance with regulatory and organizational requirements, JFrog defined.

JFrog has additionally launched new versioning capabilities in its ML Mannequin Administration answer, complementing its Amazon SageMaker integration. These capabilities combine mannequin improvement extra seamlessly into a company’s present DevSecOps workflow. In line with JFrog, this enhancement considerably will increase transparency relating to every model of the mannequin.

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