At its annual consumer convention, swampUp, the DevOps firm JFrog introduced new options and integrations with corporations like GitHub and NVIDIA to allow builders to enhance their DevSecOps capabilities and convey LLMs to manufacturing shortly and safely.
JFrog Runtime is a brand new safety answer that enables builders to find vulnerabilities in runtime environments. It screens Kubernetes clusters in actual time to establish, prioritize, and remediate safety incidents primarily based on their threat.
It gives builders with a way to trace and handle packages, arrange repositories by surroundings sorts, and activate JFrog Xray insurance policies. Different advantages embody centralized incident consciousness, complete analytics for workloads and containers, and steady monitoring of post-deployment threats like malware or privilege escalation.
“By empowering DevOps, Information Scientists, and Platform engineers with an built-in answer that spans from safe mannequin scanning and curation on the left to JFrog Runtime on the proper, organizations can considerably improve the supply of trusted software program at scale,” stated Asaf Karas, CTO of JFrog Safety.
Subsequent, the corporate introduced an enlargement to its partnership with GitHub. New integrations will present builders with higher visibility into challenge standing and safety posture, permitting them to handle potential points extra quickly.
JFrog prospects now get entry to GitHub’s Copilot chat extension, which may help them choose software program packages which have already been up to date, authorized by the group, and secure to be used.
It additionally gives a unified view of safety scan outcomes from GitHub Superior Safety and JFrog Superior Safety, a job abstract web page that reveals the well being and safety standing of GitHub Actions Workflows, and dynamic challenge mapping and authentication.
Lastly, the corporate introduced a partnership with NVIDIA, integrating NVIDIA NIM microservices with the JFrog Platform and JFrog Artifactory mannequin registry.
In accordance with JFrog, this integration will “mix GPU-optimized, pre-approved AI fashions with centralized DevSecOps processes in an end-to-end software program provide chain workflow.” The tip outcome might be that builders can deliver LLMs to manufacturing shortly whereas additionally sustaining transparency, traceability, and belief.
Advantages embody unified administration of NIM containers alongside different property, steady scanning, accelerated computing by means of NVIDIA’s infrastructure, and versatile deployment choices with JFrog Artifactory.
“As enterprises scale their generative AI deployments, a central repository may help them quickly choose and deploy fashions which are authorized for improvement,” stated Pat Lee, vice chairman of enterprise strategic partnerships at NVIDIA. “The mixing of NVIDIA NIM microservices into the JFrog Platform may help builders shortly get absolutely compliant, performance-optimized fashions shortly working in manufacturing.”
