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 produce LLMs to manufacturing rapidly and safely.
JFrog Runtime is a brand new safety answer that enables builders to find vulnerabilities in runtime environments. It displays Kubernetes clusters in actual time to determine, prioritize, and remediate safety incidents based mostly on their threat.
It gives builders with a technique to trace and handle packages, set up repositories by surroundings varieties, and activate JFrog Xray insurance policies. Different advantages embrace centralized incident consciousness, complete analytics for workloads and containers, and steady monitoring of post-deployment threats like malware or privilege escalation.
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“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 fitting, 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 undertaking standing and safety posture, permitting them to deal with potential points extra quickly.
JFrog prospects now get entry to GitHub’s Copilot chat extension, which may also help them choose software program packages which have already been up to date, accredited by the group, and protected 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 exhibits the well being and safety standing of GitHub Actions Workflows, and dynamic undertaking 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 response to 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 will likely be that builders can deliver LLMs to manufacturing rapidly whereas additionally sustaining transparency, traceability, and belief.
Advantages embrace 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 also help them quickly choose and deploy fashions which can be accredited for improvement,” stated Pat Lee, vp of enterprise strategic partnerships at NVIDIA. “The mixing of NVIDIA NIM microservices into the JFrog Platform may also help builders rapidly get absolutely compliant, performance-optimized fashions rapidly operating in manufacturing.”
