At its annual consumer convention, swampUp, the DevOps firm JFrog introduced new options and integrations with firms 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 resolution that enables builders to find vulnerabilities in runtime environments. It displays Kubernetes clusters in actual time to establish, prioritize, and remediate safety incidents primarily based on their danger.
It offers builders with a technique to trace and handle packages, set up repositories by setting 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.
“By empowering DevOps, Information Scientists, and Platform engineers with an built-in resolution that spans from safe mannequin scanning and curation on the left to JFrog Runtime on the best, organizations can considerably improve the supply of trusted software program at scale,” stated Asaf Karas, CTO of JFrog Safety.
Subsequent, the corporate introduced an growth 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 clients 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, accepted by the group, and protected to be used.
It additionally offers 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 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.
Based on 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 top consequence might be that builders can carry 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 might be accepted for growth,” stated Pat Lee, vice chairman 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 working in manufacturing.”