JFrog announces new integrations and unified ops platform

JFrog, the 16-year-old Sunnyvale, California company identified for its software program provide chain platform, has introduced a collection of main improvements designed to speed up AI mannequin deployment and improve the safety of software program improvement workflows. In partnership with NVIDIA and GitHub, and with the introduction of latest runtime safety capabilities, JFrog is positioning itself to streamline important software program processes for enterprises.

Accelerating AI deployments with NVIDIA

In a strategic collaboration with NVIDIA, JFrog has launched help for NVIDIA Inference Microservices (NIM), a instrument that permits sooner deployment of generative AI fashions throughout numerous infrastructures, together with the cloud, information facilities, and workstations. This integration combines NVIDIA’s highly effective GPU-based AI providers with JFrog’s DevSecOps instruments, providing an end-to-end software program provide chain administration system designed for pace, visibility, and safety.

“AI fashions are simply one other sort of binary, like Docker or Python. We’re very honored that NVIDIA selected JFrog to be the mannequin registry of alternative for his or her enterprise GPU-optimized fashions,” stated JFrog CEO and co-founder Shlomi Ben Haim.

The partnership offers a high-performance answer for storing, scanning, and securing AI fashions, guaranteeing that deployments occur safely and effectively.

The mixing particularly enhances AI efficiency by utilizing JFrog Artifactory to handle NVIDIA NGC fashions and artifacts. This setup permits seamless deployment, permitting builders and information scientists to give attention to innovation reasonably than infrastructure challenges. By incorporating NVIDIA’s microservices into its platform, JFrog ensures that clients can deploy AI fashions rapidly, securely, and at scale.

Ben Haim highlighted the rising considerations about AI safety, referencing JFrog’s latest discovery of malicious fashions in in style repositories. “Our collaboration with NVIDIA permits us to not solely retailer AI fashions but in addition scan and safe them, guaranteeing no unhealthy issues occur when these fashions are deployed.”

With this integration, JFrog clients can profit from centralized management over AI fashions, improved governance, and a heightened capacity to detect and reply to safety threats.

Increasing integration with GitHub

JFrog additionally revealed an enhanced partnership with GitHub, designed to supply builders a unified, safe platform for managing each code and binaries. This integration helps bidirectional navigation between GitHub and JFrog Artifactory, permitting builders to trace vulnerabilities from supply code all through to deployment.

“We developed an integration that ensures the JFrog platform and GitHub platform act as one, giving builders a seamless expertise to handle their software program provide chain from supply code by binaries to manufacturing,” Ben Haim defined. This collaboration simplifies workflows, making it simpler for builders to give attention to delivering high-quality, safe software program.

One key advantage of the combination is a consolidated dashboard that gives a complete view of a undertaking’s safety standing throughout each platforms. This allows builders to establish and resolve safety points earlier within the improvement cycle, lowering dangers and minimizing prices.

Moreover, JFrog has launched help for GitHub Copilot, a instrument that makes use of AI to supply contextual coding help, boosting developer productiveness by answering coding questions throughout the improvement surroundings.

“The partnership with GitHub contains three phases: first, integrating the platforms; second, providing one safety pane of glass; and third, integrating with GitHub Copilot to help AI purposes,” Ben Haim added, illustrating the depth of the combination and its long-term worth to builders.

New runtime safety capabilities

In an additional bid to enhance safety, JFrog has launched new runtime security measures geared toward defending software program throughout the important post-deployment section. These capabilities present real-time vulnerability detection, menace monitoring, and prioritized menace triage, serving to corporations handle safety dangers in cloud-native environments.

“Safety is now a activity that’s on the developer’s plate, and we wished to offer the developer one pane of glass to view all findings, whether or not it’s supply vulnerabilities or binary vulnerabilities,” Ben Haim stated, noting the platform’s give attention to consolidating safety information right into a single, user-friendly interface.

With greater than 32% of safety breaches occurring throughout runtime, in line with {industry} analysis, these new instruments are designed to supply steady monitoring and fast insights into vulnerabilities that come up after deployment. JFrog’s runtime security measures are tailor-made to safeguard containerized purposes, a rising necessity as extra organizations shift towards dynamic, cloud-based environments.

Eyal Dyment, VP of Safety Merchandise at JFrog, burdened the necessity for safety options that reach past the event section, stating that runtime safety is important for shielding purposes and workloads from unauthorized entry, malware assaults, and privilege escalation.

Along with the real-time visibility supplied by JFrog’s new runtime security measures, builders and safety groups can use the platform to streamline menace response and optimize model management. By automating many safety processes, JFrog’s platform helps builders save time and focus extra on coding, with out compromising the safety of their purposes.

Securing the software program chain safety

These new bulletins replicate JFrog’s dedication to offering a complete answer for the trendy software program improvement lifecycle. “JFrog is a full end-to-end software program provide chain platform. We incorporate DevOps, DevSecOps, and MLOps into one platform expertise,” Ben Haim stated, explaining the corporate’s broad strategy to securing and streamlining software program improvement.

From early-stage coding to post-deployment monitoring, JFrog’s platform integrates safety and effectivity at each step. The partnership with NVIDIA affords high-performance AI deployment capabilities, whereas the combination with GitHub enhances the traceability and safety of software program parts from supply code to binary. The introduction of runtime safety capabilities completes JFrog’s full-stack strategy, guaranteeing that vulnerabilities might be addressed all through the whole software program provide chain.

“What differentiates JFrog is that we offer full traceability and visibility into the software program provide chain, one thing that no different platform can provide,” Ben Haim remarked, emphasizing JFrog’s distinctive worth proposition within the {industry}.

As software program improvement environments turn into extra advanced and threats extra refined, JFrog’s improvements are geared toward giving corporations the instruments they should shield their software program with out sacrificing pace or productiveness.

These new options and integrations can be found to current JFrog clients as a part of the corporate’s software program provide chain platform. By bringing AI acceleration, built-in safety, and superior runtime safety into one platform, JFrog continues to place itself as a frontrunner in safe, environment friendly software program improvement and supply