JFrog and NVIDIA Collaborate to Enhance AI Model Security and Deployment

JFrog Collaborates with NVIDIA to Deliver Secure AI Models With NVIDIA NIM

JFrog swampUP - JFrog Ltd. ("JFrog") (Nasdaq: FROG), the Liquid Software company and creators of the JFrog Software Supply Chain Platform, now expanded to include a unified MLOps platform through the acquisition of Qwak AI, today announced a new product integration with NVIDIA NIM microservices, part of the NVIDIA AI Enterprise software platform. The integration of the JFrog Platform with the JFrog Artifactory model registry and NVIDIA NIM is expected to combine GPU-optimized, pre-approved AI models with centralized DevSecOps processes in an end-to-end software supply chain workflow. This allows organizations to bring secure machine learning (ML) models and large language models (LLMs) to production at lightning speed, with increased transparency, traceability, and trust. This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20240910858156/en/ "As organizations rapidly adopt AI technology, it's essential to implement practices that ensure their efficiency and safety, and that incorporate AI responsibly," said Gal Marder, EVP Strategy, JFrog. "By integrating DevOps, security, and MLOps processes into an end-to-end software supply chain workflow with NVIDIA NIM microservices, customers will be able to efficiently bring secure models to production while maintaining high levels of visibility, traceability, and control throughout the pipeline." With the rise and accelerated demand for AI in software applications, data scientists and ML engineers face significant challenges when scaling ML model deployments in enterprise environments. Fragmented asset management, security vulnerabilities, compliance issues, and performance bottlenecks are compounded by the complexities of integrating AI workflows with existing software development processes and the requirement for flexible, secure deployment options across various environments. This compounded complexity can result in very long, expensive deployment cycles and, in many cases, failure of AI initiatives. "As enterprises scale their generative AI deployments, a central repository can help them rapidly select and deploy models that are approved for development," said Pat Lee, Vice President, Enterprise Strategic Partnerships, NVIDIA. "The integration of NVIDIA NIM microservices into the JFrog Platform can help developers quickly get fully compliant, performance-optimized models quickly running in production." JFrog Artifactory provides a single solution for housing and managing all the artifacts, binaries, packages, files, containers, and components for use throughout software supply chains. The JFrog Platform's integration with NVIDIA NIM is expected to incorporate containerized AI models as software packages into existing software development workflows. By coupling NVIDIA NGC - a hub for GPU-optimized deep learning, ML and HPC models - with the JFrog platform and JFrog Artifactory model registry, organizations will be able to maintain a single source of truth for all software packages and AI models, while leveraging enterprise DevSecOps best practices to gain visibility, governance, and control across their software supply chain. The integration between the JFrog Platform and NVIDIA NIM is anticipated to deliver multiple benefits, including: For a deeper look at the integration of NVIDIA NIM into the JFrog Platform, read this blog or visit https://jfrog.com/nvidia-and-jfrog, where interested parties can also sign up for the beta program. Like this story? Post this on X (Twitter): .@jfrog + @nvidia to deliver #secure, streamlined path for quickly building world-class #GenAI solutions. Learn more: https://bit.ly/4fXMMz4 #MLOps #DevSecOps #GPUs #MachineLearning #AI About JFrog JFrog Ltd. (Nasdaq: FROG) is on a mission to create a world of software delivered without friction from developer to device. Driven by a "Liquid Software" vision, the JFrog Software Supply Chain Platform is a single system of record that powers organizations to build, manage, and distribute software quickly and securely, ensuring it is available, traceable, and tamper-proof. The integrated security features also help identify, protect, and remediate against threats and vulnerabilities. JFrog's hybrid, universal, multi-cloud platform is available as both self-hosted and SaaS services across major cloud service providers. Millions of users and 7K+ customers worldwide, including a majority of the Fortune 100, depend on JFrog solutions to securely embrace digital transformation. Once you leap forward, you won't go back! Learn more at jfrog.com and follow us on Twitter: @jfrog. Cautionary Note About Forward-Looking Statements This press release contains "forward-looking" statements, as that term is defined under the U.S. federal securities laws, including, but not limited to, statements regarding our expectations regarding the planned integration between the JFrog Platform and NVIDIA AI Enterprise and NVIDIA NIM, the anticipated enhanced security related to software supply chain workflows, the expected optimization of AI application performance, and potential benefits to developers and customers. These forward-looking statements are based on our current assumptions, expectations and beliefs and are subject to substantial risks, uncertainties, assumptions and changes in circumstances that may cause JFrog's actual results, performance or achievements to differ materially from those expressed or implied in any forward-looking statement. There are a significant number of factors that could cause actual results, performance or achievements, to differ materially from statements made in this press release, including but not limited to risks detailed in our filings with the Securities and Exchange Commission, including in our annual report on Form 10-K for the year ended December 31, 2023, our quarterly reports on Form 10-Q, and other filings and reports that we may file from time to time with the Securities and Exchange Commission. Forward-looking statements represent our beliefs and assumptions only as of the date of this press release. We disclaim any obligation to update forward-looking statements except as required by law.

JFrog announces new integrations with Github Copilot, Nvidia Microservices and unified ops platform

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More JFrog, the 16-year-old Sunnyvale, California company known for its software supply chain platform, has announced a series of major innovations designed to accelerate AI model deployment and enhance the security of software development workflows. In partnership with NVIDIA and GitHub, and with the introduction of new runtime security capabilities, JFrog is positioning itself to streamline critical software processes for enterprises. Accelerating AI deployments with NVIDIA In a strategic collaboration with NVIDIA, JFrog has introduced support for NVIDIA Inference Microservices (NIM), a tool that enables faster deployment of generative AI models across various infrastructures, including the cloud, data centers, and workstations. This integration combines NVIDIA's powerful GPU-based AI services with JFrog's DevSecOps tools, offering an end-to-end software supply chain management system designed for speed, visibility, and security. "AI models are just another type of binary, like Docker or Python. We're very honored that NVIDIA chose JFrog to be the model registry of choice for their enterprise GPU-optimized models," said JFrog CEO and co-founder Shlomi Ben Haim. The partnership provides a high-performance solution for storing, scanning, and securing AI models, ensuring that deployments happen safely and efficiently. The integration specifically enhances AI performance by using JFrog Artifactory to manage NVIDIA NGC models and artifacts. This setup enables seamless deployment, allowing developers and data scientists to focus on innovation rather than infrastructure challenges. By incorporating NVIDIA's microservices into its platform, JFrog ensures that customers can deploy AI models quickly, securely, and at scale. Ben Haim highlighted the growing concerns about AI security, referencing JFrog's recent discovery of malicious models in popular repositories. "Our collaboration with NVIDIA allows us to not only store AI models but also scan and secure them, ensuring no bad things happen when these models are deployed." With this integration, JFrog customers can benefit from centralized control over AI models, improved governance, and a heightened ability to detect and respond to security threats. Expanding integration with GitHub JFrog also revealed an enhanced partnership with GitHub, designed to offer developers a unified, secure platform for managing both code and binaries. This integration supports bidirectional navigation between GitHub and JFrog Artifactory, allowing developers to track vulnerabilities from source code all the way through to deployment. "We developed an integration that ensures the JFrog platform and GitHub platform act as one, giving developers a seamless experience to manage their software supply chain from source code through binaries to production," Ben Haim explained. This collaboration simplifies workflows, making it easier for developers to focus on delivering high-quality, secure software. One key benefit of the integration is a consolidated dashboard that provides a comprehensive view of a project's security status across both platforms. This enables developers to identify and resolve security issues earlier in the development cycle, reducing risks and minimizing costs. Additionally, JFrog has introduced support for GitHub Copilot, a tool that uses AI to offer contextual coding assistance, boosting developer productivity by answering coding questions within the development environment. "The partnership with GitHub includes three phases: first, integrating the platforms; second, offering one security pane of glass; and third, integrating with GitHub Copilot to support AI applications," Ben Haim added, illustrating the depth of the integration and its long-term value to developers. New runtime security capabilities In a further bid to improve security, JFrog has launched new runtime security features aimed at protecting software during the critical post-deployment phase. These capabilities provide real-time vulnerability detection, threat monitoring, and prioritized threat triage, helping companies address security risks in cloud-native environments. "Security is now a task that is on the developer's plate, and we wanted to give the developer one pane of glass to view all findings, whether it's source vulnerabilities or binary vulnerabilities," Ben Haim said, noting the platform's focus on consolidating security data into a single, user-friendly interface. With more than 32% of security breaches occurring during runtime, according to industry research, these new tools are designed to offer continuous monitoring and immediate insights into vulnerabilities that arise after deployment. JFrog's runtime security features are tailored to safeguard containerized applications, a growing necessity as more organizations shift toward dynamic, cloud-based environments. Eyal Dyment, VP of Security Products at JFrog, stressed the need for security solutions that extend beyond the development phase, pointing out that runtime security is essential for protecting applications and workloads from unauthorized access, malware attacks, and privilege escalation. In addition to the real-time visibility offered by JFrog's new runtime security features, developers and security teams can use the platform to streamline threat response and optimize version control. By automating many security processes, JFrog's platform helps developers save time and focus more on coding, without compromising the security of their applications. Securing the software chain security These new announcements reflect JFrog's commitment to providing a comprehensive solution for the modern software development lifecycle. "JFrog is a full end-to-end software supply chain platform. We incorporate DevOps, DevSecOps, and MLOps into one platform experience," Ben Haim said, explaining the company's broad approach to securing and streamlining software development. From early-stage coding to post-deployment monitoring, JFrog's platform integrates security and efficiency at every step. The partnership with NVIDIA offers high-performance AI deployment capabilities, while the integration with GitHub enhances the traceability and security of software components from source code to binary. The introduction of runtime security capabilities completes JFrog's full-stack approach, ensuring that vulnerabilities can be addressed throughout the entire software supply chain. "What differentiates JFrog is that we provide full traceability and visibility into the software supply chain, something that no other platform can offer," Ben Haim remarked, emphasizing JFrog's unique value proposition in the industry. As software development environments become more complex and threats more sophisticated, JFrog's innovations are aimed at giving companies the tools they need to protect their software without sacrificing speed or productivity. These new features and integrations are available to existing JFrog customers as part of the company's software supply chain platform. By bringing AI acceleration, integrated security, and advanced runtime protection into one platform, JFrog continues to position itself as a leader in secure, efficient software development and delivery

JFrog unveils new runtime security and Nvidia integration for AI model protection - SiliconANGLE

JFrog unveils new runtime security and Nvidia integration for AI model protection Software supply chain company JFrog Ltd. today announced a new runtime security solution and a new product integration with Nvidia Corp. that provides users with enhanced security and the ability to secure artificial intelligence models. JFrog's new JFrog Runtime offers end-to-end protection for applications throughout their entire lifecycle, from development to deployment and production. The new service integrates into DevSecOps workflows, allowing organizations to implement security measures at every step of the software supply chain. In doing so, the service tackles vulnerabilities in real time to ensure that cloud-native applications, such as containers in Kubernetes environments, are monitored for potential risks. Features of JFrog Runtime include real-time vulnerability detection and risk prioritization that allows security and development teams to identify security issues based on their business impact and hence accelerating the triage process. The platform also safeguards applications against potential post-deployment threats, such as malware or privilege escalation attacks, through advanced monitoring for cloud-based workloads. JFrog Runtime also enhances collaboration between security and development teams through the provision of a unified platform for managing risks. With the unified platform, developers can track software packages from various sources to ensure compliance and version control, while at the same time, security teams can enforce policies that maintain the integrity of the software throughout its lifecycle. Announced alongside JFrog Runtime today was JFrog partnering with Nvidia to integrate Nvidia NIM microservices into the JFrog Platform, enabling enterprises to deploy secure, graphics processing unit-optimized AI models quickly. Nvidia NIM is a microservices platform within Nvidia AI Enterprise that provides GPU-optimized infrastructure for deploying high-performance AI models and large language models securely and efficiently. The new integration allows organizations to leverage Nvidia's AI infrastructure for high-performance machine learning while maintaining visibility and security through JFrog's unified DevSecOps workflows. Through the combination of JFrog Artifactory with Nvidia NIM, JFrog says that enterprises can streamline AI model management and accelerate the deployment of LLMs. The platform also offers users centralized control that ensures compliance and traceability across AI deployments, from development to production. "As enterprises scale their generative AI deployments, a central repository can help them rapidly select and deploy models that are approved for development," Pat Lee, vice president of Enterprise Strategic Partnerships at Nvidia, commented on the new integration. "The integration of Nvidia NIM microservices into the JFrog Platform can help developers quickly get fully compliant, performance-optimized models quickly running in production." JFrog Artifactory provides a single solution for housing and managing all artifacts, binaries, packages, files, containers and components for use throughout software supply chains. The JFrog Platform's integration with Nvidia NIM is expected to incorporate containerized AI models as software packages into existing software development workflows.

JFrog and NVIDIA partner for AI model deployment optimization By Investing.com

SUNNYVALE, Calif. & AUSTIN, Texas - In a move to streamline the deployment of AI models in enterprise environments, JFrog Ltd. (NASDAQ:FROG) has announced an integration with NVIDIA (NASDAQ:NVDA)'s NIM microservices. This collaboration is designed to enhance the delivery of GPU-optimized AI model services, combining the JFrog Platform with NVIDIA AI Enterprise capabilities. The integration aims to address the challenges faced by data scientists and ML engineers in scaling machine learning model deployments. By leveraging NVIDIA's NIM microservices, the JFrog Platform intends to provide a unified MLOps platform that facilitates the selection and deployment of pre-approved AI models within a secure and efficient software supply chain workflow. JFrog's EVP Strategy, Gal Marder, emphasized the importance of incorporating AI responsibly, ensuring efficiency, safety, and transparency throughout the development pipeline. Pat Lee, Vice President at NVIDIA, noted that the integration with NVIDIA NIM microservices can help developers deploy compliant and performance-optimized models swiftly into production. The JFrog Platform, expanded through the acquisition of Qwak AI, offers centralized DevSecOps processes for managing artifacts, binaries, and AI models. The anticipated benefits of this integration include unified management of assets, comprehensive security and integrity through continuous scanning, exceptional model performance and scalability using NVIDIA's accelerated computing, and flexible deployment options. This partnership is expected to provide a single source of truth for all software packages and AI models, maintaining high levels of visibility, governance, and control across software supply chains. The integration is also projected to deliver low latency and high throughput for the scalable deployment of large language models to large-scale production environments. For interested parties, JFrog has provided further information on the integration and a sign-up option for the beta program on their website. This news article is based on a press release statement and has been prepared without any promotional language or bias. It provides a factual summary of the key points of the integration between JFrog and NVIDIA. In other recent news, JFrog has reported a 22% year-over-year increase in total revenue for the second quarter of 2024, reaching $103 million. The company's cloud revenue also surged by 42% to $39.3 million. Simultaneously, JFrog added 115 new customers to its over $100,000 ARR category and projected revenues between $105 million and $106 million for the upcoming third quarter. In addition to its financial performance, JFrog announced a strategic partnership with GitHub and acquired MLOps platform company Qwak AI to enhance its AI-powered software capabilities. The company was also included in the Department of Defense (DoD) Enterprise Software Initiative (ESI) DevSecOps Agency Catalog, affirming its commitment to secure software supply chain solutions. Several analyst firms have updated their ratings on JFrog. Needham raised its price target for JFrog to $33.00, maintaining a Buy rating, while Baird initiated coverage with an Outperform rating and a price target of $32.00. KeyBanc reiterated its Overweight rating on JFrog, and Canaccord Genuity maintained its Buy rating, emphasizing JFrog's strategic value. These are among the recent developments for JFrog. In light of JFrog Ltd.'s recent announcement regarding the integration with NVIDIA's NIM microservices, investors might find the following InvestingPro Data and Tips illuminating. JFrog, with a market capitalization of approximately $3.1 billion, has been navigating the competitive tech landscape with some notable financial metrics. The company boasts a robust gross profit margin of 78.77% for the last twelve months as of Q2 2024, underlining the efficiency of its operations despite its current lack of profitability. From an investment perspective, JFrog has more liquid assets than short-term obligations, indicating a strong liquidity position. This is an important factor for potential investors as it means the company can cover its immediate liabilities without financial strain. Additionally, JFrog's net income is expected to grow this year, which may signal a positive trajectory for the company's financial health and could be a point of interest for those looking at long-term investment potential. While the company does not pay dividends, suggesting a reinvestment of earnings back into the company's growth initiatives, it's also worth noting that the stock has experienced a significant decline over the last six months. This could present a buying opportunity for investors who believe in the company's future profitability, which analysts predict will be achieved this year. For those seeking more detailed analysis, there are additional InvestingPro Tips available on the JFrog profile at Investing.com. These insights can further guide investment decisions regarding JFrog's stock performance and financial stability.