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The latest News and Information on Continuous Integration and Development, and related technologies.

Revolutionize Your Development Pipeline Embrace DevOps for Seamless Integration and Continuous Delivery

Traditional development methodologies are being replaced by more efficient and collaborative approaches like DevOps. By integrating development (Dev) and operations (Ops) teams, DevOps streamlines the software delivery process, leading to faster time-to-market, improved product quality, and increased customer satisfaction.

Practical Workflows for Managing Vulnerabilities using Cloudsmith

Worried about supply chain attacks and hidden vulnerabilities compromising your organization's software integrity? Join Alison Sickelka, VP Product, and Ciara Carey, Developer Relations, as they lead our webinar, 'Practical Workflows for Managing Vulnerabilities using Cloudsmith.' Discover how Cloudsmith serves as your organization's central source of truth for builds, mitigating risks, optimizing workflows, and ensuring global distribution.

Advancing MLOps with JFrog and Qwak

Modern AI applications are having a dramatic impact on our industry, but there are still certain hurdles when it comes to bringing ML models to production. The process of building ML models is so complex and time-intensive that many data scientists still struggle to turn concepts into production-ready models. Bridging the gap between MLOps and DevSecOps workflows is key to streamlining this process.

Achieving AI development at scale ft. Luis Ceze of OctoAI

In this episode, Rob is joined by Luis Ceze, CEO of OctoAI and a distinguished professor of computer science at the University of Washington. Together, they unpack the surge of interest in AI, attributing it to the convergence of factors like the unprecedented availability of data thanks to the internet boom and the accessibility of powerful computing resources.

Four Key Lessons for ML Model Security & Management

With Gartner estimating that over 90% of newly created business software applications will contain ML models or services by 2027, it is evident that the open source ML revolution is well underway. By adopting the right MLOps processes and leveraging the lessons learned from the DevOps revolution, organizations can navigate the open source and proprietary ML landscape with confidence.