MLOps, or DevOps for machine learning, is bringing the best practices of software development to data science. You know the saying, “Give a man a fish, and you’ll feed him for a day ...

Locking down AI pipelines in Azure? A zero-trust, metadata-driven setup makes it secure, scalable and actually team-friendly.

Having separate DevOps and MLOps configurations makes it difficult to maintain a consistent approach to versioning, auditing, and traceability across the entire software system.

The XOps approach, rooted in structured operational excellence and proactive governance, positions businesses for sustained leadership.

OctoML CEO: MLOps needs to step aside for DevOps New tools from the Apache TVM inventors promote what are called "intelligent applications," programs that embed machine learning as functions.

JFrog’s swampUP is the premier DevOps, DevSecOps, MLOps - EveryOps! – conference, where developers, DevOps teams, security researchers, data scientists, innovators and IT professionals come ...

JFrog Becomes an AI System of Record, Launches JFrog ML – Industry's First End-to-End DevOps, DevSecOps & MLOps Platform for Trusted AI Delivery ...

By combining DevOps and MLOps into a single Software Supply Chain, organizations can better achieve their shared goals of rapid delivery, automation, and reliability, creating an efficient and ...