devops

Discover 10 MLOps tools designed to comply with the EU AI Act. Keep your AI systems transparent, secure, and compliant with minimal risk.

Protect your LLMs from data breaches and attacks. Explore the critical security risks and strategies to protect your models and sensitive data.

Step-by-step guide for DevOps engineers: add ML model packaging, versioning, and deployment to your existing CI/CD pipeline using KitOps. Open source.

What makes a great workflow between data scientists and ML application developers? This post discusses the disparities, required tools, and, eventually, a solution to poor collaboration.

The New Stack highlights KitOps’s innovative approach to unifying DevOps and MLOps workflows through ModelKits, enabling seamless AI/ML model deployment using existing containerization tools.

AWS bet early on cloud computing and maintained focus, leading to their success. Today, enterprises face similar challenges with AI, divided between cautious approaches and building in-house AI teams. This article outlines a path to tool selection, project prioritization, and organizational structure that will lead to an enduring competitive edge.