MLOps (Machine Learning Operations) combines machine learning, DevOps, and data engineering to streamline and automate workflows for ML model development, deployment, and maintenance.

Rust is gaining popularity in MLOps for its performance, safety, and reliability. It's used to build efficient ML infrastructure, data processing pipelines, vector databases, and model serving systems. Rust's speed and memory safety make it particularly suitable for high-performance, mission-critical MLOps components.