A SaaS-first MLOps suite that tracks experiments, datasets and models while enabling collaborative LLM/GenAI application development.
An open-source platform from Databricks that manages the entire machine-learning lifecycle with experiment tracking, model packaging, registry and deployment.
An Iguazio-backed open-source framework that orchestrates data/ML/LLM pipelines with serverless execution, tracking and monitoring.
Netflix’s human-centric framework for building and operating real-life data-science and ML workflows with idiomatic Python and production-grade scaling.
A Kubernetes-native workflow engine (originally at Lyft, now LF AI & Data) that provides strongly-typed, versioned data/ML pipelines at scale.
An extensible open-source MLOps framework that lets teams design portable, reproducible pipelines decoupled from infra stacks.
A Yunshan Networks open-source observability stack that delivers zero-code eBPF-based tracing, metrics and continuous profiling for cloud-native & AI workloads.
