MLflow
by Linux Foundation
Open-source platform for ML and GenAI lifecycle management with a REST API for experiments, runs, metrics, models and traces.
- Category
- Cloud & Data Platforms
- Type
- MLOps
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- Access token, Username and password
- Docs
- MLflow API docs
02Data
What you can sync.
- Experiments
- Runs
- Metrics
- Registered models
- Traces
Load MLflow experiments into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other MLflow data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An access token
- A username and password
MLflow uses an access token or a username and password. You add the credentials once, when the AI asks for them, and it tells you where to create them in Linux Foundation if you need help.
04How it works
How it works in DataMind.
-
Pick MLflow.
Open Lake, pick MLflow in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the MLflow API docs.
-
Answer a few questions.
The AI reads the MLflow documentation, then asks which credentials you will use, which data to sync (for example experiments and runs), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then MLflow data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
