Main features & enhancements
* **Feature Store**: Support controlling whether to update stats, katyakats
* **Frameworks**: Add XGBoost, LGBM and SciKitLearn to MLRun's frameworks infrastructure, guy1992l
* **Frameworks**: Add AutoMLRun `apply_mlrun` and replaced bokeh with plotly, guy1992l
* **Frameworks**: Support LGBM auto-logging, AlxZed
* **Datastore**: Enable no credentials for working with GCP workload identity, theSaarco
* **Model Monitoring**: Use feature store for model monitoring graph, dinal
* **Runtimes**: Limit function's service accounts based on project configuration, theSaarco
* **Runtimes**: Enhance Nuclio http/stream triggers + support ignore tagged cells, yaronha
* **Runtimes**: When editing a function, you can force a rebuild of the image by checking the Build a new image option. (The default is not checked.), yaronha
* **Secrets**: Delete project secrets on project deletion, theSaarco
* **API**: Decouple the migrations from service initialization, Hedingber
* **Requirements**: Bump scikit-learn to 1.x, Hedingber
* **Requirements**: Support PyArrow 5, gtopper
* **Requirements**: Bump pip to 21.2.x and python to 3.7.11, Hedingber
* **System Tests**: Add test for remote spark ingestion, urihoenig
* **UI**: When editing a function, you can force a rebuild of the image by checking the Build a new image option (The default is not checked), ilan7empest
* **UI**: [Release notes](https://github.com/mlrun/ui/releases/tag/v0.9.0)
Notes
* **Limitations**: Ingesting data: Do not name columns starting with either `t_` or `aggr_`. They are reserved for internal use, and the data does not ingest correctly
* **Limitations**: When creating a feature-vector, feature-sets cannot be referenced using a version or tag. In practice this means that only features from the latest version of a feature-set can be used. ((In the UI be careful to only select features from the latest version)
More info can be found in the RCs release notes: