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Feast Blog

30 articles total

Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features.

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Bringing Chronon Features to Feast
Feast Feature and Vector Serving at ScyllaDB Speed
Fast like a cache, priced like storage: Benchmarking Aerospike on Feast
Aerospike now available as a Feast online store
Feast Gets Native Apache Iceberg Support
How to Use Feast for SLM/LLM Post-Training with Ray
Using Feast's OpenAI Compatible Search API
Data Quality Monitoring in Feast 0.64
Extending Feast Observability: Offline Store Metrics and SOX Audit Logging
Tuning the Feast Feature Server for Sub-2ms Online Serving
Native MLflow Integration for Feast: Automatic Feature Lineage for Every Experiment
Native MongoDB Support in Feast: One Database for Operational Data, Features, and Vectors
Building AI Agents with Feast: Feature Stores as Context and Memory
Feast Introduces Experimental Feature View Versioning
Monitoring Your Feast Feature Server with Prometheus and Grafana
Feast Meets Oracle: Unlocking Feature Store for Oracle Database Users
Feast + MLflow + Kubeflow: A Unified AI/ML Lifecycle
Feature Server High-Availability and Auto-Scaling on Kubernetes
Historical Features Without Entity IDs
Tracking Feature Lineage with OpenLineage