# feast | Feast | Knowledge Base | Instagit

The Open Source Feature Store for AI/ML

GitHub Stars: 6.7k

Repository: https://github.com/feast-dev/feast

---

## Articles

### [How to Migrate from an Older Feast Version to the Latest Release](/feast-dev/feast/feast-migrate-older-version-latest-release)

Easily migrate from older Feast versions to the latest release. Upgrade your SDK, use the repo-upgrade tool, and switch registries for a smoother workflow.

- Tags: migration-guide
- Published: 2026-03-01

### [Feast Monitoring and Observability: Prometheus Metrics, OpenTelemetry Traces, and Data Quality Validation](/feast-dev/feast/feast-monitoring-observability-options)

Explore Feast monitoring and observability with Prometheus metrics, OpenTelemetry traces, and data quality validation. Configure your stack via Helm and Kubernetes.

- Tags: getting-started
- Published: 2026-03-01

### [How Feast Supports Multi-Region Deployments: A Technical Guide to Global Feature Stores](/feast-dev/feast/feast-multi-region-deployments-support)

Learn how Feast supports multi-region deployments. Configure region and location parameters for data locality and compliance across your global feature store.

- Tags: technical-guide
- Published: 2026-03-01

### [How to Handle Schema Evolution and Feature Version Upgrades in Feast](/feast-dev/feast/feast-schema-evolution-feature-version-upgrades)

Learn how to manage schema evolution and feature version upgrades in Feast by separating logical definitions from physical storage. Utilize Iceberg or Delta Lake for physical changes and immutable FeatureServices for versioned ...

- Tags: how-to-guide
- Published: 2026-03-01

### [Best Practices for Organizing Feature Repositories in Feast](/feast-dev/feast/feast-best-practices-organizing-feature-repositories)

Master organizing feature repositories in Feast with best practices. Learn modular file structures, clear separation of config and Python logic, and naming conventions for discoverability and maintainability.

- Tags: best-practices
- Published: 2026-03-01

### [How to Use Feast's Vector Search Functionality for Embedding-Based Retrieval](/feast-dev/feast/feast-vector-search-embedding-retrieval)

Learn how to use Feast's vector search for efficient embedding-based retrieval. Index vectors and query nearest neighbors with `retrieve_online_documents_v2` or `FeastVectorStore`.

- Tags: how-to-guide
- Published: 2026-03-01

### [How to Integrate Feast with Great Expectations for Data Validation](/feast-dev/feast/feast-integrate-great-expectations-data-validation)

Integrate Feast with Great Expectations for robust data validation. Learn how to install, define profilers, and validate historical features seamlessly.

- Tags: how-to-guide
- Published: 2026-03-01

### [What’s the Difference Between Incremental and Full Materialization in Feast?](/feast-dev/feast/feast-incremental-vs-full-materialization)

Discover the difference between incremental and full materialization in Feast. Learn why incremental materialization is the preferred choice for efficient production pipelines.

- Tags: deep-dive
- Published: 2026-03-01

### [How to Set Up High Availability for the Feast Registry](/feast-dev/feast/feast-high-availability-registry-setup)

Learn how to set up high availability for the Feast registry. Configure PostgreSQL or MySQL, deploy replicas with the Feast Operator, and use a Kubernetes ClusterIP Service for load balancing.

- Tags: how-to-guide
- Published: 2026-03-01

### [Feast Data Sources: How to Connect BigQuery, Redshift, Snowflake, PostgreSQL, and Parquet](/feast-dev/feast/feast-supported-data-sources-bigquery-redshift-snowflake-postgres-parquet)

Connect Feast to BigQuery, Redshift, Snowflake, PostgreSQL, and Parquet. Standardize validation and type mapping for production-grade data sources. Learn more now.

- Tags: how-to-guide
- Published: 2026-03-01

### [How the Feast Python Feature Server Works: Architecture and Configuration Guide](/feast-dev/feast/feast-python-feature-server-configuration)

Understand the Feast Python feature server architecture and configuration. Learn how to set up and run this gRPC service for real-time and batch feature retrieval via feast listen or programmatically.

- Tags: architecture
- Published: 2026-03-01

### [How to Use Feast's Feature Service API for Model Serving](/feast-dev/feast/feast-feature-service-api-model-serving)

Learn how to use Feast's Feature Service API to bundle features from multiple views for efficient model serving. Ensure consistent feature sets between training and inference.

- Tags: how-to-guide
- Published: 2026-03-01

### [How to Use Feast with AWS Lambda for Serverless Feature Serving](/feast-dev/feast/feast-aws-lambda-serverless-feature-serving)

Deploy a serverless feature store using Feast AWS Lambda. Expose online features via HTTP without managing instances or containers

- Tags: how-to-guide
- Published: 2026-03-01

### [Feast Batch Processing Engines: Local, Spark, Ray, Snowflake, and AWS Lambda](/feast-dev/feast/feast-batch-processing-compute-engines-spark-ray-snowflake-lambda)

Explore Feast batch processing engines: local, Spark, Ray, Snowflake, and AWS Lambda. Materialize features efficiently for your data science projects.

- Tags: deep-dive
- Published: 2026-03-01

### [How to Deploy Feast on Kubernetes for Production: Helm Chart vs Operator Guide](/feast-dev/feast/feast-deploy-feast-kubernetes-production)

Deploy Feast on Kubernetes for production with a Helm chart for simple installs or the Feast Operator for native lifecycle management autoscaling and git sync.

- Tags: how-to-guide
- Published: 2026-03-01

### [Feast Authentication and Authorization Options: OIDC, Kubernetes RBAC, and No-Auth Configuration](/feast-dev/feast/feast-authentication-authorization-options)

Explore Feast authentication options including OIDC, Kubernetes RBAC, and no-auth. Integrate with authorization managers for granular API permissions.

- Tags: deep-dive
- Published: 2026-03-01

### [How to Implement On-Demand Transformations in Feast: A Complete Guide](/feast-dev/feast/feast-implement-on-demand-transformations)

Learn how to implement on-demand transformations in Feast using ODFVs. Dynamically transform source features with pandas Python native or Substrait execution modes for efficient feature computation.

- Tags: how-to-guide
- Published: 2026-03-01

### [How to Set Up Streaming Ingestion with Kafka or Kinesis Sources in Feast](/feast-dev/feast/feast-streaming-ingestion-kafka-kinesis-sources)

Learn to set up streaming ingestion with Kafka or Kinesis sources in Feast. This guide explains the client-side pipeline for real-time feature engineering and materialization.

- Tags: how-to-guide
- Published: 2026-03-01

### [Feast Registry Types Explained: File, SQL, Snowflake, and Remote Backends](/feast-dev/feast/feast-file-sql-snowflake-remote-registry-differences)

Explore Feast registry types: File, SQL, Snowflake, and Remote. Understand their differences in storage, concurrency, and complexity for your specific use case.

- Tags: deep-dive
- Published: 2026-03-01

### [How the Feast Materialization Process Works: A Complete Guide to Optimizing Large Dataset Transfers](/feast-dev/feast/feast-materialization-process-optimize-large-datasets)

Learn how the Feast materialization process moves feature data to online stores. Optimize large dataset transfers by configuring partitions, staging, and time windows.

- Tags: deep-dive
- Published: 2026-03-01

### [Feast Online Store Implementations: Redis vs DynamoDB vs SQLite Comparison](/feast-dev/feast/feast-online-store-implementations-comparison-redis-dynamodb-sqlite)

Compare Feast online store implementations: Redis, DynamoDB, and SQLite. Discover sub-millisecond feature retrieval options for your infrastructure needs.

- Tags: comparison
- Published: 2026-03-01

### [How to Configure a Custom Offline Store in Feast](/feast-dev/feast/feast-configure-custom-offline-store)

Learn how to configure a custom offline store in Feast by implementing configuration and store classes. Point to your custom store in feature_store.yaml for tailored data storage.

- Tags: how-to-guide
- Published: 2026-03-01

### [BatchFeatureView vs FeatureView vs StreamFeatureView vs OnDemandFeatureView in Feast](/feast-dev/feast/feast-batch-featureview-vs-featureview-streamfeatureview-ondemandfeatureview)

Understand Feast feature views. Learn the differences between BatchFeatureView, StreamFeatureView, and OnDemandFeatureView for batch, real-time, and on-demand feature computation.

- Tags: deep-dive
- Published: 2026-03-01

### [How Feast Handles Point-in-Time Joins to Prevent Data Leakage During Training](/feast-dev/feast/feast-point-in-time-joins-data-leakage-training)

Feast prevents data leakage with point-in-time joins using TTL-aware SQL or Pandas. Learn how Feast guarantees temporal correctness for accurate model training.

- Tags: deep-dive
- Published: 2026-03-01