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feat: [Backend] Data Quality Monitoring with native compute, multi-backend support, REST API, CLI by jyejare · Pull Request #6202 · feast-dev/feast · GitHub
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feat: [Backend] Data Quality Monitoring with native compute, multi-backend support, REST API, CLI - #6202

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feat: [Backend] Data Quality Monitoring with native compute, multi-backend support, REST API, CLI#6202
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@jyejare jyejare commented Mar 31, 2026 •
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To check real UI monitoring:

Visit PR #6422, see Demo.

What this PR does / why we need it:

This PR introduces comprehensive feature quality monitoring capabilities to Feast, enabling proactive tracking of feature distributions and data quality metrics. Currently, Feast has no built-in tools for monitoring feature health in production — ML teams must build custom solutions to detect issues like distribution shifts, elevated null rates, or degraded data quality before they silently impact model performance.

What it adds:

Core Monitoring Engine

  • Hybrid computation engine — SQL push-down on the native OfflineStore as the primary compute path, with a Python-based (PyArrow/NumPy) fallback for backends that don't implement native compute. This leverages the offline store as a compute engine (same architecture as Feast materialization).
  • Fully native storage — Monitoring metrics are stored within the configured OfflineStore backend itself (no separate monitoring database). Six static methods on the OfflineStore base class (compute_monitoring_metrics, get_monitoring_max_timestamp, ensure_monitoring_tables, save_monitoring_metrics, query_monitoring_metrics, clear_monitoring_baseline) handle compute and storage.
  • PyArrow-based metrics computation (MetricsCalculator) — Backend-agnostic statistical computation as fallback, supporting:
    • Numeric features: mean, stddev, min/max, percentiles (p50/p75/p90/p95/p99), null rate, histograms
    • Categorical features: top-N value counts with other/unique counts
    • Automatic feature type classification from Feast's PrimitiveFeastType and ValueType

Multi-Backend Support (8 Offline Stores)

All 6 native monitoring methods implemented for each backend with dialect-specific SQL:

Backend Compute Storage Dialect highlights
PostgreSQL SQL push-down INSERT ON CONFLICT PERCENTILE_CONT, WIDTH_BUCKET
Snowflake SQL push-down MERGE with VARIANT JSON APPROX_PERCENTILE, WIDTH_BUCKET
BigQuery SQL push-down MERGE into BQ tables APPROX_QUANTILES, parameterized queries
Redshift SQL push-down MERGE via Data API APPROXIMATE PERCENTILE_DISC
Spark SparkSQL push-down Parquet tables PERCENTILE_APPROX, spark.sql()
Oracle SQL via Ibis MERGE FROM DUAL PERCENTILE_CONT WITHIN GROUP
DuckDB In-memory SQL Parquet files QUANTILE_CONT, HISTOGRAM
Dask PyArrow compute Parquet files pyarrow.compute + numpy

Multi-Granularity Time-Series Metrics

  • 5 granularities: daily, weekly, biweekly, monthly, quarterly
  • Auto-compute mode: Detects latest event timestamp and computes all granularities in one job
  • Pre-computed metrics stored per date + granularity for fast retrieval
  • On-demand transient compute: Fresh statistics for arbitrary date ranges (not stored)

Batch + Log Data Source Support

  • Batch source: Reads from the feature view's batch_source via OfflineStore.pull_all_from_table_or_query()
  • Log source: Reads from feature serving logs via FeatureService.logging_config destination, using __log_timestamp as event timestamp
  • Feature name normalization: Prefixed log column names (driver_stats__conv_rate) are parsed back to their original feature_view_name + feature_name for storage compatibility and drift detection
  • data_source_type column (batch / log) differentiates metrics in storage

Orchestration Service (MonitoringService)

  • Ties registry, offline store, calculator, and storage together
  • Computes and aggregates metrics at feature, feature view, and feature service levels
  • Cached OfflineStore instance for performance
  • Unified compute/timestamp methods handling both batch and log paths with SQL push-down + fallback

NaN/Inf Sanitization

  • Multi-layered protection against NaN/Inf float values that break JSON serialization:
    • opt_float() in monitoring_utils.py — sanitizes at SQL result parsing
    • _sanitize_floats() in monitoring_service.py — final safety net on all API read paths
    • Applied in PyArrow compute paths (MetricsCalculator, Dask backend)
  • Prevents HTTP 422 errors from Out of range float values are not JSON compliant: nan

Shared Utilities (monitoring_utils.py)

  • Centralized table name constants, column lists, PK definitions
  • monitoring_table_meta(), opt_float(), empty_numeric_metric(), empty_categorical_metric(), normalize_monitoring_row(), build_view_aggregate()
  • Used by all 8 backends — eliminates duplication and ensures consistency

DQM Job Engine (DQMJobManager)

  • Asynchronous job abstraction for metric computation (compute, baseline, auto_compute)
  • Job status tracking in feast_monitoring_jobs table
  • Forwards all parameters including set_baseline to the compute engine
  • Supports future integration with Ray/Spark job runners

REST API (/monitoring/)

Method Endpoint Description
POST /monitoring/compute Submit batch DQM job
POST /monitoring/auto_compute Auto-detect dates, all granularities
POST /monitoring/compute/transient On-demand compute (not stored)
POST /monitoring/compute/log Compute from serving logs
POST /monitoring/auto_compute/log Auto-detect log dates, all granularities
GET /monitoring/jobs/{job_id} DQM job status
GET /monitoring/metrics/features Per-feature metrics
GET /monitoring/metrics/feature_views Per-view aggregates
GET /monitoring/metrics/feature_services Per-service aggregates
GET /monitoring/metrics/baseline Baseline distribution retrieval
GET /monitoring/metrics/timeseries Time-series data for trend analysis

All endpoints support cascading filters: project, feature_service_name, feature_view_name, feature_name, granularity, data_source_type, date range.

RBAC enforced using existing AuthzedAction.DESCRIBE (read) and AuthzedAction.UPDATE (compute).

CLI (feast monitor run)

Options:
  --feature-view TEXT       Feature view name (omit for all)
  --feature-service TEXT    Feature service name (required for --source-type log with explicit dates)
  --feature-name TEXT       Feature name(s), repeatable
  --start-date TEXT         Start date YYYY-MM-DD (omit for auto-detect)
  --end-date TEXT           End date YYYY-MM-DD (omit for auto-detect)
  --granularity TEXT        daily | weekly | biweekly | monthly | quarterly
  --set-baseline            Mark this computation as baseline
  --source-type TEXT        batch | log | all (default: batch)

Auto-Baseline on feast apply

  • Automatically queues baseline metric computation for new features on feast apply
  • Non-blocking (async DQM job), idempotent (skips existing baselines)
  • Configurable — can be disabled via feature_store.yaml:
data_quality_monitoring:
  auto_baseline: false

Feast Operator Support

  • New CRD type: DataQualityMonitoringConfig added to FeatureStoreSpec
  • Operator generates data_quality_monitoring section in feature_store.yaml when config is set
  • DeepCopy methods auto-generated via make generate
  • Disabling auto-baseline from operator CR:
apiVersion: feast.dev/v1
kind: FeatureStore
spec:
  feastProject: my_project
  dataQualityMonitoring:
    autoBaseline: false

Documentation

  • How-to guide: docs/how-to-guides/feature-monitoring.md — Production setup, CLI usage, REST API reference, orchestrator integration (Airflow, KFP, cron, K8s CronJob), backend compatibility table
  • Quickstart notebook: examples/monitoring/monitoring-quickstart.ipynb — 12-step hands-on walkthrough with visualization examples
  • docs/SUMMARY.md updated with links to both

Design decisions:

  • Native OfflineStore compute + storage — Each backend implements its own SQL push-down for metrics calculation and uses its native UPSERT/MERGE for storage. No separate monitoring database needed.
  • Hybrid fallback — Backends that don't implement native compute fall back to Python/PyArrow, ensuring all offline stores are supported.
  • Separate /monitoring/ route rather than extending existing /metrics/ — The existing metrics route serves registry inventory metadata; monitoring serves statistical feature quality data with a different data path.
  • DQM Job Engine for async computation — Supports future Ray/Spark integration for distributed metric computation.
  • Top-level data_quality_monitoring config — Sits alongside materialization and openlineage in RepoConfig, reflecting that it spans offline store compute/storage + apply trigger + server API.

Which issue(s) this PR fixes:

Partially Fixes #5919

Checks

  • I've made sure the tests are passing.
  • My commits are signed off (git commit -s)
  • My PR title follows conventional commits format

Testing Strategy

  • Unit tests
  • Integration tests
  • Operator unit tests (Ginkgo)

Test coverage (all passing):

Test Suite Count Covers
test_metrics_calculator.py 30+ Numeric/categorical computation, edge cases (empty, all-null, single value, high cardinality), type classification, PyArrow type classification, NaN/Inf sanitization, JSON serializability
test_compute_correctness.py 40+ Per-backend metric accuracy for all 8 offline stores (DuckDB, Dask, PostgreSQL, Snowflake, BigQuery, Redshift, Oracle, Spark) — numeric stats, histograms, categorical counts
test_monitoring_integration.py 16+ End-to-end batch/log computation, baseline flow, view/service aggregation, native storage dispatch, log feature name normalization, REST API endpoints, CLI, RBAC enforcement
repo_config_test.go 92 Operator repo config generation including DataQualityMonitoring config with auto_baseline disabled, YAML serialization verification

Snyk SAST scan: 0 vulnerabilities across all new files.

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jyejare requested a review from a team as a code owner March 31, 2026 10:53
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jyejare marked this pull request as draft March 31, 2026 10:54
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jyejare force-pushed the monitoring_plus branch 4 times, most recently from d0b45bb to c06853e Compare April 21, 2026 14:00
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jyejare marked this pull request as ready for review April 21, 2026 14:34
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jyejare requested review from a team and sudohainguyen as code owners April 21, 2026 14:34
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@jyejare jyejare changed the title feat: Add feature quality monitoring with statistical metrics, REST API, and CLI feat: Add feature quality monitoring with native offline store compute/storage, multi-backend support, REST API, CLI, and operator config Apr 21, 2026
@jyejare jyejare changed the title feat: Add feature quality monitoring with native offline store compute/storage, multi-backend support, REST API, CLI, and operator config feat: [Backend] Add feature quality monitoring with native offline store compute/storage, multi-backend support, REST API, CLI, and operator config Apr 21, 2026
@jyejare jyejare changed the title feat: [Backend] Add feature quality monitoring with native offline store compute/storage, multi-backend support, REST API, CLI, and operator config feat: [Backend] DQM with native compute, multi-backend support, REST API, CLI Apr 21, 2026
@jyejare jyejare mentioned this pull request May 5, 2026
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jyejare force-pushed the monitoring_plus branch from 3da4dde to 0344087 Compare May 5, 2026 08:52
ntkathole
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(feast_feature_freshness_seconds)."""


class DqmInitialDistributionConfig(FeastConfigBaseModel):

@ntkathole ntkathole May 6, 2026 •
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I think these configs should also live at top instead of feature_server. It uses the offline store, not the online server. This field is more similar to materialization, which is top-level config.

#feature_store.yaml        

feature_monitoring:   
  auto_baseline: false

This matches the pattern: materialization: spans offline+online stores, openlineage: spans apply+materialize - feature_monitoring: spans offline store (compute/storage) + apply trigger + server API.

@jyejare jyejare May 8, 2026

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This could be due to the existing metrics config is residing under server config. The metrics(even operational metrics) could also be computed for offline store. So I think its good if we move both operational metrics and dqm metrics under the parent monitoring config.

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jyejare force-pushed the monitoring_plus branch from 58795bc to a26ab3c Compare May 8, 2026 07:23
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jyejare added a commit to jyejare/feast that referenced this pull request Jun 3, 2026
@jyejare
fix: Address Devin AI review comments on PR feast-dev#6202
fbc5254 
- Forward set_baseline parameter in DQMJobManager.execute_job for
  compute jobs so user intent to mark a computation as baseline is
  no longer silently dropped.
- Add "1=1" fallback when ts_filter is empty (both start_date and
  end_date are None) in BigQuery, PostgreSQL, and Snowflake monitoring
  compute to prevent invalid SQL generation.

Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
jyejare force-pushed the monitoring_plus branch 2 times, most recently from 0fe6970 to d114171 Compare June 3, 2026 12:36
jyejare added a commit to jyejare/feast that referenced this pull request Jun 3, 2026
@jyejare
fix: Address Devin AI review comments on PR feast-dev#6202
13411af 
- Forward set_baseline parameter in DQMJobManager.execute_job for
  compute jobs so user intent to mark a computation as baseline is
  no longer silently dropped.
- Add "1=1" fallback when ts_filter is empty (both start_date and
  end_date are None) in BigQuery, PostgreSQL, and Snowflake monitoring
  compute to prevent invalid SQL generation.

Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
jyejare force-pushed the monitoring_plus branch 7 times, most recently from 462da5b to 1d61e7c Compare June 4, 2026 14:22
@ntkathole

ntkathole commented Jun 9, 2026

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@jyejare please resolve conflicts

jyejare and others added 10 commits June 9, 2026 13:43
@jyejare
feat: Statistical/Distribution metrics in Feast
d273343 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
chore: Serving Time metrics and monitoring rollout to more backends
65a6849 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
chore: Performance Improvements
261c6e6 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
docs: Monitoring User Guide
f32628d 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
feat: Optional Monitoring and utils file added
e6fcd74 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
test: Validate the query logic to validate metrics calculation
1f07b23 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
fix: Review comments and relevent code fixed
f1dbcb9 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
fix: None values handled gracefully
1a41858 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
chore: Update the monitoring backend based on frontent needs
707114e 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
@jyejare
fix: Address Devin AI and others review comments
50b45ac 
Signed-off-by: Jitendra Yejare <11752425+jyejare@users.noreply.github.com>
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jyejare force-pushed the monitoring_plus branch from 1d61e7c to 50b45ac Compare June 9, 2026 08:19
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Looks good

@ntkathole
ntkathole merged commit 5458c37 into feast-dev:master Jun 9, 2026
36 of 37 checks passed
franciscojavierarceo pushed a commit that referenced this pull request Jun 13, 2026
@feast-ci-bot
chore(release): release 0.64.0
9bb73cc 
# [0.64.0](v0.63.0...v0.64.0) (2026-06-13)

### Bug Fixes

* Add async_supported property to RedisOnlineStore ([9b088fe](9b088fe))
* Add missing feast init templates to operator CRD and enhance persistence documentation ([1941d4d](1941d4d))
* Allow to publish from reference branch ([5458ec8](5458ec8))
* API calls list ([4203eb7](4203eb7))
* **bigquery:** Enable list inference for parquet loads in offline_write_batch ([9243497](9243497)), closes [#5845](#5845)
* Bump grpcio dependencies ([07b4782](07b4782))
* **compute-engine/local:** Honor field_mapping on join keys in dedup + join nodes ([#6395](#6395)) ([bd01824](bd01824))
* **dynamodb:** Avoid tag race condition by using diff-based tag updates ([#6479](#6479)) ([bad2b7d](bad2b7d)), closes [#6418](#6418)
* **dynamodb:** Fix mypy type for _build_projection_expression return ([217b4da](217b4da))
* Fix intermittent async test failures for DynamoDB and Redis ([63c5eb1](63c5eb1))
* Fix mongodb blog title ([57d28d4](57d28d4))
* Fix shared SQL registry crash - avoid unnecessary UDF deserialization in proto cache building ([ac588d7](ac588d7))
* Fix SparkRetrievalJob.persist() failing for SparkSource ([209d7cd](209d7cd))
* Fixed formatting and image for mongo blog ([#6377](#6377)) ([f8389fb](f8389fb))
* Fixes for ray source ([7f592a4](7f592a4))
* **go:** skip registry refresh when cache_ttl_seconds <= 0 ([97ed40c](97ed40c))
* Handle array of strings columns in Athena materialization ([#6324](#6324)) ([4ed0278](4ed0278))
* make milvus VARCHAR max_length configurable, remove hardcoded 512 limit ([3b98c22](3b98c22))
* **operator:** Set appProtocol: grpc on registry gRPC Service ([#6367](#6367)) ([c9ae2b4](c9ae2b4))
* PyJWT 2.10+ added validation that rejects empty HMAC keys ([e756ffe](e756ffe))
* RemoteOnlineStore sends all features in a single HTTP request ([8f187dd](8f187dd))
* Remove registry proto dump to enforce RBAC and add permission checks to Commit/Refresh RPCs ([328431f](328431f))
* Remove selector migration job - no longer needed ([51c325e](51c325e))
* replace broken .claude skill symlink with correct relative path ([4541690](4541690))
* Replace selector label strip patch with migration Job for upgrade-safe selector uniqueness ([00dea50](00dea50))
* Scope feature view name conflict check to current project in file-based registry ([#6369](#6369)) ([a4fde83](a4fde83)), closes [#6209](#6209)
* **snowflake:** Stop double-quoting connection identifiers ([#6462](#6462)) ([e914d59](e914d59))
* **spark:** S3/GCS PyArrow filesystem resolution for staging paths ([#6442](#6442)) ([ae50414](ae50414))
* **trino:** Clean up temporary entity tables after retrieval ([#6381](#6381)) ([d86b13d](d86b13d)), closes [#6306](#6306)
* Update go-feature-server base image to Go 1.25 and fix operator Dockerfile COPY permissions ([86ef0bc](86ef0bc))

### Features

* [Backend] Data Quality Monitoring with native compute, multi-backend support, REST API, CLI ([#6202](#6202)) ([5458c37](5458c37))
* Add apache flink compute engine ([#6476](#6476)) ([9636d6a](9636d6a))
* Add demo noteboooks for users ([e362173](e362173))
* Add enabled/disabled toggle for feature views ([#6401](#6401)) ([5f1fa0d](5f1fa0d)), closes [#6395](#6395)
* Add Label View to init template ([ec272d5](ec272d5))
* Add mTLS support to remote registry gRPC client ([#6474](#6474)) ([c9602d8](c9602d8))
* Add Prometheus gauges for FeatureStore installation telemetry ([#6354](#6354)) ([1b681b7](1b681b7))
* Adds registry REST API endpoints for managing entities, data sources, and feature views ([#6413](#6413)) ([f77bd1d](f77bd1d))
* Allow CRUD on entities, data sources, and feature views from UI ([#6412](#6412)) ([2321c07](2321c07))
* Allow default openlineage configuration ([#6467](#6467)) ([276b6df](276b6df))
* **bigquery:** Support DATE-type event timestamp columns ([#6362](#6362)) ([753dee5](753dee5)), closes [#2530](#2530)
* **cli:** Add `feast projects delete` command (closes [#5095](#5095)) ([#6318](#6318)) ([1a4b96c](1a4b96c))
* Data Quality Monitoring added in feast UI ([#6422](#6422)) ([fa271be](fa271be))
* **dynamodb:** Use ProjectionExpression when requested_features is set ([0adc906](0adc906)), closes [#6058](#6058)
* Enhance DataSource and FeatureView modals with error handling and submission states ([96d7169](96d7169))
* Expose registry endpoints on feature server for MCP access ([f77981c](f77981c))
* Feast First-Class LabelView Implementation ([#6292](#6292)) ([c0e7e5d](c0e7e5d))
* Feast-MLflow Integration ([#6235](#6235)) ([7279c75](7279c75))
* Operational metrics for offline store and SOX metrics for both ([#6340](#6340)) ([65b1b80](65b1b80))
* Pre-compute feature service ([8011550](8011550))
* REST API-backed UI for RBAC compatibility and per-page lazy loading ([#6414](#6414)) ([6ae80af](6ae80af))
* Support non-string map key types ([#6382](#6382)) ([#6383](#6383)) ([728aa2e](728aa2e))
* Update FeatureStore CRD with DRA Fields ([01241e4](01241e4))

### Performance Improvements

* Cache feature view resolution in get_online_features to reduce per-request overhead ([55c2f18](55c2f18))
* Optimize feature serving latency with batched async Redis, cached checks fix ([103809a](103809a))
* Replace MessageToDict with optimized custom dict builder ([#6015](#6015)) ([9902064](9902064))
Srihari1192 pushed a commit to Srihari1192/feast that referenced this pull request Jun 22, 2026
@feast-ci-bot Srihari Venkataramaiah
chore(release): release 0.64.0
22c3721 
# [0.64.0](feast-dev/feast@v0.63.0...v0.64.0) (2026-06-13)

### Bug Fixes

* Add async_supported property to RedisOnlineStore ([9b088fe](feast-dev@9b088fe))
* Add missing feast init templates to operator CRD and enhance persistence documentation ([1941d4d](feast-dev@1941d4d))
* Allow to publish from reference branch ([5458ec8](feast-dev@5458ec8))
* API calls list ([4203eb7](feast-dev@4203eb7))
* **bigquery:** Enable list inference for parquet loads in offline_write_batch ([9243497](feast-dev@9243497)), closes [feast-dev#5845](feast-dev#5845)
* Bump grpcio dependencies ([07b4782](feast-dev@07b4782))
* **compute-engine/local:** Honor field_mapping on join keys in dedup + join nodes ([feast-dev#6395](feast-dev#6395)) ([bd01824](feast-dev@bd01824))
* **dynamodb:** Avoid tag race condition by using diff-based tag updates ([feast-dev#6479](feast-dev#6479)) ([bad2b7d](feast-dev@bad2b7d)), closes [feast-dev#6418](feast-dev#6418)
* **dynamodb:** Fix mypy type for _build_projection_expression return ([217b4da](feast-dev@217b4da))
* Fix intermittent async test failures for DynamoDB and Redis ([63c5eb1](feast-dev@63c5eb1))
* Fix mongodb blog title ([57d28d4](feast-dev@57d28d4))
* Fix shared SQL registry crash - avoid unnecessary UDF deserialization in proto cache building ([ac588d7](feast-dev@ac588d7))
* Fix SparkRetrievalJob.persist() failing for SparkSource ([209d7cd](feast-dev@209d7cd))
* Fixed formatting and image for mongo blog ([feast-dev#6377](feast-dev#6377)) ([f8389fb](feast-dev@f8389fb))
* Fixes for ray source ([7f592a4](feast-dev@7f592a4))
* **go:** skip registry refresh when cache_ttl_seconds <= 0 ([97ed40c](feast-dev@97ed40c))
* Handle array of strings columns in Athena materialization ([feast-dev#6324](feast-dev#6324)) ([4ed0278](feast-dev@4ed0278))
* make milvus VARCHAR max_length configurable, remove hardcoded 512 limit ([3b98c22](feast-dev@3b98c22))
* **operator:** Set appProtocol: grpc on registry gRPC Service ([feast-dev#6367](feast-dev#6367)) ([c9ae2b4](feast-dev@c9ae2b4))
* PyJWT 2.10+ added validation that rejects empty HMAC keys ([e756ffe](feast-dev@e756ffe))
* RemoteOnlineStore sends all features in a single HTTP request ([8f187dd](feast-dev@8f187dd))
* Remove registry proto dump to enforce RBAC and add permission checks to Commit/Refresh RPCs ([328431f](feast-dev@328431f))
* Remove selector migration job - no longer needed ([51c325e](feast-dev@51c325e))
* replace broken .claude skill symlink with correct relative path ([4541690](feast-dev@4541690))
* Replace selector label strip patch with migration Job for upgrade-safe selector uniqueness ([00dea50](feast-dev@00dea50))
* Scope feature view name conflict check to current project in file-based registry ([feast-dev#6369](feast-dev#6369)) ([a4fde83](feast-dev@a4fde83)), closes [feast-dev#6209](feast-dev#6209)
* **snowflake:** Stop double-quoting connection identifiers ([feast-dev#6462](feast-dev#6462)) ([e914d59](feast-dev@e914d59))
* **spark:** S3/GCS PyArrow filesystem resolution for staging paths ([feast-dev#6442](feast-dev#6442)) ([ae50414](feast-dev@ae50414))
* **trino:** Clean up temporary entity tables after retrieval ([feast-dev#6381](feast-dev#6381)) ([d86b13d](feast-dev@d86b13d)), closes [feast-dev#6306](feast-dev#6306)
* Update go-feature-server base image to Go 1.25 and fix operator Dockerfile COPY permissions ([86ef0bc](feast-dev@86ef0bc))

### Features

* [Backend] Data Quality Monitoring with native compute, multi-backend support, REST API, CLI ([feast-dev#6202](feast-dev#6202)) ([5458c37](feast-dev@5458c37))
* Add apache flink compute engine ([feast-dev#6476](feast-dev#6476)) ([9636d6a](feast-dev@9636d6a))
* Add demo noteboooks for users ([e362173](feast-dev@e362173))
* Add enabled/disabled toggle for feature views ([feast-dev#6401](feast-dev#6401)) ([5f1fa0d](feast-dev@5f1fa0d)), closes [feast-dev#6395](feast-dev#6395)
* Add Label View to init template ([ec272d5](feast-dev@ec272d5))
* Add mTLS support to remote registry gRPC client ([feast-dev#6474](feast-dev#6474)) ([c9602d8](feast-dev@c9602d8))
* Add Prometheus gauges for FeatureStore installation telemetry ([feast-dev#6354](feast-dev#6354)) ([1b681b7](feast-dev@1b681b7))
* Adds registry REST API endpoints for managing entities, data sources, and feature views ([feast-dev#6413](feast-dev#6413)) ([f77bd1d](feast-dev@f77bd1d))
* Allow CRUD on entities, data sources, and feature views from UI ([feast-dev#6412](feast-dev#6412)) ([2321c07](feast-dev@2321c07))
* Allow default openlineage configuration ([feast-dev#6467](feast-dev#6467)) ([276b6df](feast-dev@276b6df))
* **bigquery:** Support DATE-type event timestamp columns ([feast-dev#6362](feast-dev#6362)) ([753dee5](feast-dev@753dee5)), closes [feast-dev#2530](feast-dev#2530)
* **cli:** Add `feast projects delete` command (closes [feast-dev#5095](feast-dev#5095)) ([feast-dev#6318](feast-dev#6318)) ([1a4b96c](feast-dev@1a4b96c))
* Data Quality Monitoring added in feast UI ([feast-dev#6422](feast-dev#6422)) ([fa271be](feast-dev@fa271be))
* **dynamodb:** Use ProjectionExpression when requested_features is set ([0adc906](feast-dev@0adc906)), closes [feast-dev#6058](feast-dev#6058)
* Enhance DataSource and FeatureView modals with error handling and submission states ([96d7169](feast-dev@96d7169))
* Expose registry endpoints on feature server for MCP access ([f77981c](feast-dev@f77981c))
* Feast First-Class LabelView Implementation ([feast-dev#6292](feast-dev#6292)) ([c0e7e5d](feast-dev@c0e7e5d))
* Feast-MLflow Integration ([feast-dev#6235](feast-dev#6235)) ([7279c75](feast-dev@7279c75))
* Operational metrics for offline store and SOX metrics for both ([feast-dev#6340](feast-dev#6340)) ([65b1b80](feast-dev@65b1b80))
* Pre-compute feature service ([8011550](feast-dev@8011550))
* REST API-backed UI for RBAC compatibility and per-page lazy loading ([feast-dev#6414](feast-dev#6414)) ([6ae80af](feast-dev@6ae80af))
* Support non-string map key types ([feast-dev#6382](feast-dev#6382)) ([feast-dev#6383](feast-dev#6383)) ([728aa2e](feast-dev@728aa2e))
* Update FeatureStore CRD with DRA Fields ([01241e4](feast-dev@01241e4))

### Performance Improvements

* Cache feature view resolution in get_online_features to reduce per-request overhead ([55c2f18](feast-dev@55c2f18))
* Optimize feature serving latency with batched async Redis, cached checks fix ([103809a](feast-dev@103809a))
* Replace MessageToDict with optimized custom dict builder ([feast-dev#6015](feast-dev#6015)) ([9902064](feast-dev@9902064))
@jyejare jyejare mentioned this pull request Jul 21, 2026
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@anshishrivastava anshishrivastava mentioned this pull request Jul 23, 2026
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@devin-ai-integration devin-ai-integration[bot] devin-ai-integration[bot] left review comments
@ntkathole ntkathole ntkathole approved these changes
@sudohainguyen sudohainguyen Awaiting requested review from sudohainguyen sudohainguyen is a code owner
@robhowley robhowley Awaiting requested review from robhowley robhowley is a code owner automatically assigned from feast-dev/maintainers
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@lokeshrangineni lokeshrangineni Awaiting requested review from lokeshrangineni lokeshrangineni is a code owner automatically assigned from feast-dev/maintainers

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Revamp Data Quality Monitoring

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@jyejare @Srihari1192 @ntkathole