feast-dev · ntkathole · Jun 3, 2026 · Apr 27, 2026 · May 11, 2026 · May 28, 2026
@@ -352,11 +352,14 @@ feature_server:
     push: true              # push request counters
     materialization: true   # materialization counters & duration
     freshness: true         # feature freshness gauges
+    offline_features: true  # offline store retrieval counters & latency
+    audit_logging: false    # structured JSON audit logs (see below)
 ```
 
 Any category set to `false` will emit no metrics and start no background
 threads (e.g., setting `freshness: false` prevents the registry polling
-thread from starting). All categories default to `true`.
+thread from starting). All categories default to `true` except
+`audit_logging`, which defaults to `false`.
 
 ### Available metrics
 
@@ -375,6 +378,9 @@ thread from starting). All categories default to `true`.
 | `feast_materialization_result_total` | Counter | `feature_view`, `status` | `materialization` | Materialization runs (success/failure) |
 | `feast_materialization_duration_seconds` | Histogram | `feature_view` | `materialization` | Materialization duration per feature view |
 | `feast_feature_freshness_seconds` | Gauge | `feature_view`, `project` | `freshness` | Seconds since last materialization |
+| `feast_offline_store_request_total` | Counter | `method`, `status` | `offline_features` | Total offline store retrieval requests |
+| `feast_offline_store_request_latency_seconds` | Histogram | `method` | `offline_features` | Latency of offline store retrieval operations |
+| `feast_offline_store_row_count` | Histogram | `method` | `offline_features` | Rows returned by offline store retrieval |
 
 ### Per-ODFV transformation metrics
 
@@ -405,6 +411,70 @@ The `odfv_name` label lets you filter or group by individual ODFV,
 and the `mode` label (`python`, `pandas`, `substrait`) lets you compare
 transformation engines.
 
+### Audit logging
+
+Feast can emit structured JSON audit log entries for every online and offline
+feature retrieval. These are written via the standard `feast.audit` Python
+logger, so you can route them to a dedicated file, SIEM, or log aggregator
+independently of application logs.
+
+Audit logging is **disabled by default**. Enable it in `feature_store.yaml`:
+
+```yaml
+feature_server:
+  type: local
+  metrics:
+    enabled: true
+    audit_logging: true
+```
+
+**Online audit log** (emitted per `/get-online-features` call):
+
+```json
+{
+  "event": "online_feature_request",
+  "timestamp": "2026-05-11T08:30:00.123456+00:00",
+  "requestor_id": "user@example.com",
+  "entity_keys": ["driver_id"],
+  "entity_count": 3,
+  "feature_views": ["driver_hourly_stats"],
+  "feature_count": 3,
+  "status": "success",
+  "latency_ms": 12.34
+}
+```
+
+**Offline audit log** (emitted per `RetrievalJob.to_arrow()` call):
+
+```json
+{
+  "event": "offline_feature_retrieval",
+  "timestamp": "2026-05-11T08:31:00.456789+00:00",
+  "method": "to_arrow",
+  "start_time": "2026-05-11T08:30:59.226789+00:00",
+  "end_time": "2026-05-11T08:31:00.456789+00:00",
+  "feature_views": ["driver_hourly_stats"],
+  "feature_count": 3,
+  "row_count": 500,
+  "status": "success",
+  "duration_ms": 1230.0
+}
+```
+
+The `requestor_id` field in online audit logs is populated from the
+security manager's current user when authentication is configured, and
+falls back to `"anonymous"` otherwise.
+
+To route audit logs to a separate file:
+
+```python
+import logging
+
+handler = logging.FileHandler("/var/log/feast/audit.log")
+handler.setFormatter(logging.Formatter("%(message)s"))
+logging.getLogger("feast.audit").addHandler(handler)
+```
+
 ### Scraping with Prometheus
 
 ```yaml

@@ -26,8 +26,8 @@ spec:
             push: true            # push/write request counters
             materialization: true # materialization counters and duration histograms
             freshness: false      # feature freshness gauges (can be expensive at scale)
-            # Example: when a future SDK adds "registry_sync", enable it here
-            # registry_sync: false
+            offline_features: true # offline store retrieval counters, latency, row count
+            audit_logging: false   # structured JSON audit logs via the feast.audit logger
         offlinePushBatching:
           enabled: true
           batchSize: 1000          # max rows per offline write batch

@@ -152,28 +152,71 @@ class ChatRequest(BaseModel):
     messages: List[ChatMessage]
 
 
-def _resolve_feature_counts(
+def _parse_feature_info(
     features: Union[List[str], "feast.FeatureService"],
 ) -> tuple:
-    """Return (feature_count, feature_view_count) from the resolved features.
+    """Return ``(feature_view_names, feature_count)`` from resolved features.
 
     ``features`` is either a list of ``"feature_view:feature"`` strings or
     a ``FeatureService`` with ``feature_view_projections``.
+
+    Returns:
+        (fv_names, feat_count) where fv_names is a list of unique feature
+        view name strings and feat_count is the total number of features.
     """
     from feast.feature_service import FeatureService
+    from feast.utils import _parse_feature_ref
 
     if isinstance(features, FeatureService):
         projections = features.feature_view_projections
-        fv_count = len(projections)
+        fv_names = [p.name for p in projections]
         feat_count = sum(len(p.features) for p in projections)
     elif isinstance(features, list):
         feat_count = len(features)
-        fv_names = {ref.split(":")[0].split("@")[0] for ref in features if ":" in ref}
-        fv_count = len(fv_names)
+        fv_names = list({_parse_feature_ref(ref)[0] for ref in features if ":" in ref})
     else:
+        fv_names = []
         feat_count = 0
-        fv_count = 0
-    return str(feat_count), str(fv_count)
+    return fv_names, feat_count
+
+
+def _resolve_feature_counts(
+    features: Union[List[str], "feast.FeatureService"],
+) -> tuple:
+    """Return ``(feature_count_str, feature_view_count_str)`` for Prometheus labels."""
+    fv_names, feat_count = _parse_feature_info(features)
+    return str(feat_count), str(len(fv_names))
+
+
+def _emit_online_audit(
+    request: GetOnlineFeaturesRequest,
+    features: Union[List[str], "feast.FeatureService"],
+    entity_count: int,
+    status: str,
+    latency_ms: float,
+):
+    """Best-effort audit log emission for online feature requests."""
+    try:
+        from feast.permissions.security_manager import get_security_manager
+
+        requestor_id = "anonymous"
+        sm = get_security_manager()
+        if sm and sm.current_user:
+            requestor_id = sm.current_user.username or "anonymous"
+
+        fv_names, feat_count = _parse_feature_info(features)
+
+        feast_metrics.emit_online_audit_log(
+            requestor_id=requestor_id,
+            entity_keys=list(request.entities.keys()),
+            entity_count=entity_count,
+            feature_views=fv_names,
+            feature_count=feat_count,
+            status=status,
+            latency_ms=latency_ms,
+        )
+    except Exception:
+        logger.warning("Failed to emit online audit log", exc_info=True)
 
 
 async def _get_features(
@@ -390,11 +433,22 @@ async def get_online_features(request: GetOnlineFeaturesRequest) -> Any:
                 include_feature_view_version_metadata=request.include_feature_view_version_metadata,
             )
 
-            if store._get_provider().async_supported.online.read:
-                response = await store.get_online_features_async(**read_params)  # type: ignore
-            else:
-                response = await run_in_threadpool(
-                    lambda: store.get_online_features(**read_params)  # type: ignore
+            audit_start_ms = time.monotonic() * 1000
+            audit_status = "success"
+            try:
+                if store._get_provider().async_supported.online.read:
+                    response = await store.get_online_features_async(**read_params)  # type: ignore
+                else:
+                    response = await run_in_threadpool(
+                        lambda: store.get_online_features(**read_params)  # type: ignore
+                    )
+            except Exception:
+                audit_status = "error"
+                raise
+            finally:
+                audit_latency_ms = time.monotonic() * 1000 - audit_start_ms
+                _emit_online_audit(
+                    request, features, entity_count, audit_status, audit_latency_ms
                 )
 
             response_dict = await run_in_threadpool(

@@ -82,6 +82,17 @@ class MetricsConfig(FeastConfigBaseModel):
     """Emit per-feature-view freshness gauges
     (feast_feature_freshness_seconds)."""
 
+    offline_features: StrictBool = True
+    """Emit offline store retrieval metrics
+    (feast_offline_store_request_total,
+    feast_offline_store_request_latency_seconds,
+    feast_offline_store_row_count)."""
+
+    audit_logging: StrictBool = False
+    """Emit structured JSON audit log entries for online and offline
+    feature requests via the ``feast.audit`` logger.  Captures requestor
+    identity, entity keys, feature views, row counts, and latency."""
+
 
 class BaseFeatureServerConfig(FeastConfigBaseModel):
     """Base Feature Server config that should be extended"""

@@ -11,9 +11,11 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+import logging
+import time
 import warnings
 from abc import ABC
-from datetime import datetime
+from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from typing import (
     TYPE_CHECKING,
@@ -70,6 +72,23 @@ def __init__(
         self.max_event_timestamp = max_event_timestamp
 
 
+def _extract_retrieval_metadata(job: "RetrievalJob") -> tuple:
+    """Return ``(feature_view_names, feature_count)`` from a RetrievalJob's metadata."""
+    from feast.utils import _parse_feature_ref
+
+    try:
+        meta = job.metadata
+        if meta:
+            feature_count = len(meta.features)
+            feature_views = list(
+                {_parse_feature_ref(ref)[0] for ref in meta.features if ":" in ref}
+            )
+            return feature_views, feature_count
+    except (NotImplementedError, AttributeError):
+        pass
+    return [], 0
+
+
 class RetrievalJob(ABC):
     """A RetrievalJob manages the execution of a query to retrieve data from the offline store."""
 
@@ -152,7 +171,51 @@ def to_arrow(
             validation_reference (optional): The validation to apply against the retrieved dataframe.
             timeout (optional): The query timeout if applicable.
         """
-        features_table = self._to_arrow_internal(timeout=timeout)
+        start_wall = time.monotonic()
+        status_label = "success"
+        row_count = 0
+        try:
+            features_table = self._to_arrow_internal(timeout=timeout)
+            row_count = features_table.num_rows
+        except Exception:
+            status_label = "error"
+            raise
+        finally:
+            try:
+                from feast import metrics as feast_metrics
+
+                elapsed = time.monotonic() - start_wall
+
+                if feast_metrics._config.offline_features:
+                    feast_metrics.offline_store_request_total.labels(
+                        method="to_arrow", status=status_label
+                    ).inc()
+                    feast_metrics.offline_store_request_latency_seconds.labels(
+                        method="to_arrow"
+                    ).observe(elapsed)
+                    feast_metrics.offline_store_row_count.labels(
+                        method="to_arrow"
+                    ).observe(row_count)
+
+                if feast_metrics._config.audit_logging:
+                    feature_views, feature_count = _extract_retrieval_metadata(self)
+                    end_dt = datetime.now(tz=timezone.utc)
+                    start_dt = end_dt - timedelta(seconds=elapsed)
+                    feast_metrics.emit_offline_audit_log(
+                        method="to_arrow",
+                        feature_views=feature_views,
+                        feature_count=feature_count,
+                        row_count=row_count,
+                        status=status_label,
+                        start_time=start_dt.isoformat(),
+                        end_time=end_dt.isoformat(),
+                        duration_ms=elapsed * 1000,
+                    )
+            except Exception:
+                logging.getLogger(__name__).debug(
+                    "Failed to record offline store metrics", exc_info=True
+                )
+
         if self.on_demand_feature_views:
             # Build a mapping of ODFV name to requested feature names
             # This ensures we only return the features that were explicitly requested