Use data_product config for metric discovery instead of filter_tag in webapp

connectors/openmetadata/enricher.py

@@ -340,6 +340,35 @@ class CatalogEnricher:
             logger.warning(f"Failed to fetch metrics from catalog: {e}")
             return []
 
+    def get_metrics_by_data_product(self, data_product_name: str, limit: int = 200) -> List[Dict[str, Any]]:
+        """
+        Fetch metrics belonging to a specific data product.
+
+        Preferred over get_metrics() + tag filter when data_product is configured,
+        as it returns exactly the metrics in the data product regardless of tags.
+
+        Returns empty list if enricher disabled, catalog unavailable, or on error.
+        Never raises exception (graceful degradation).
+        """
+        if not self.enabled or not self._client:
+            return []
+
+        try:
+            cache_key = f"__metrics_dp_{data_product_name}__"
+            cached = self._get_from_cache(cache_key)
+            if cached is not None:
+                logger.debug(f"Catalog cache hit: metrics for data product '{data_product_name}'")
+                return cached
+
+            metrics = self._client.search_by_data_product(data_product_name, entity_type="metric", limit=limit)
+            self._cache_entry(cache_key, metrics)
+            logger.info(f"Loaded {len(metrics)} metrics from data product '{data_product_name}'")
+            return metrics
+
+        except Exception as e:
+            logger.warning(f"Failed to fetch metrics for data product '{data_product_name}': {e}")
+            return []
+
     def clear_cache(self):
         """Manually clear all cached entries."""
         self._cache.clear()

webapp/app.py

@@ -83,6 +83,7 @@ logger = logging.getLogger(__name__)
 # Global catalog enricher (initialized in create_app)
 _catalog_enricher = None
 _catalog_filter_tag = ""
+_catalog_data_product = ""
 
 
 def get_git_commit_hash() -> str:
@@ -124,11 +125,14 @@ def create_app() -> Flask:
             _catalog_enricher = CatalogEnricher(instance_config)
             if _catalog_enricher.enabled:
                 logger.info("OpenMetadata catalog enricher initialized")
-            # Store filter tag for metric filtering
+            # Store metric discovery config
-            global _catalog_filter_tag
+            global _catalog_filter_tag, _catalog_data_product
             om_config = instance_config.get("openmetadata", {})
+            _catalog_data_product = om_config.get("data_product", "").strip()
             _catalog_filter_tag = om_config.get("filter_tag", "").strip()
-            if _catalog_filter_tag:
+            if _catalog_data_product:
+                logger.info(f"Catalog metric discovery: data product '{_catalog_data_product}'")
+            elif _catalog_filter_tag:
                 logger.info(f"Catalog metric filter tag: {_catalog_filter_tag}")
         except Exception as e:
             logger.warning(f"Failed to initialize catalog enricher: {e}")
@@ -722,19 +726,21 @@ def _load_metrics_from_catalog() -> list:
         return []
 
     try:
-        # Fetch metrics from catalog
+        # Fetch metrics - prefer data product filter, fall back to tag filter
-        raw_metrics = _catalog_enricher.get_metrics()
+        if _catalog_data_product:
+            raw_metrics = _catalog_enricher.get_metrics_by_data_product(_catalog_data_product)
+        else:
+            raw_metrics = _catalog_enricher.get_metrics()
+            if _catalog_filter_tag and _TRANSFORMER_AVAILABLE:
+                raw_metrics = [
+                    m for m in raw_metrics
+                    if _transformer_has_tag(m.get("tags", []), _catalog_filter_tag)
+                ]
+
         if not raw_metrics:
             logger.debug("No metrics found in catalog")
             return []
 
-        # Filter by tag if configured
-        if _catalog_filter_tag and _TRANSFORMER_AVAILABLE:
-            raw_metrics = [
-                m for m in raw_metrics
-                if _transformer_has_tag(m.get("tags", []), _catalog_filter_tag)
-            ]
-
         # Parse each metric and group by category
         categories = {}
         for raw in raw_metrics: