Google Vertex AI Feature Store metrics

A Vertex AI feature store stores machine learning features and serves them to models at prediction time. The health of a feature store reflects both its serving metrics and the state that Google reports for it, such as stable, updating, or error. Ensure your cloud platform is configured in SolarWinds Observability SaaS to collect this service's data. See Add a GCP cloud account.

Many of the collected metrics from Vertex AI Feature Store entities are displayed as widgets in SolarWinds Observability explorers; additional metrics may be collected and available in the Metrics Explorer. You can also create an alert for when an entity's metric value moves out of a specific range. See Entities in SolarWinds Observability SaaS for information about entity types in SolarWinds Observability SaaS.

The following table lists some of the metrics collected for these entities. To see the Vertex AI Feature Store metrics in the Metrics Explorer, type aiplatform.googleapis.com/featurestore in the search box.

Metric	Unit	Description
sw.metrics.healthscore	Percent (%)	Health state. The health state provides real-time insight into the overall health and performance of your monitored entities. The health state is determined based on anomalies detected for the entity, alerts triggered for the entity's metrics, and the status of the entity. The health state is displayed as one of the following four states and colors: Good, Moderate, Bad, or Unknown. You can determine the impact of the alerts, anomalies, and statuses on the health of an entity type by going to Settings > Health, and selecting a specific entity type. You can also customize the impact. To view the health of Google Vertex AI Feature Store entities in the Metrics Explorer, filter the sw.metrics.healthscore metric by entity_types and select gcpvertexaifeaturestore.
gcp.aiplatform.googleapis.com. featurestore.onlineServing.requestCount	Count per second	Number of online serving requests to the feature store.
gcp.aiplatform.googleapis.com. featurestore.onlineServing.latencies	Milliseconds (ms)	Latency distribution for online serving requests to the feature store.
gcp.aiplatform.googleapis.com. featurestore.onlineServing.requestBytesCount	Bytes	Size of the online serving requests sent to the feature store.
gcp.aiplatform.googleapis.com. featurestore.onlineServing.responseSize	Bytes	Size of the online serving responses returned by the feature store.
gcp.aiplatform.googleapis.com. featurestore.cpuLoad	Scaled percentage	Average CPU load for a node in the feature store online storage.
gcp.aiplatform.googleapis.com. featurestore.cpuLoadHottestNode	Scaled percentage	CPU load for the busiest node in the feature store online storage.
gcp.aiplatform.googleapis.com. featurestore.nodeCount	Count	Number of nodes in the feature store online storage.
gcp.aiplatform.googleapis.com. featurestore.storage.storedBytes	Bytes	Bytes stored in the feature store online storage.
gcp.aiplatform.googleapis.com. featurestore.storage.billableProcessedBytes	Bytes	Number of bytes billed for offline data processed.
gcp.aiplatform.googleapis.com. featurestore.streamingWrite.offlineProcessedCount	Count per second	Number of streaming write requests processed for offline storage.