Configure the Prometheus receiver to collect Pinecone metrics
Collect Pinecone metrics with the Splunk Distribution of the OpenTelemetry Collector.
You can monitor the performance of your Pinecone vector database by configuring the Splunk Distribution of the OpenTelemetry Collector to send Pinecone metrics to Splunk Observability Cloud.
This solution uses the Prometheus receiver to collect metrics from Pinecone, which exposes the API endpoint https://api.pinecone.io/prometheus/projects/PROJECT_ID/metrics/discovery to publish Prometheus-compatible metrics.
To configure the Prometheus receiver to collect Pinecone metrics, you must meet the following requirements.
You have a standard or enterprise Pinecone plan. For more information, see Pricing on the Pinecone website.
If you're using Pinecone Bring your own cloud, you must configure Prometheus monitoring within your VPC. For instructions, see Monitor with Prometheus in the Pinecone documentation.
- Deploy the Splunk Distribution of the OpenTelemetry Collector to your host or container platform:
- To activate the Prometheus receiver for Pinecone manually in the Collector configuration, make the following changes to your
values.yamlconfiguration file. - Restart the Splunk Distribution of the OpenTelemetry Collector.
Configuration settings
Learn about the configuration settings for the Prometheus receiver.
To view the configuration options for the Prometheus receiver, see Settings.
Metrics
The following metrics are available for Pinecone. These metrics fall under the default metric category. For more information on these metrics, see Available metrics in the Pinecone documentation.
| Metric name | Type | Description |
|---|---|---|
pinecone_db_record_total | gauge | The total number of records in the index. |
pinecone_db_op_upsert_total | counter | The number of upsert requests made to an index. |
pinecone_db_op_upsert_duration_total | counter | The total time taken processing upsert requests for an index in milliseconds. |
pinecone_db_op_query_total | counter | The number of query requests made to an index. |
pinecone_db_op_query_duration_total | counter | The total time taken processing query requests for an index in milliseconds. |
pinecone_db_op_fetch_total | counter | The number of fetch requests made to an index. |
pinecone_db_op_fetch_duration_total | counter | The total time taken processing fetch requests for an index in milliseconds. |
pinecone_db_op_update_total | counter | The number of update requests made to an index. |
pinecone_db_op_update_duration_total | counter | The total time taken processing update requests for an index in milliseconds. |
pinecone_db_op_delete_total | counter | The number of delete requests made to an index. |
pinecone_db_op_delete_duration_total | counter | The total time taken processing delete requests for an index in milliseconds. |
pinecone_db_write_unit_total | counter | The total number of write units consumed by an index. |
pinecone_db_read_unit_total | counter | The total number of read units consumed by an index. |
pinecone_db_storage_size_bytes | gauge | The total size of the index in bytes. |
Attributes
The following resource attributes are available for Pinecone.
| Attribute name | Description |
|---|---|
index_name | Name of the index to which the metric applies. |
cloud | Cloud where the index is deployed: aws, gcp, or azure. |
region | Region where the index is deployed. |
capacity_mode | Type of index: serverless or byoc. |
Next steps
After you set up data collection from Pinecone, the data populates built-in dashboards that you can use to monitor and troubleshoot Pinecone vector databases.
For more information on using built-in dashboards in Splunk Observability Cloud, see: