Learn about the Wavefront Google Cloud Spanner Integration.

Google Cloud Platform Integration

The Google Cloud Platform integration is full-featured native integration offering agentless data ingestion of GCP metric data, as well as pre-defined dashboards and alert conditions for certain GCP services.

Metrics Configuration

Wavefront ingests Google Cloud Platform metrics using the v3 Stackdriver Monitoring APIs. For details on the metrics, see the metrics documentation.

Metrics originating from Google Cloud Platform are prefixed with gcp. within Wavefront. Once the integration has been set up, you can browse the available GCP metrics in the metrics browser.


Wavefront provides Google Cloud Platform dashboards for the following services:

  • Google App Engine
  • Google BigQuery
  • Google Cloud Bigtable
  • Google Cloud Billing
  • Google Cloud Datastore
  • Google Cloud Dataproc
  • Google Cloud Functions
  • Google Cloud Logging
  • Google Cloud Pub/Sub
  • Google Cloud Router
  • Google Cloud Spanner
  • Google Cloud Storage
  • Google Cloud VPN
  • Google Compute Engine
  • Google Container Engine
  • Google Firebase
  • Google Kubernetes Engine
  • Google ML Engine


The Google Cloud Platform integration dashboard contains predefined alert conditions. These conditions are embedded as queries in the dashboard’s charts. For example:


To create the alert, click the Create Alert link under the query and configure the alert properties (notification targets, condition checking frequency, etc.).

Google Cloud Platform Integration

Add a GCP Integration

Adding a Google Cloud Platform (GCP) integration requires establishing a trust relationship between GCP and Tanzu Observability by Wavefront. Minimum required permissions you need depend on the services that you are using. See Google Cloud Platform Overview and Permissions for details.

The overall process involves the following:

  • Creating a service account
  • Giving that account viewer privileges
  • Downloading a JSON private key

To register a Google Cloud Platform integration:

  1. In the Name text box, enter a meaningful name.
  2. In the JSON key text box, enter your JSON key to give read-only access to a GCP project. Note: The JSON key is securely stored and never exposed except for read-only access to the GCP APIs.
  3. (Optional) Select the categories to fetch.
  4. (Optional) In the Metric Allow List text box, you can add metrics to an allow list by entering a regular expression.

    For example, to monitor all the CPU metrics coming from the Compute Engine, enter ^gcp.compute.instance.cpu.*$.

  5. (Optional) In the Additional Metric Prefixes text box, enter a comma separated list of additional metrics prefixes. The metrics names that start with these prefixes will be imported in addition to what you have selected as categories.
  6. (Optional) Change the Service Refresh Rate. The default is 5 minutes.
  7. (Optional) Select to enable Detailed Histogram Metrics, Delta Counts, and Pricing & Billing information. Note: Enabling Detailed Histogram Metrics and Delta Counts will increase your ingestion rate and costs.

    If you select to enable the Pricing & Billing information, you must also provide an API key.

  8. Click Register.
Metric Name Description
gcp.spanner.api.api_request_count The Cloud Spanner API requests.
gcp.spanner.api.received_bytes_count The uncompressed request bytes received by Cloud Spanner.
gcp.spanner.api.request_count The rate of Cloud Spanner API requests.
gcp.spanner.api.request_latencies The distribution of server request latencies for a database. This includes latency of request processing in Cloud Spanner backends and API layer. It does not include network or reverse-proxy overhead between clients and servers.
gcp.spanner.api.sent_bytes_count The uncompressed response bytes sent by Cloud Spanner.
gcp.spanner.instance.backup.used_bytes The backup storage used in bytes.
gcp.spanner.instance.cpu.smoothed_utilization The 24-hour smoothed utilization of provisioned CPU.
gcp.spanner.instance.cpu.utilization The percent utilization of provisioned CPU.
gcp.spanner.instance.cpu.utilization_by_operation_type The percent utilization of provisioned CPU, by operation type. Currently, it does not include CPU utilization for system tasks.
gcp.spanner.instance.cpu.utilization_by_priority The percent utilization of provisioned CPU, by priority.
gcp.spanner.instance.leader_percentage_by_region The percentage of leaders by cloud region.
gcp.spanner.instance.node_count The total number of nodes.
gcp.spanner.instance.processing_units The total number of processing units.
gcp.spanner.instance.session_count The number of sessions in use.
gcp.spanner.instance.storage.limit_bytes The storage limit for instance in bytes.
gcp.spanner.instance.storage.limit_bytes_per_processing_unit The storage limit per processing unit in bytes.
gcp.spanner.instance.storage.used_bytes The storage used in bytes.
gcp.spanner.instance.storage.utilization The storage used as a fraction of storage limit.
gcp.spanner.lock_stat.total.lock_wait_time The total lock wait time for lock conflicts recorded for the entire database.
gcp.spanner.query_count The count of queries by database name, status, query type, and used optimizer version.
gcp.spanner.query_stat.total.bytes_returned_count The number of data bytes that the queries returned, excluding transmission encoding overhead.
gcp.spanner.query_stat.total.cpu_time The number of seconds of CPU time Cloud Spanner spent on operations to execute the queries.
gcp.spanner.query_stat.total.execution_count The number of times Cloud Spanner saw queries during the interval.
gcp.spanner.query_stat.total.failed_execution_count The number of times queries failed during the interval.
gcp.spanner.query_stat.total.query_latencies The distribution of total length of time, in seconds, for query executions within the database.
gcp.spanner.query_stat.total.returned_rows_count The number of rows that the queries returned.
gcp.spanner.query_stat.total.scanned_rows_count The number of rows that the queries scanned excluding deleted values.
gcp.spanner.read_stat.total.bytes_returned_count The total number of data bytes that the reads returned excluding transmission encoding overhead.
gcp.spanner.read_stat.total.client_wait_time The number of seconds spent waiting due to throttling.
gcp.spanner.read_stat.total.cpu_time The number of seconds of CPU time Cloud Spanner spent execute the reads excluding prefetch CPU and other overhead.
gcp.spanner.read_stat.total.execution_count The number of times Cloud Spanner executed the read shapesduring the interval.
gcp.spanner.read_stat.total.leader_refresh_delay The number of seconds spent coordinating reads across instances in multi-regionconfigurations.
gcp.spanner.read_stat.total.locking_delays The distribution of total time in seconds spent waiting due to locking.
gcp.spanner.read_stat.total.returned_rows_count The number of rows that the reads returned.
gcp.spanner.row_deletion_policy.deleted_rows_count Count of rows deleted by the policy since the last sample.
gcp.spanner.row_deletion_policy.processed_watermark_age The time between now and the read timestamp of the last successful execution.
gcp.spanner.row_deletion_policy.undeletable_rows The number of rows in all tables in the database that can’t be deleted.
gcp.spanner.transaction_stat.total.bytes_written_count The number of bytes written by transactions.
gcp.spanner.transaction_stat.total.commit_attempt_count The number of commit attempts for transactions.
gcp.spanner.transaction_stat.total.commit_retry_count The number of commit attempts that are retries from previously aborted transaction attempts.
gcp.spanner.transaction_stat.total.participants The distribution of total number of participants in each commit attempt.
gcp.spanner.transaction_stat.total.transaction_latencies The distribution of total seconds takenfrom the first operation of the transaction to commit or abort.