Learn about the Wavefront Google Cloud Bigtable 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.

Dashboards

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

Alerts

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

images/alert_condition.png

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.bigtable.backup.bytes_used Backup storage used in bytes.
gcp.bigtable.cluster.cluster.autoscaling.max_node_count Maximum number of nodes in an autoscaled cluster.
gcp.bigtable.cluster.cluster.autoscaling.min_node_count Minimum number of nodes in an autoscaled cluster.
gcp.bigtable.cluster.cluster.autoscaling.recommended_node_count_for_cpu Recommended number of nodes in an autoscaled cluster based on CPU usage.
gcp.bigtable.cluster.cluster.autoscaling.recommended_node_count_for_storage Recommended number of nodes in an autoscaled cluster based on storage usage.
gcp.bigtable.cluster.cpu_load CPU load of a cluster.
gcp.bigtable.cluster.cpu_load_by_app_profile_by_method_by_table CPU load of a cluster split by app profile, method, and table.
gcp.bigtable.cluster.cpu_load_hottest_node CPU load of the busiest node in a cluster.
gcp.bigtable.cluster.disk_load Utilization of the HDD disks in a cluster.
gcp.bigtable.cluster.node_count Number of nodes in a cluster.
gcp.bigtable.cluster.storage_utilization Storage used as a fraction of the total storage capacity.
gcp.bigtable.disk.bytes_used Amount of compressed data for tables stored in a cluster.
gcp.bigtable.disk.per_node_storage_capacity Capacity of compressed data for tables that can be stored per node in the cluster.
gcp.bigtable.disk.storage_capacity Capacity of compressed data for tables that can be stored in a cluster.
gcp.bigtable.replication.latency Distribution of replication request latencies for a table. Includes only requests that have been received by the destination cluster.
gcp.bigtable.replication.max_delay Upper bound for replication delay between clusters of a table.
gcp.bigtable.server.error_count Number of server requests for a table that failed with an error.
gcp.bigtable.server.latencies Distribution of server request latencies for a table, measured when calls reach Cloud Bigtable.
gcp.bigtable.server.modified_rows_count Number of rows modified by server requests for a table.
gcp.bigtable.server.multi_cluster_failovers_count Number of failovers during multi-cluster requests.
gcp.bigtable.server.received_bytes_count Number of uncompressed bytes of request data received by servers for a table.
gcp.bigtable.server.request_count Number of server requests for a table.
gcp.bigtable.server.returned_rows_count Number of rows returned by server requests for a table.
gcp.bigtable.server.sent_bytes_count Number of uncompressed bytes of response data sent by servers for a table.
gcp.bigtable.table.bytes_used Amount of compressed data stored in a table.
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