Table: gcp_compute_instance_metric_cpu_utilization_daily - Query GCP Compute Engine Instances using SQL

Google Cloud Compute Engine is a service that provides secure and customizable compute instances that can be used to build and host your applications. These instances are highly scalable and flexible, offering a variety of machine types to suit your needs. Compute Engine instances can be managed through the Google Cloud Console, the RESTful API, or the command-line interface.

Table Usage Guide

The gcp_compute_instance_metric_cpu_utilization_daily table provides insights into the daily CPU utilization metrics of Google Cloud Compute Engine instances. As a system administrator or a DevOps engineer, you can explore instance-specific details through this table, including the CPU usage patterns, to manage and optimize resource allocation effectively. Use this table to monitor the performance of your instances, identify those with high CPU usage, and make informed decisions about scaling your resources.

GCP Monitoring Metrics provide data about the performance of your systems. The gcp_compute_instance_metric_cpu_utilization_daily table provides metric statistics at 24 hour intervals for the most recent 5 days.

Examples

Basic info

Analyze the daily CPU utilization metrics of your Google Cloud Compute instances to gain insights into usage patterns and performance. This can be particularly useful for capacity planning, identifying resource-intensive instances, and optimizing costs.

select
  name,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  gcp_compute_instance_metric_cpu_utilization_daily
order by
  name,
  timestamp;

select
  name,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  gcp_compute_instance_metric_cpu_utilization_daily
order by
  name,
  timestamp;

CPU Over 80% average

Analyze the instances where CPU utilization exceeds 80% on average. This query can help in identifying potential performance issues and ensuring optimal resource allocation.

select
  name,
  timestamp,
  round(minimum :: numeric, 2) as min_cpu,
  round(maximum :: numeric, 2) as max_cpu,
  round(average :: numeric, 2) as avg_cpu,
  sample_count
from
  gcp_compute_instance_metric_cpu_utilization_daily
where
  average > 0.80
order by
  name,
  timestamp;

select
  name,
  timestamp,
  round(minimum, 2) as min_cpu,
  round(maximum, 2) as max_cpu,
  round(average, 2) as avg_cpu,
  sample_count
from
  gcp_compute_instance_metric_cpu_utilization_daily
where
  average > 0.80
order by
  name,
  timestamp;

Query examples

Schema for gcp_compute_instance_metric_cpu_utilization_daily

Name	Type	Operators	Description
_ctx	jsonb		Steampipe context in JSON form.
average	double precision		The average of the metric values that correspond to the data point.
location	text		The GCP multi-region, region, or zone in which the resource is located.
maximum	double precision		The maximum metric value for the data point.
metadata	jsonb		The associated monitored resource metadata.
metric_kind	text		The metric type.
metric_labels	jsonb		The set of label values that uniquely identify this metric.
metric_type	text		The associated metric. A fully-specified metric used to identify the time series.
minimum	double precision		The minimum metric value for the data point.
name	text	=	The name of the instance.
project	text	=, !=, ~~, ~~, !~~, !~~	The GCP Project in which the resource is located.
resource	jsonb		The associated monitored resource.
sample_count	double precision		The number of metric values that contributed to the aggregate value of this data point.
sp_connection_name	text	=, !=, ~~, ~~, !~~, !~~	Steampipe connection name.
sp_ctx	jsonb		Steampipe context in JSON form.
sum	double precision		The sum of the metric values for the data point.
timestamp	timestamp with time zone		The time stamp used for the data point.
unit	text		The data points of this time series. When listing time series, points are returned in reverse time order.When creating a time series, this field must contain exactly one point and the point's type must be the same as the value type of the associated metric. If the associated metric's descriptor must be auto-created, then the value type of the descriptor is determined by the point's type, which must be BOOL, INT64, DOUBLE, or DISTRIBUTION.

Export

This table is available as a standalone Exporter CLI. Steampipe exporters are stand-alone binaries that allow you to extract data using Steampipe plugins without a database.

You can download the tarball for your platform from the Releases page, but it is simplest to install them with the steampipe_export_installer.sh script:

/bin/sh -c "$(curl -fsSL https://steampipe.io/install/export.sh)" -- gcp

You can pass the configuration to the command with the --config argument:

steampipe_export_gcp --config '<your_config>' gcp_compute_instance_metric_cpu_utilization_daily