Table: gcp_compute_instance_metric_cpu_utilization - Query Google Cloud Compute Engine Instance Metrics using SQL

Google Cloud Compute Engine is a service within Google Cloud Platform that offers scalable and flexible virtual machine computing capabilities. It allows you to run large-scale workloads on virtual machines hosted on Google's infrastructure. Compute Engine instances can be tailored to specific workloads for optimal performance and cost efficiency.

Table Usage Guide

The gcp_compute_instance_metric_cpu_utilization table provides insights into the CPU utilization of Compute Engine Instances within Google Cloud Platform (GCP). As a system administrator or DevOps engineer, explore instance-specific details through this table, including CPU usage patterns, potential performance bottlenecks, and resource optimization opportunities. Utilize it to uncover information about instances, such as those with high CPU utilization, to make informed decisions about resource allocation and workload management.

Google Monitoring Metrics provide data about the performance of your systems. The gcp_compute_instance_metric_cpu_utilization table provides metric statistics at 5 minute intervals for the most recent 5 days.

Examples

Basic info

Explore the utilization of your Google Cloud Platform's compute instances over time. This query helps you understand the CPU usage patterns, including peaks and average usage, enabling you to optimize resource allocation and manage costs effectively.

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

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

CPU Over 80% average

Determine the areas in which the average CPU utilization exceeds 80%. This can be used to identify potential performance issues and ensure efficient 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
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
where
  average > 0.80
order by
  name,
  timestamp;

Schema for gcp_compute_instance_metric_cpu_utilization

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