steampipe plugin install gcp

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

NameTypeOperatorsDescription
_ctxjsonbSteampipe context in JSON form.
averagedouble precisionThe average of the metric values that correspond to the data point.
locationtextThe GCP multi-region, region, or zone in which the resource is located.
maximumdouble precisionThe maximum metric value for the data point.
metadatajsonbThe associated monitored resource metadata.
metric_kindtextThe metric type.
metric_labelsjsonbThe set of label values that uniquely identify this metric.
metric_typetextThe associated metric. A fully-specified metric used to identify the time series.
minimumdouble precisionThe minimum metric value for the data point.
nametext=The name of the instance.
projecttext=, !=, ~~, ~~*, !~~, !~~*The GCP Project in which the resource is located.
resourcejsonbThe associated monitored resource.
sample_countdouble precisionThe number of metric values that contributed to the aggregate value of this data point.
sp_connection_nametext=, !=, ~~, ~~*, !~~, !~~*Steampipe connection name.
sp_ctxjsonbSteampipe context in JSON form.
sumdouble precisionThe sum of the metric values for the data point.
timestamptimestamp with time zoneThe time stamp used for the data point.
unittextThe 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