steampipe plugin install gcp

Table: gcp_compute_disk_metric_read_ops_daily - Query GCP Compute Disk Metrics using SQL

Google Cloud Compute Disks are persistent, high-performance block storage for Google Cloud's virtual machines (VMs). These disks are designed to offer reliable and efficient storage for your VMs, with the added benefit of easy integration with Google Cloud's suite of data management tools. They are suitable for both boot and non-boot purposes, and come in a variety of types to suit different needs.

Table Usage Guide

The gcp_compute_disk_metric_read_ops_daily table provides insights into Compute Disk Metrics within Google Cloud Platform. As a system administrator, explore disk-specific details through this table, such as daily read operations count, to monitor disk usage patterns and identify potential anomalies. Utilize it to uncover information about disks, such as those with high read operations, suggesting high disk usage and potential need for resource optimization.

GCP Monitoring metrics provide data about the performance of your systems. The gcp_compute_disk_metric_read_ops_daily table provides metric statistics at 24 hour intervals for the last year.

Examples

Basic info

Explore the daily read operations of your Google Cloud Platform compute disk. This query helps you understand the operational range and average count, allowing you to optimize disk usage and performance.

select
name,
minimum,
maximum,
average,
sample_count
from
gcp_compute_disk_metric_read_ops_daily
order by
name;
select
name,
minimum,
maximum,
average,
sample_count
from
gcp_compute_disk_metric_read_ops_daily
order by
name;

Intervals averaging over 100 read ops

Explore which disk operations in your GCP Compute environment are averaging over 100 read operations, allowing you to identify potential bottlenecks and optimize for better performance. This can be particularly useful in identifying high-usage disks that may need additional resources or configuration changes.

select
name,
round(minimum :: numeric, 2) as min_read_ops,
round(maximum :: numeric, 2) as max_read_ops,
round(average :: numeric, 2) as avg_read_ops,
sample_count
from
gcp_compute_disk_metric_read_ops_daily
where
average > 10
order by
name;
select
name,
round(minimum, 2) as min_read_ops,
round(maximum, 2) as max_read_ops,
round(average, 2) as avg_read_ops,
sample_count
from
gcp_compute_disk_metric_read_ops_daily
where
average > 10
order by
name;

Intervals averaging fewer than 10 read ops

Analyze the settings to understand the performance of your GCP compute disks, specifically those with an average of fewer than 10 read operations. This can help in identifying underutilized resources and optimizing your storage configuration.

select
name,
round(minimum :: numeric, 2) as min_read_ops,
round(maximum :: numeric, 2) as max_read_ops,
round(average :: numeric, 2) as avg_read_ops,
sample_count
from
gcp_compute_disk_metric_read_ops_daily
where
average < 1
order by
name;
select
name,
round(minimum, 2) as min_read_ops,
round(maximum, 2) as max_read_ops,
round(average, 2) as avg_read_ops,
sample_count
from
gcp_compute_disk_metric_read_ops_daily
where
average < 1
order by
name;

Schema for gcp_compute_disk_metric_read_ops_daily

NameTypeOperatorsDescription
_ctxjsonbSteampipe context in JSON form, e.g. connection_name.
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 disk.
projecttextThe 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.
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_disk_metric_read_ops_daily