Table: gcp_compute_disk_metric_write_ops_daily - Query GCP Compute Engine Disk Metrics using SQL

Google Cloud's Compute Engine Disk is a block storage system for Google Compute Engine virtual machines. The compute engine disks provide persistent disk storage for instances in any zone or region. These disks are integrated with Google's infrastructure, ensuring data durability and security.

Table Usage Guide

The gcp_compute_disk_metric_write_ops_daily table provides insights into Compute Engine Disk Metrics within Google Cloud Platform (GCP). As a system administrator, you can explore disk-specific details through this table, including daily write operations count. Utilize it to uncover information about disk usage, such as those with high write operations, thereby allowing you to identify potential areas for efficiency improvements.

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

Examples

Basic info

Explore which Google Cloud Platform compute disk has the highest and lowest average daily write operations. This can help to identify instances where disks may be under or over-utilized, allowing for better resource allocation and performance optimization.

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

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

Intervals averaging over 100 write ops

Analyze the settings to understand which disks are experiencing a high average of write operations. This can be useful in identifying potential bottlenecks or performance issues in the system.

select
  name,
  round(minimum :: numeric, 2) as min_write_ops,
  round(maximum :: numeric, 2) as max_write_ops,
  round(average :: numeric, 2) as avg_write_ops,
  sample_count
from
  gcp_compute_disk_metric_write_ops_daily
where
  average > 10
order by
  name;

select
  name,
  round(minimum, 2) as min_write_ops,
  round(maximum, 2) as max_write_ops,
  round(average, 2) as avg_write_ops,
  sample_count
from
  gcp_compute_disk_metric_write_ops_daily
where
  average > 10
order by
  name;

Intervals averaging fewer than 1 write ops

Analyze the usage patterns of your Google Cloud Platform compute disk by identifying those instances where the average daily write operations fall below 1. This can help in optimizing resource allocation by pinpointing under-utilized disks.

select
  name,
  round(minimum :: numeric, 2) as min_write_ops,
  round(maximum :: numeric, 2) as max_write_ops,
  round(average :: numeric, 2) as avg_write_ops,
  sample_count
from
  gcp_compute_disk_metric_write_ops_daily
where
  average < 1
order by
  name;

select
  name,
  round(minimum, 2) as min_write_ops,
  round(maximum, 2) as max_write_ops,
  round(average, 2) as avg_write_ops,
  sample_count
from
  gcp_compute_disk_metric_write_ops_daily
where
  average < 1
order by
  name;

Query examples

compute_disk_top_10_write_ops_avg

Schema for gcp_compute_disk_metric_write_ops_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 disk.
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_disk_metric_write_ops_daily