Table: gcp_sql_database_instance_metric_connections_daily - Query GCP SQL Database Instance Metrics using SQL

Google Cloud SQL is a fully-managed database service that makes it easy to set up, maintain, manage, and administer your relational databases on Google Cloud Platform. You can use Cloud SQL with MySQL, PostgreSQL, or SQL Server. The service provides detailed metrics on database instances, including connection metrics, to help monitor the health and performance of your databases.

Table Usage Guide

The gcp_sql_database_instance_metric_connections_daily table provides insights into daily connection metrics for Google Cloud SQL instances. As a database administrator, you can explore instance-specific details through this table, including the number of established connections, aborted connections, and failed connection attempts. Use it to monitor database connection patterns, identify potential anomalies, and optimize your database performance.

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

Examples

Basic info

Analyze the daily connection metrics of Google Cloud SQL database instances to gain insights into their usage patterns. This could be useful for capacity planning and performance optimization.

select
  instance_id,
  minimum,
  maximum,
  average,
  sample_count
from
  gcp_sql_database_instance_metric_connections_daily
order by
  instance_id;

select
  instance_id,
  minimum,
  maximum,
  average,
  sample_count
from
  gcp_sql_database_instance_metric_connections_daily
order by
  instance_id;

Intervals averaging over 100 connections

Explore which Google Cloud SQL database instances have an average daily connection count exceeding 100. This is useful for identifying potentially over-utilized instances that may require capacity scaling or performance optimization.

select
  instance_id,
  round(minimum :: numeric, 2) as min_connection,
  round(maximum :: numeric, 2) as max_connection,
  round(average :: numeric, 2) as avg_connection,
  sample_count
from
  gcp_sql_database_instance_metric_connections_daily
where
  average > 100
order by
  instance_id;

select
  instance_id,
  round(minimum, 2) as min_connection,
  round(maximum, 2) as max_connection,
  round(average, 2) as avg_connection,
  sample_count
from
  gcp_sql_database_instance_metric_connections_daily
where
  average > 100
order by
  instance_id;

Intervals averaging fewer than 10 connections

Analyze the settings to understand the performance of your Google Cloud SQL Database instances, specifically those that average fewer than 10 connections daily. This can be beneficial in identifying underutilized instances and optimizing resource allocation.

select
  instance_id,
  round(minimum :: numeric, 2) as min_connection,
  round(maximum :: numeric, 2) as max_connection,
  round(average :: numeric, 2) as avg_connection,
  sample_count
from
  gcp_sql_database_instance_metric_connections_daily
where
  average < 10
order by
  instance_id;

select
  instance_id,
  round(minimum, 2) as min_connection,
  round(maximum, 2) as max_connection,
  round(average, 2) as avg_connection,
  sample_count
from
  gcp_sql_database_instance_metric_connections_daily
where
  average < 10
order by
  instance_id;

Schema for gcp_sql_database_instance_metric_connections_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.
instance_id	text		The ID of the instance.
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.
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_sql_database_instance_metric_connections_daily