Table: gcp_sql_database_instance_metric_connections_hourly - Query GCP SQL Database Instances using SQL

A Google Cloud SQL Database Instance is a fully-managed relational database service in Google Cloud. It offers easy-to-use, scalable database instances that support applications of any size. It provides high performance, scalability, and convenience with features such as automated backups, replication, and failover.

Table Usage Guide

The gcp_sql_database_instance_metric_connections_hourly table provides insights into the hourly metric connections of Google Cloud SQL Database Instances. As a database administrator or a DevOps engineer, you can use this table to monitor and analyze connection patterns, which can help in identifying potential issues and optimizing database performance. This table is particularly useful for tracking connection trends, identifying peak usage times, and planning capacity.

GCP Monitoring metrics provide data about the performance of your systems. The gcp_sql_database_instance_metric_connections_hourly table provides metric statistics at 1 hour intervals for the most recent 60 days.

Examples

Basic info

Explore the varying connection metrics of Google Cloud SQL databases to understand their performance over time. This can assist in identifying potential issues or areas for optimization based on the minimum, maximum, and average connections.

select
  instance_id,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  gcp_sql_database_instance_metric_connections_hourly
order by
  instance_id;

select
  instance_id,
  timestamp,
  minimum,
  maximum,
  average,
  sample_count
from
  gcp_sql_database_instance_metric_connections_hourly
order by
  instance_id;

Intervals averaging over 100 connections

Explore instances where database connections average over 100 per hour, offering insights into potential high-traffic periods or potential performance issues. This could be crucial for capacity planning, load balancing and optimizing database performance.

select
  instance_id,
  timestamp,
  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_hourly
where
  average > 100
order by
  instance_id;

select
  instance_id,
  timestamp,
  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_hourly
where
  average > 100
order by
  instance_id;

Intervals averaging fewer than 10 connections

Explore which instances are maintaining an average connection count of less than 10. This is useful for identifying underutilized resources and optimizing your database for cost efficiency.

select
  instance_id,
  timestamp,
  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_hourly
where
  average < 10
order by
  instance_id;

select
  instance_id,
  timestamp,
  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_hourly
where
  average < 10
order by
  instance_id;

Schema for gcp_sql_database_instance_metric_connections_hourly

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_hourly