steampipe plugin install aws

Table: aws_rds_db_instance_metric_read_iops_daily - Query AWS RDS DBInstance using SQL

The AWS RDS DBInstance is a relational database service that provides you with six familiar database engines to choose from, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server. It is designed to provide a set of features to manage, scale, and operate relational databases in the cloud easily. The 'read_iops_daily' metric specifically provides insights into the average number of disk I/O operations per second for read operations in a day.

Table Usage Guide

The aws_rds_db_instance_metric_read_iops_daily table in Steampipe provides you with information about the daily read IOPS metrics of AWS RDS DBInstances. This table allows you, as a DevOps engineer, to query DBInstance-specific details, including the number of read I/O operations from the DBInstance per day. You can utilize this table to gather insights on DBInstance performance, such as identifying DBInstances that have a high read I/O operations rate, which could indicate potential performance bottlenecks. The schema outlines the various attributes of the DBInstance's daily read IOPS metrics for you, including the DBInstance identifier, timestamp of the metric, and the minimum, maximum, and average number of read IOPS.

The aws_rds_db_instance_metric_read_iops_daily table provides you with metric statistics at 24-hour intervals for the last year.

Examples

Basic info

Explore the daily read input/output operations (IOPS) metrics of your Amazon RDS database instances. This can help you understand the performance trends and capacity planning for your databases over time.

select
db_instance_identifier,
timestamp,
minimum,
maximum,
average,
sum,
sample_count
from
aws_rds_db_instance_metric_read_iops_daily
order by
db_instance_identifier,
timestamp;
select
db_instance_identifier,
timestamp,
minimum,
maximum,
average,
sum,
sample_count
from
aws_rds_db_instance_metric_read_iops_daily
order by
db_instance_identifier,
timestamp;

Intervals where volumes exceed 1000 average read ops

Identify instances where the daily average read operations on AWS RDS database instances exceed 1000. This can be useful in understanding and managing resource usage and performance.

select
db_instance_identifier,
timestamp,
minimum,
maximum,
average,
sum,
sample_count
from
aws_rds_db_instance_metric_read_iops_daily
where
average > 1000
order by
db_instance_identifier,
timestamp;
select
db_instance_identifier,
timestamp,
minimum,
maximum,
average,
sum,
sample_count
from
aws_rds_db_instance_metric_read_iops_daily
where
average > 1000
order by
db_instance_identifier,
timestamp;

Intervals where volumes exceed 8000 max read ops

This query is useful to identify periods when the read operations on your AWS RDS database instances exceed a certain threshold. It helps in monitoring and managing system performance, ensuring optimal resource utilization and preventing potential system overloads.

select
db_instance_identifier,
timestamp,
minimum,
maximum,
average,
sum,
sample_count
from
aws_rds_db_instance_metric_read_iops_daily
where
maximum > 8000
order by
db_instance_identifier,
timestamp;
select
db_instance_identifier,
timestamp,
minimum,
maximum,
average,
sum,
sample_count
from
aws_rds_db_instance_metric_read_iops_daily
where
maximum > 8000
order by
db_instance_identifier,
timestamp;

Read, Write, and Total IOPS

Explore the performance of your database by analyzing the average, maximum, and minimum input/output operations per second (IOPS) for both read and write operations. This query helps in understanding the IOPS trends and can be used for capacity planning and performance tuning.

select
r.db_instance_identifier,
r.timestamp,
round(r.average) + round(w.average) as iops_avg,
round(r.average) as read_ops_avg,
round(w.average) as write_ops_avg,
round(r.maximum) + round(w.maximum) as iops_max,
round(r.maximum) as read_ops_max,
round(w.maximum) as write_ops_max,
round(r.minimum) + round(w.minimum) as iops_min,
round(r.minimum) as read_ops_min,
round(w.minimum) as write_ops_min
from
aws_rds_db_instance_metric_read_iops_daily as r,
aws_rds_db_instance_metric_write_iops_daily as w
where
r.db_instance_identifier = w.db_instance_identifier
and r.timestamp = w.timestamp
order by
r.db_instance_identifier,
r.timestamp;
select
r.db_instance_identifier,
r.timestamp,
round(r.average) + round(w.average) as iops_avg,
round(r.average) as read_ops_avg,
round(w.average) as write_ops_avg,
round(r.maximum) + round(w.maximum) as iops_max,
round(r.maximum) as read_ops_max,
round(w.maximum) as write_ops_max,
round(r.minimum) + round(w.minimum) as iops_min,
round(r.minimum) as read_ops_min,
round(w.minimum) as write_ops_min
from
aws_rds_db_instance_metric_read_iops_daily as r,
aws_rds_db_instance_metric_write_iops_daily as w
where
r.db_instance_identifier = w.db_instance_identifier
and r.timestamp = w.timestamp
order by
r.db_instance_identifier,
r.timestamp;

Schema for aws_rds_db_instance_metric_read_iops_daily

NameTypeOperatorsDescription
_ctxjsonbSteampipe context in JSON form.
account_idtext=, !=, ~~, ~~*, !~~, !~~*The AWS Account ID in which the resource is located.
averagedouble precisionThe average of the metric values that correspond to the data point.
db_instance_identifiertextThe friendly name to identify the DB Instance.
maximumdouble precisionThe maximum metric value for the data point.
metric_nametextThe name of the metric.
minimumdouble precisionThe minimum metric value for the data point.
namespacetextThe metric namespace.
partitiontextThe AWS partition in which the resource is located (aws, aws-cn, or aws-us-gov).
regiontextThe AWS Region in which the resource is located.
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 standard unit for the data point.

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)" -- aws

You can pass the configuration to the command with the --config argument:

steampipe_export_aws --config '<your_config>' aws_rds_db_instance_metric_read_iops_daily