Table: aws_rds_db_instance_metric_read_iops_hourly - Query AWS RDS DB Instances using SQL

The AWS RDS DB Instance is a part of Amazon's Relational Database Service that provides resizable capacity for an industry-standard relational database and manages common database administration tasks. It offers high availability and security, along with compatibility with several database engines, including MySQL, Oracle, and PostgreSQL. The 'aws_rds_db_instance_metric_read_iops_hourly' represents the Input/Output Operations Per Second (IOPS) for read operations on the DB instance, measured on an hourly basis.

Table Usage Guide

The aws_rds_db_instance_metric_read_iops_hourly table in Steampipe provides you with information about the read IOPS metrics for AWS Relational Database Service (RDS) DB instances on an hourly basis. This table enables you, as a DevOps engineer, database administrator, or other technical professional, to query read IOPS metrics. These can be useful for monitoring database performance, planning for capacity, and troubleshooting performance issues. The schema outlines various attributes of the read IOPS metrics for you, including the timestamp, average, maximum, and minimum read IOPS, as well as the standard deviation.

The aws_rds_db_instance_metric_read_iops_hourly table provides you with metric statistics at 1 hour intervals for the most recent 60 days.

Examples

Basic info

Analyze the performance of your AWS RDS database instances over time to optimize resource allocation and improve efficiency. This query helps you understand the input/output operations per second (IOPS) on an hourly basis, allowing for effective capacity planning and performance tuning.

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

Intervals where volumes exceed 1000 average read ops

Identify instances where the average read operations per second on your Amazon RDS database instances exceed 1000 within an hour. This can help you manage and optimize your database performance by pinpointing periods of high demand.

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

Intervals where volumes exceed 8000 max read ops

Discover the instances when the read operations on your AWS RDS database instances exceed a certain threshold, in this case, 8000 maximum read operations per hour. This can be particularly useful for identifying periods of high load or potential performance issues.

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

Intervals where volume average iops exceeds provisioned iops

Determine the instances where the average input/output operations per second (IOPS) exceeds the provisioned IOPS for your Amazon RDS database instances. This can help you identify periods of high load, enabling you to better plan for capacity and avoid potential performance issues.

select
  r.db_instance_identifier,
  r.timestamp,
  v.iops as provisioned_iops,
  round(r.average) + round(w.average) as iops_avg,
  round(r.average) as read_ops_avg,
  round(w.average) as write_ops_avg
from
  aws_rds_db_instance_metric_read_iops_hourly as r,
  aws_rds_db_instance_metric_write_iops_hourly as w,
  aws_rds_db_instance as v
where
  r.db_instance_identifier = w.db_instance_identifier
  and r.timestamp = w.timestamp
  and v.db_instance_identifier = r.db_instance_identifier
  and r.average + w.average > v.iops
order by
  r.db_instance_identifier,
  r.timestamp;

select
  r.db_instance_identifier,
  r.timestamp,
  v.iops as provisioned_iops,
  round(r.average) + round(w.average) as iops_avg,
  round(r.average) as read_ops_avg,
  round(w.average) as write_ops_avg
from
  aws_rds_db_instance_metric_read_iops_hourly as r
  join aws_rds_db_instance_metric_write_iops_hourly as w on r.db_instance_identifier = w.db_instance_identifier
  and r.timestamp = w.timestamp
  join aws_rds_db_instance as v on v.db_instance_identifier = r.db_instance_identifier
where
  r.average + w.average > v.iops
order by
  r.db_instance_identifier,
  r.timestamp;

Read, Write, and Total IOPS

Analyze the input/output operations per second (IOPS) for your AWS RDS database instances to understand their read and write performance over time. This can help in optimizing resources and planning for capacity needs.

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_hourly as r,
  aws_rds_db_instance_metric_write_iops_hourly 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_hourly as r,
  aws_rds_db_instance_metric_write_iops_hourly as w
where
  r.db_instance_identifier = w.db_instance_identifier
  and r.timestamp = w.timestamp
order by
  r.db_instance_identifier,
  r.timestamp;

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_hourly