Table: aws_ebs_volume_metric_read_ops_hourly - Query Amazon EC2 EBS Volume using SQL

The AWS EBS (Elastic Block Store) Volume is a high-performance block storage service designed for use with Amazon Elastic Compute Cloud (EC2) for both throughput and transaction intensive workloads at any scale. It offers a range of volume types that are optimized to handle different workloads, including those that require high performance like transactional workloads, and those that require low cost per gigabyte like data warehousing. EBS Volumes are highly available and reliable storage volumes that can be attached to any running instance that is in the same Availability Zone.

Table Usage Guide

The aws_ebs_volume_metric_read_ops_hourly table in Steampipe provides you with information about the read operations metrics of Amazon Elastic Block Store (EBS) volumes within Amazon Elastic Compute Cloud (EC2). This table allows you, as a DevOps engineer, to query volume-specific read operations details on an hourly basis, including the number of completed read operations from a volume, average, maximum, and minimum read operations, and the count of data points used for the statistical calculation. You can utilize this table to gather insights on volume performance, monitor the read activity of EBS volumes, and make data-driven decisions for performance optimization. The schema outlines the various attributes of the EBS volume read operations metrics for you, including the volume ID, timestamp, average read operations, and more.

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

Examples

Basic info

Explore the performance of your AWS EBS volume over time. This query allows you to track the number of read operations per hour, helping you to understand usage patterns and optimize resource allocation.

select
  volume_id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  aws_ebs_volume_metric_read_ops_hourly
order by
  volume_id,
  timestamp;

select
  volume_id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  aws_ebs_volume_metric_read_ops_hourly
order by
  volume_id,
  timestamp;

Intervals where volumes exceed 1000 average read ops

Identify instances where the average read operations on AWS EBS volumes exceed 1000. This can be useful in monitoring and managing resource utilization, helping to optimize performance and prevent potential bottlenecks.

select
  volume_id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  aws_ebs_volume_metric_read_ops_hourly
where
  average > 1000
order by
  volume_id,
  timestamp;

select
  volume_id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  aws_ebs_volume_metric_read_ops_hourly
where
  average > 1000
order by
  volume_id,
  timestamp;

Intervals where volumes exceed 8000 max read ops

Identify instances where your AWS Elastic Block Store (EBS) volumes exceed 8000 maximum read operations per hour. This can help in analyzing the performance of your volumes and take necessary actions if they are under heavy load.

select
  volume_id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  aws_ebs_volume_metric_read_ops_hourly
where
  maximum > 8000
order by
  volume_id,
  timestamp;

select
  volume_id,
  timestamp,
  minimum,
  maximum,
  average,
  sum,
  sample_count
from
  aws_ebs_volume_metric_read_ops_hourly
where
  maximum > 8000
order by
  volume_id,
  timestamp;

Intervals where volume average iops exceeds provisioned iops

Determine the periods where the average input/output operations per second (IOPS) surpasses the provisioned IOPS for Amazon EBS volumes. This can be used to identify potential performance issues and ensure that the provisioned IOPS meets the application demand.

select
  r.volume_id,
  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_ebs_volume_metric_read_ops_hourly as r,
  aws_ebs_volume_metric_write_ops_hourly as w,
  aws_ebs_volume as v
where
  r.volume_id = w.volume_id
  and r.timestamp = w.timestamp
  and v.volume_id = r.volume_id
  and r.average + w.average > v.iops
order by
  r.volume_id,
  r.timestamp;

select
  r.volume_id,
  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_ebs_volume_metric_read_ops_hourly as r
  join aws_ebs_volume_metric_write_ops_hourly as w on r.volume_id = w.volume_id
  and r.timestamp = w.timestamp
  join aws_ebs_volume as v on v.volume_id = r.volume_id
where
  r.average + w.average > v.iops
order by
  r.volume_id,
  r.timestamp;

Read, Write, and Total IOPS

Explore the performance of your AWS EBS volumes by evaluating the average, maximum, and minimum input/output operations per second (IOPS). This analysis can help identify any unusual activity or potential bottlenecks in your system, allowing you to optimize for better performance.

select
  r.volume_id,
  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_ebs_volume_metric_read_ops_hourly as r,
  aws_ebs_volume_metric_write_ops_hourly as w
where
  r.volume_id = w.volume_id
  and r.timestamp = w.timestamp
order by
  r.volume_id,
  r.timestamp;

select
  r.volume_id,
  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_ebs_volume_metric_read_ops_hourly as r,
  aws_ebs_volume_metric_write_ops_hourly as w
where
  r.volume_id = w.volume_id
  and r.timestamp = w.timestamp
order by
  r.volume_id,
  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_ebs_volume_metric_read_ops_hourly