Table: aws_ebs_volume_metric_read_ops_daily - Query AWS EBS Volume Metrics using SQL

The AWS EBS Volume Metrics is a feature of Amazon Elastic Block Store (EBS) that provides raw block-level storage that can be attached to Amazon EC2 instances. These metrics provide visibility into the performance, operation, and overall health of your volumes, allowing you to optimize usage and respond to system-wide performance changes. With the ability to query these metrics using SQL, you can gain insights into read operations on a daily basis, enhancing your ability to monitor and manage your data storage effectively.

Table Usage Guide

The aws_ebs_volume_metric_read_ops_daily table in Steampipe provides you with information about the daily read operations metrics of AWS Elastic Block Store (EBS) volumes. This table allows you, as a system administrator, DevOps engineer, or other technical professional, to query details about the daily read operations performed on EBS volumes, which is useful for your performance analysis, capacity planning, and cost optimization. The schema outlines various attributes of the EBS volume metrics, including the average, maximum, and minimum read operations, as well as the sum of read operations and the time of the metric capture.

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

Examples

Basic info

Explore the performance of your AWS EBS volumes over time. This query can help you understand the volume of read operations, which can be useful in assessing system performance, identifying potential bottlenecks, and planning for capacity.

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

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

Intervals where volumes exceed 1000 average read ops

Discover the instances when the average read operations on AWS EBS volumes exceed 1000. This information can be used to identify potential performance issues or optimize resource allocation.

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

Intervals where volumes exceed 8000 max read ops

Determine the instances where the daily read operations on AWS EBS volumes exceed a threshold of 8000. This can be useful in identifying potential performance issues or capacity planning for your storage infrastructure.

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

Read, Write, and Total IOPS

Explore the average, maximum, and minimum Input/Output operations for each volume over time to understand the performance of your storage volumes. This query is useful for identifying any potential bottlenecks or inefficiencies in data transfer operations.

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_daily as r,
  aws_ebs_volume_metric_write_ops_daily 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_daily as r,
  aws_ebs_volume_metric_write_ops_daily 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_daily