Table: aws_cost_by_region_monthly - Query AWS Cost Explorer region using SQL

The AWS Cost Explorer region provides detailed information about your AWS costs, enabling you to analyze your costs and usage over time. You can use it to identify trends, isolate cost drivers, and detect anomalies. With SQL queries, you can retrieve monthly cost data specific to each AWS region.

Table Usage Guide

The aws_cost_by_region_monthly table in Steampipe provides you with information about the monthly cost breakdown by region within AWS Cost Explorer. This table allows you, as a financial analyst, DevOps engineer, or other stakeholder, to query cost-specific details, including the region name, the cost associated with it, and the currency code. You can utilize this table to gather insights on cost management, such as tracking AWS expenses, identifying cost trends, and auditing. The schema outlines the various attributes of the cost information, including the region name, cost, and currency code.

Amazon Cost Explorer helps you visualize, understand, and manage your AWS costs and usage. The aws_cost_by_region_monthly table provides you with a simplified view of cost for regions in your account (or all linked accounts when run against the organization master), summarized by month, for the last year.

Important Notes

• The pricing for the Cost Explorer API is per API request - Each request you make will incur a cost of $0.01.

Examples

Basic info

Explore which AWS regions have the highest costs over time. This query is useful in identifying potential areas for cost reduction through region optimization or consolidation.

select
  region,
  period_start,
  blended_cost_amount :: numeric :: money,
  unblended_cost_amount :: numeric :: money,
  amortized_cost_amount :: numeric :: money,
  net_unblended_cost_amount :: numeric :: money,
  net_amortized_cost_amount :: numeric :: money
from
  aws_cost_by_region_monthly
order by
  region,
  period_start;

select
  region,
  period_start,
  cast(blended_cost_amount as decimal),
  cast(unblended_cost_amount as decimal),
  cast(amortized_cost_amount as decimal),
  cast(net_unblended_cost_amount as decimal),
  cast(net_amortized_cost_amount as decimal)
from
  aws_cost_by_region_monthly
order by
  region,
  period_start;

Min, Max, and average monthly unblended_cost_amount by region

Explore which AWS regions have the lowest, highest, and average monthly costs, providing a clear understanding of your AWS expenditure. This can help in budgeting and identifying regions that may be costing more than expected.

select
  region,
  min(unblended_cost_amount) :: numeric :: money as min,
  max(unblended_cost_amount) :: numeric :: money as max,
  avg(unblended_cost_amount) :: numeric :: money as average
from
  aws_cost_by_region_monthly
group by
  region
order by
  region;

select
  region,
  min(unblended_cost_amount) as min,
  max(unblended_cost_amount) as max,
  avg(unblended_cost_amount) as average
from
  aws_cost_by_region_monthly
group by
  region
order by
  region;

Top 10 most expensive region (by average monthly unblended_cost_amount)

Discover the segments that are incurring the highest average monthly costs on your AWS account. This information can be crucial for budgeting and cost management strategies, helping you to identify areas where expenses can be reduced.

select
  region,
  sum(unblended_cost_amount) :: numeric :: money as sum,
  avg(unblended_cost_amount) :: numeric :: money as average
from
  aws_cost_by_region_monthly
group by
  region
order by
  average desc
limit
  10;

select
  region,
  sum(unblended_cost_amount) as sum,
  avg(unblended_cost_amount) as average
from
  aws_cost_by_region_monthly
group by
  region
order by
  average desc
limit
  10;

Top 10 most expensive region (by total monthly unblended_cost_amount)

This query helps to pinpoint the top 10 most costly regions in terms of total monthly unblended cost. It is useful for gaining insights into where the majority of your AWS costs are coming from, allowing for more informed budgeting and cost management decisions.

select
  region,
  sum(unblended_cost_amount) :: numeric :: money as sum,
  avg(unblended_cost_amount) :: numeric :: money as average
from
  aws_cost_by_region_monthly
group by
  region
order by
  sum desc
limit
  10;

select
  region,
  sum(unblended_cost_amount) as sum,
  avg(unblended_cost_amount) as average
from
  aws_cost_by_region_monthly
group by
  region
order by
  sum desc
limit
  10;

Ranked - Most expensive month (unblended_cost_amount) by region

This query is designed to identify the most costly month for each region in terms of unblended costs. It can be useful for budgeting and cost management, helping to highlight areas where expenses may be unexpectedly high.

with ranked_costs as (
  select
    region,
    period_start,
    unblended_cost_amount :: numeric :: money,
    rank() over(
      partition by region
      order by
        unblended_cost_amount desc
    )
  from
    aws_cost_by_region_monthly
)
select
  *
from
  ranked_costs
where
  rank = 1;

Error: SQLite does not support the rank window function.

Month on month growth (unblended_cost_amount) by region

Analyze your AWS monthly costs to understand the percentage change in expenditure for each region. This could be useful for identifying trends, managing budgets, and making strategic decisions about resource allocation.

with cost_data as (
  select
    region,
    period_start,
    unblended_cost_amount as this_month,
    lag(unblended_cost_amount, -1) over(
      partition by region
      order by
        period_start desc
    ) as previous_month
  from
    aws_cost_by_region_monthly
)
select
  region,
  period_start,
  this_month :: numeric :: money,
  previous_month :: numeric :: money,
  case
    when previous_month = 0
    and this_month = 0 then 0
    when previous_month = 0 then 999
    else round(
      (100 * ((this_month - previous_month) / previous_month)) :: numeric,
      2
    )
  end as percent_change
from
  cost_data
order by
  region,
  period_start;

with cost_data as (
  select
    region,
    period_start,
    unblended_cost_amount as this_month,
    lag(unblended_cost_amount, -1) over(
      partition by region
      order by
        period_start desc
    ) as previous_month
  from
    aws_cost_by_region_monthly
)
select
  region,
  period_start,
  this_month,
  previous_month,
  case
    when previous_month = 0
    and this_month = 0 then 0
    when previous_month = 0 then 999
    else round(
      (100 * ((this_month - previous_month) / previous_month)),
      2
    )
  end as percent_change
from
  cost_data
order by
  region,
  period_start;

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_cost_by_region_monthly