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add table for cost by region monthly #2310

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3 changes: 2 additions & 1 deletion aws/plugin.go
Original file line number Diff line number Diff line change
Expand Up @@ -170,6 +170,7 @@ func Plugin(ctx context.Context) *plugin.Plugin {
"aws_cost_by_account_monthly": tableAwsCostByLinkedAccountMonthly(ctx),
"aws_cost_by_record_type_daily": tableAwsCostByRecordTypeDaily(ctx),
"aws_cost_by_record_type_monthly": tableAwsCostByRecordTypeMonthly(ctx),
"aws_cost_by_region_monthly": tableAwsCostByRegionMonthly(ctx),
"aws_cost_by_service_daily": tableAwsCostByServiceDaily(ctx),
"aws_cost_by_service_monthly": tableAwsCostByServiceMonthly(ctx),
"aws_cost_by_service_usage_type_daily": tableAwsCostByServiceUsageTypeDaily(ctx),
Expand Down Expand Up @@ -467,7 +468,7 @@ func Plugin(ctx context.Context) *plugin.Plugin {
"aws_securityhub_hub": tableAwsSecurityHub(ctx),
"aws_securityhub_insight": tableAwsSecurityHubInsight(ctx),
"aws_securityhub_member": tableAwsSecurityHubMember(ctx),
"aws_securityhub_enabled_product_subscription": tableAwsSecurityhubEnabledProductSubscription(ctx),
"aws_securityhub_enabled_product_subscription": tableAwsSecurityhubEnabledProductSubscription(ctx),
"aws_securityhub_product": tableAwsSecurityhubProduct(ctx),
"aws_securityhub_standards_control": tableAwsSecurityHubStandardsControl(ctx),
"aws_securityhub_standards_subscription": tableAwsSecurityHubStandardsSubscription(ctx),
Expand Down
108 changes: 108 additions & 0 deletions aws/table_aws_cost_by_region_monthly.go
Original file line number Diff line number Diff line change
@@ -0,0 +1,108 @@
package aws

import (
"context"
"strings"
"time"

"github.com/aws/aws-sdk-go-v2/aws"
"github.com/aws/aws-sdk-go-v2/service/costexplorer"
"github.com/aws/aws-sdk-go-v2/service/costexplorer/types"

"github.com/turbot/steampipe-plugin-sdk/v5/grpc/proto"
"github.com/turbot/steampipe-plugin-sdk/v5/plugin"
"github.com/turbot/steampipe-plugin-sdk/v5/plugin/transform"
)

func tableAwsCostByRegionMonthly(_ context.Context) *plugin.Table {
return &plugin.Table{
Name: "aws_cost_by_region_monthly",
Description: "AWS Cost Explorer - Cost by Region (Monthly)",
List: &plugin.ListConfig{
Hydrate: listCostByRegionMonthly,
Tags: map[string]string{"service": "ce", "action": "GetCostAndUsage"},
KeyColumns: plugin.KeyColumnSlice{
{Name: "region", Operators: []string{"=", "<>"}, Require: plugin.Optional},
},
},
Columns: costExplorerColumns([]*plugin.Column{
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Hi @razbne,

Could you please add the missing common columns to this table? These columns are shared across tables.

  • For an aggregator connection, the partition and account_id columns are important to identify the account associated with the displayed result.
  • I understand that we can't use the awsGlobalRegionColumns() function here since the region column will always show as global.
  • However, we can manually include it as follows:
Columns: costExplorerColumns([]*plugin.Column{
			{
				Name:        "region",
				Description: "The name of the AWS region.",
				Type:        proto.ColumnType_STRING,
				Transform:   transform.FromField("Dimension1"),
			},

			// Steampipe common columns
			{
				Name:        "partition",
				Type:        proto.ColumnType_STRING,
				Hydrate:     getCommonColumns,
				Description: "The AWS partition in which the resource is located (aws, aws-cn, or aws-us-gov).",
			},
			{
				Name:        "account_id",
				Type:        proto.ColumnType_STRING,
				Hydrate:     getCommonColumns,
				Description: "The AWS Account ID in which the resource is located.",
				Transform:   transform.FromCamel(),
			},
		}),

{
Name: "region",
Description: "The name of the AWS region.",
Type: proto.ColumnType_STRING,
Transform: transform.FromField("Dimension1"),
},
}),
}
}

//// LIST FUNCTION

func listCostByRegionMonthly(ctx context.Context, d *plugin.QueryData, _ *plugin.HydrateData) (interface{}, error) {
params := buildCostByRegionInput("MONTHLY", d)
return streamCostAndUsage(ctx, d, params)
}

func buildCostByRegionInput(granularity string, d *plugin.QueryData) *costexplorer.GetCostAndUsageInput {
timeFormat := "2006-01-02"
if granularity == "HOURLY" {
timeFormat = "2006-01-02T15:04:05Z"
}

endTime := time.Now().Format(timeFormat)
startTime := getCEStartDateForGranularity(granularity).Format(timeFormat)

params := &costexplorer.GetCostAndUsageInput{
TimePeriod: &types.DateInterval{
Start: aws.String(startTime),
End: aws.String(endTime),
},
Granularity: types.Granularity(granularity),
Metrics: AllCostMetrics(),
GroupBy: []types.GroupDefinition{
{
Type: types.GroupDefinitionType("DIMENSION"),
Key: aws.String("REGION"),
},
},
}

var filters []types.Expression

for _, keyQual := range d.Table.List.KeyColumns {
filterQual := d.Quals[keyQual.Name]
if filterQual == nil {
continue
}
for _, qual := range filterQual.Quals {
if qual.Value != nil {
value := qual.Value
switch qual.Operator {
case "=":
filter := types.Expression{}
filter.Dimensions = &types.DimensionValues{}
filter.Dimensions.Key = types.Dimension(strings.ToUpper(keyQual.Name))
filter.Dimensions.Values = []string{value.GetStringValue()}
filters = append(filters, filter)
case "<>":
filter := types.Expression{}
filter.Not = &types.Expression{}
filter.Not.Dimensions = &types.DimensionValues{}
filter.Not.Dimensions.Key = types.Dimension(strings.ToUpper(keyQual.Name))
filter.Not.Dimensions.Values = []string{value.GetStringValue()}
filters = append(filters, filter)
}
}
}
}
Comment on lines +72 to +97
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Please update the local variable name to lowerCamelCase for consistency across the tables.

Suggested change
for _, keyQual := range d.Table.List.KeyColumns {
filterQual := d.Quals[keyQual.Name]
if filterQual == nil {
continue
}
for _, qual := range filterQual.Quals {
if qual.Value != nil {
value := qual.Value
switch qual.Operator {
case "=":
filter := types.Expression{}
filter.Dimensions = &types.DimensionValues{}
filter.Dimensions.Key = types.Dimension(strings.ToUpper(keyQual.Name))
filter.Dimensions.Values = []string{value.GetStringValue()}
filters = append(filters, filter)
case "<>":
filter := types.Expression{}
filter.Not = &types.Expression{}
filter.Not.Dimensions = &types.DimensionValues{}
filter.Not.Dimensions.Key = types.Dimension(strings.ToUpper(keyQual.Name))
filter.Not.Dimensions.Values = []string{value.GetStringValue()}
filters = append(filters, filter)
}
}
}
}
for _, keyQual := range d.Table.List.KeyColumns {
filterQual := d.Quals[keyQual.Name]
if filterQual == nil {
continue
}
for _, qual := range filterQual.Quals {
if qual.Value != nil {
value := qual.Value
switch qual.Operator {
case "=":
filter := types.Expression{}
filter.Dimensions = &types.DimensionValues{}
filter.Dimensions.Key = types.Dimension(strings.ToUpper(keyQual.Name))
filter.Dimensions.Values = []string{value.GetStringValue()}
filters = append(filters, filter)
case "<>":
filter := types.Expression{}
filter.Not = &types.Expression{}
filter.Not.Dimensions = &types.DimensionValues{}
filter.Not.Dimensions.Key = types.Dimension(strings.ToUpper(keyQual.Name))
filter.Not.Dimensions.Values = []string{value.GetStringValue()}
filters = append(filters, filter)
}
}
}
}


if len(filters) > 1 {
params.Filter = &types.Expression{
And: filters,
}
} else if len(filters) == 1 {
params.Filter = &(filters[0])
}

return params
}
229 changes: 229 additions & 0 deletions docs/tables/aws_cost_by_region_monthly.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,229 @@
---
title: "Steampipe Table: aws_cost_by_region_monthly - Query AWS Cost Explorer Service using SQL"
description: "Allows users to query AWS Cost Explorer Service for monthly cost breakdown by region. This table provides details such as the region name, the cost associated with it, and the currency code."
---

# 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](https://aws.amazon.com/aws-cost-management/pricing/) 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.

```sql+postgres
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;
```

```sql+sqlite
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.

```sql+postgres
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;
```

```sql+sqlite
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.

```sql+postgres
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;
```

```sql+sqlite
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;
```


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Suggested change

### 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.

```sql+postgres
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;
```

```sql+sqlite
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;
```


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Suggested change

### 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.

```sql+postgres
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;
```

```sql+sqlite
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.

```sql+postgres
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;
```

```sql+sqlite
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;
```
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