Now you have pulled together optimization data there different ways in which you can analyze and visualize it and use to make infrastructure optimization decisions
Visualization of Trusted Advisor data with Amazon QuickSight
You can visualize Trusted Advisor Data with TAO Dashboard.
To deploy TAO Dashboard
please follow either automated
or manual
deployment steps and specify organizational data collection bucket created in this lab as a source
Visualization of Compute Optimizer data with Amazon QuickSight
AWS Organization Data and The Cost Intelligence Dashboard
This video shows you how to use the Optimization Data Collection Lab to pull in AWS Organization data such as Account names and Tags into the Cost And Usage report so it can be used in the CID.
You can also use the below query to update your account_map table in athena to read from this data
New Account Map Query
CREATE OR REPLACE VIEW "account_map" AS
SELECT DISTINCT
id account_id
, split_part(arn, ':',5) parent_account_id
, name account_name
, email account_email_id
FROM
"optimization_data"."organisation_data"
Snapshots and AMIs
When a AMI gets created it takes a Snapshot of the volume. This is then needed to be kept in the account whilst the AMI is used. Once the AMI is released the Snapshot can no longer be used but it still incurs costs. Using this query we can identify Snapshots that have the ‘AMI Available’, those where the ‘AMI Removed’ and those that fall outside of this scope and are ‘NOT AMI’. Data must be collected and the crawler finished running before this query can be run.
Optimization Data Snapshots and AMIs Query
SELECT *,
CASE
WHEN snap_ami_id = imageid THEN
'AMI Avalible'
WHEN snap_ami_id LIKE 'ami%' THEN
'AMI Removed'
ELSE 'Not AMI'
END AS status
FROM (
(SELECT snapshotid AS snap_id,
volumeid as volume,
volumesize,
starttime,
Description AS snapdescription,
year,
month,
ownerid,
CASE
WHEN substr(Description, 1, 22) = 'Created by CreateImage' THEN
split_part(Description,' ', 5)
WHEN substr(Description, 2, 11) = 'Copied snap' THEN
split_part(Description,' ', 9)
WHEN substr(Description, 1, 22) = 'Copied for Destination' THEN
split_part(Description,' ', 4)
ELSE ''
END AS "snap_ami_id"
FROM "optimization_data"."snapshot_data"
) AS snapshots
LEFT JOIN
(SELECT imageid,
name,
description,
state,
rootdevicetype,
virtualizationtype
FROM "optimization_data"."ami_data") AS ami
ON snapshots.snap_ami_id = ami.imageid )
There is an option to add pricing data to this query. This assumes you have already run the accounts collector lambda.
Optimization Data Snapshots and AMIs with pricing data
Lambda
Go to AWS Lambda
Find the pricing-Lambda-Function function
Test the function
Athena
Go to AWS Athena
Go to Saved queries at the top of the screen
Run the ec2_pricing Query to create a pricing table
In Saved queries Run the region_names Query to create a normalized region name table
In Saved queries run snapshot-ami-query to create a view
Run the below to see your data
SELECT * FROM "optimization_data"."snapshot_ami_quicksight_view" limit 10;
EBS Volumes and Trusted Advisor Recommendations
Trusted advisor identifies idle and underutilized volumes. This query joins together the data so you can see what portion of your volumes are flagged. Data must be collected and the crawler finished running before this query can be run.
This section requires you to have the Inventory Module and the Trusted Advisor Module deployed.
Optimization Data EBS Volumes and Trusted Advisors Query
SELECT * FROM
"optimization_data"."ebs_data"
LEFT JOIN
(select "volume id","volume name", "volume type","volume size", "monthly storage cost" ,accountid, category, region, year,month
from
"optimization_data".ta_data ) ta
ON "ebs_data"."volumeid" = "ta"."volume id" and "ebs_data"."year" = "ta"."year" and "ebs_data"."month" = "ta"."month"
There is an option to add pricing data to this query.
Optimization Data EBS Volumes and Trusted Advisor with pricing data
Lambda
Go to AWS Lambda
Find the pricing-Lambda-Function function
Test the function
Athena
Go to AWS Athena and run the below
Go to Saved queries at the top of the screen
Run the ec2-view Query to create a view of ebs and ta data
Run the ec2_pricing Query to create a pricing table
In Saved queries run the region_names Query to create a normalized region name table
In Saved queries run ebs-ta-query-pricing to create a view
Run the below to see your data
SELECT * FROM "optimization_data"."ebs_quicksight_view" limit 10;
The section below will bring in opportunities to move EBS volumes to gp3
EBS Volumes and Trusted Advisor moving to gp3
Go to AWS Athena and run the below
Go to Saved queries at the top of the screen
Run the ec2-view Query to create a view of ebs and ta data
Run the ec2_pricing Query to create a pricing table
In Saved queries run the region_names Query to create a normalized region name table
In Saved queries run gp3-opportunity to create a view
EBS Volumes and Trusted Advisor Recommendations
Trusted advisor identifies idle and underutilized volumes. This query joins together the data so you can see what portion of your volumes are flagged. Data must be collected and the crawler finished running before this query can be run.
This section requires you to have the Inventory Module and the Trusted Advisor Module deployed.
Optimization Data EBS Volumes and Trusted Advisors Query
CREATE OR REPLACE VIEW "ebs_view" AS
SELECT *FROM
"optimization_data"."ebs_data"
LEFT JOIN
(select "volume id","volume name", "volume type","volume size", "monthly storage cost" ,accountid as ta_accountid, status, category, region as ta_region, year as ta_year ,month as ta_month
from
"optimization_data".ta_data
where category = 'cost_optimizing') ta
ON "ebs_data"."volumeid" = "ta"."volume id" and "ebs_data"."year" = "ta"."ta_year" and "ebs_data"."month" = "ta"."ta_month"
LEFT JOIN (
SELECT
"region" "region_code"
, "regionname"
FROM
storage.region_names
) region ON ("ebs_data"."region" = "region"."region_code")
AWS Budgets into Cost Dashboard
In these labs we have a couple of amazing cost dashboards that can be found here
. If you would like to add your budget data into these dashboard please follow the below steps. Data must be collected and the crawler finished running before this query can be run.
There is a saved query called aws_budgets created in the CloudFormation. This is used when connecting to dashboard.
Guide to add AWS Budgets into Cost Dashboard
Ensure you have budget data in your Amazon Athena table
Create a Amazon Athena View of this data to extract the relevant information. The costfilters identifies if this is just an account spend budget or filtered. As this if for CUDOS we have filtered these out for the query but all budgets data is in the table.
CREATE OR REPLACE VIEW aws_budgets_view AS
SELECT
budgetname budget_name
, CAST(budgetlimit.amount AS decimal) budget_amount
, CAST(calculatedspend.actualspend.amount AS decimal) actualspend
, CAST(calculatedspend.forecastedspend.amount AS decimal) forecastedspend
, timeunit
, account_id
, budgettype budget_type
, year budget_year
, month budget_month
FROM
"optimization_data"."budgets"
WHERE (budgettype = 'COST') AND costfilters.filter[1] = 'None'
Go to the Amazon QuickSight service homepage
In QuickSight, select the summary_view Data Set
Select Edit data set
Select Add data:
Select your Amazon Athena aws_budgets_view table and click Select
Click on the join and choose month, year from summary_view and budget_month, budget_year to join. Click Save.
In your Analysis you can now add a Budget figure to your lines. Make sure to change to Average.
AWS EBS Volumes and Snapshots
If you wish to see whats volumes have what snapshots attached to them from a holistic view then this query can combine these two data sources. This could provide information into which snapshots you could archive using Elastic Block Storage Snapshots Archive
Optimization Data Snapshots with EBS
WITH data as (
Select volumeid,
snapshotid,
ownerid "account_id",
cast( replace(split(split(starttime, '+') [ 1 ], '.') [ 1 ], 'T', ' ') as timestamp) as start_time,
CAST("concat"("year", '-', "month", '-01') AS date) "data_date",
sum(volumesize) "volume_size"
from "optimization_data"."snapshot_data"
group by 1,2,3,4,5
),
latest AS(
Select max(data_date) "latest_date" from data
),
ratio AS(
Select distinct volumeid, data_date, latest_date,
count(distinct snapshotid) AS "snapshot_count_per_volume"
from data
LEFT JOIN latest ON latest.latest_date = data_date
WHERE volumeid like 'vol%' and data_date = latest_date
group by 1,2,3
)
select data.volumeid,
data.snapshotid,
account_id,
data.data_date,
start_time,
volume_size,
snapshot_count_per_volume,
CASE WHEN data.volumeid NOT LIKE 'vol%' THEN 1 ELSE dense_rank() OVER (partition by data.volumeid ORDER by start_time) END AS "snapshot_lineage"
from data
Left JOIN ratio ON ratio.volumeid = data.volumeid
ORDER by volumeid, snapshot_lineage
If you wish to connect to your Cost and Usage report for snapshot costs please use the below:
Optimization Data Snapshots with EBS and CUR
WITH cur_mapping AS (
SELECT DISTINCT
split_part(line_item_resource_id,'/',2) AS "snapshot_id",
line_item_usage_account_id AS "linked_account_id",
CAST("concat"("year", '-', "month", '-01') AS date) "billing_period", sum(line_item_usage_amount) "snapshot_size",
sum(line_item_unblended_cost) "snapshot_cost"
FROM "athenacurcfn_mybillingreport"."mybillingreport"
WHERE (CAST("concat"("year", '-', "month", '-01') AS date) = ("date_trunc"('month', current_date) - INTERVAL '1' MONTH)) AND (line_item_resource_id <> '') AND (line_item_line_item_type LIKE '%Usage%') AND (line_item_product_code = 'AmazonEC2') AND (line_item_usage_type LIKE '%EBS:Snapshot%')
group by 1,2,3
),
snapshot_data AS (
Select volumeid,
snapshotid,
ownerid "account_id",
cast(
replace(split(split(starttime, '+') [ 1 ], '.') [ 1 ], 'T', ' ') as timestamp
) as start_time,
CAST("concat"("year", '-', "month", '-01') AS date) "data_date",
sum(volumesize) "volume_size"
from "optimization_data"."snapshot_data"
group by 1,2,3,4,5
),
data AS (
SELECT DISTINCT volumeid,
snapshotid,
account_id,
billing_period,
data_date,
start_time,
sum(snapshot_size) AS snapshot_size,
sum(snapshot_cost) AS snapshot_cost,
sum(volume_size) AS "volume_size"
FROM snapshot_data
LEFT JOIN cur_mapping ON cur_mapping.snapshot_id = snapshotid AND cur_mapping.linked_account_id = account_id
group by 1,2,3,4,5,6
),
latest AS(
Select max(data_date) "latest_date"
from data
),
ratio AS(
Select distinct volumeid, data_date, latest_date,
count(distinct snapshotid) AS "snapshot_count_per_volume",
sum(snapshot_cost) AS "all_snapshot_cost_per_volume",
sum(snapshot_size) AS "all_snapshot_size_per_volume"
from data
LEFT JOIN latest ON latest.latest_date = data_date
WHERE volumeid like 'vol%' and data_date = latest_date
group by 1,2,3
)
select data.volumeid,
data.snapshotid,
account_id,
data.data_date,
start_time,
billing_period,
snapshot_size,
volume_size,
all_snapshot_cost_per_volume
all_snapshot_size_per_volume,
snapshot_count_per_volume,
CASE WHEN data.volumeid NOT LIKE 'vol%' THEN 1 ELSE dense_rank() OVER (partition by data.volumeid ORDER by start_time) END AS "snapshot_lineage"
from data
LEFT JOIN ratio ON ratio.volumeid = data.volumeid
ECS Chargeback
Report to show costs associated with ECS Tasks leveraging EC2 instances within a Cluster
Athena Configuration
Navigate to the Athena service
Select the “optimization data” database
In Saved Queries find “cluster_metadata_view”" Change ‘BU’ to the tag you wish to do chargeback for
Click the Run button
In Saved Queries find “ec2_cluster_costs_view”"
– Replace ${CUR} in the “FROM” clause with your CUR table name
– For example, “curdb”.“ecs_services_clusters_data”
Click the Run button
In Saved Queries find “bu_usage_view”"
– Replace ${CUR} in the “FROM” clause with your CUR table name
– For example, “curdb”.“ecs_services_clusters_data”
Click the Run button
Now your views are created you can run your report
Manually execute billing report
In Saved Queries find “ecs_chargeback_report”
– Replace “bu_usage_view.month” value with the appropriate month desired for the report
– For example, a value of ‘2’ returns the charges for February
Click the Run button
Example Output
Breakdown:
task_usage: total memory resources reserved (in GBs) by all tasks over the billing period (i.e. – monthly)
percent: task_usage / total_usage
ec2_cost: monthly cost for EC2 instance in $
Services: Name of service
servicearn: Arn of service
Value: Value of specified tag for the ECS service (could be App, TeamID, etc?)
AWS Transit Gateway Chargeback
AWS Transit Gateway data transfer cost billed at the central networking account is allocated proportionally to the end usage accounts. The proportion is calculated by connecting with AWS CloudWatch bytes in bytes out data at each Transit Gateway attachement level. The total central data transfer cost is calculated at the central networking account with Cost and Usage Report. The chargeback amount is the corresponding proportional cost of the total central amount.
Athena Configuration
Navigate to the Athena service and open Saved Queries.
Select your database where you have your Cost and Usage Report
In Saved Queries find “tgw_chargeback_cur”"
Replace < CURDatabase > with your database name in the tgw_chargeback_cur. For example:
"cur"."cost_and_usage_report"
The Cloud Watch data collection is automated for all the regions. However, if you are destined to only chargeback to a subset of selected regions, you need to specify it in “product_location LIKE ‘%US%'” line.
Click the Run button
In Saved Queries find “tgw_chargeback_cw”"
Select the “optimization data” database
Replace < CURDatabase > with your database name in the tgw_chargeback_cw.
Click the Run button
Now your views are created and you can run your report
RDS Graviton Eligibility
Graviton2 instances provide up to 35% performance improvement and up to 52% price/performance improvement for open source databases depending on database engine, version, and workload. You can easily determine what databases in your account can take advantage of Graviton using the RDS Graviton Eligibility query. This query will output all existing RDS databases, if they are eligible for graviton, if it requires any version upgrades in order to to migrate, the target graviton instance, as well as estimated savings.
This section requires you to have the RDS Module deployed.
Optimize RDS with Graviton
Navigate to Lambda and test the Accounts-Collector-Function-OptimizationDataCollectionStack and pricing-Lambda-Function-OptimizationDataCollectionStack lambdas
Navigate to Athena
Go to Saved queries at the top of the screen
Run the region_names Query to create a normalized region name table
Run the rds_pricing_table Query to create a pricing look up table for RDS
Run the graviton_mapping Query to create a mapping of existing Intel based instances to the proper Graviton based instance
Run the rds_metrics-rds-graviton Query to provide the output of your RDS instances and their graviton eligibility and savings. You can download the results to further filter and analyze the results
Analyzing Your Results
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Breakdown: