Tutorials

Correlating Costs to Resources for Azure Cost Optimization with CloudQuery

• January 4, 2023

Introduction #

Optimizing cloud costs is a never-ending task. There are many ways to do it, and many tools to help you do it. One of the most important things to do is to correlate your cloud costs with your cloud infrastructure. This tutorial will show how to correlate between Azure Cost Analysis data and CloudQuery to optimize cost.

Prerequisites #

Azure Source Plugin
PostgreSQL Destination Plugin
A PostgreSQL instance (can be local or remote)

Create a Cost Analysis Report in Azure #

First, we need to create a Cost Analysis Report in Azure. To do that, go to the Cost Management section in the Azure Portal and click on the Cost Analysis tab.

Then, click on the Cost by Resource button.

Here you can make adjustments to your report. Make sure to select the time range you want to analyze. For this tutorial, we'll leave this at the default of current billing period. Make sure the Group By option is set to Resource.

Use the Save as button to save this as a new report view. Give it a name and click Save.

Now we can configure CloudQuery so each time we run cloudquery sync the data from this report will be synced to a PostgreSQL database.

Syncing data #

Before going off and writing queries, we need to sync the data from Azure to our PostgreSQL database. To do that, we'll use the cloudquery sync command. Let's start with creating a configuration file (For the full configuration reference, check out the Azure Source Plugin and PostgreSQL Destination Plugin):

kind: source
spec:
  # Source spec section
  name: 'azure'
  path: 'cloudquery/azure'
  registry: 'cloudquery'
  version: 'v16.0.3'
  destinations: ['postgresql']
  tables: ['azure_costmanagement_views', 'azure_costmanagement_view_queries']
---
kind: destination
spec:
  name: postgresql
  path: cloudquery/postgresql
  registry: 'cloudquery'
  version: 'v8.7.5'
  spec:
    # You will need to edit this to specify your own DSN
    connection_string: 'postgresql://postgres:pass@localhost:5432/postgres?sslmode=disable'

Save this file as config.yml and run cloudquery sync ./config.yml. This might take a hot minute or two, depending on how many subscriptions you have and how many resources you have in them.

Once the data is synced we can move on to the next section.

Understanding the Cost Report #

Now that we have the data synced, we can start writing queries. Let's start with a simple query to see what the data looks like. We'll start with the azure_costmanagement_views table. This table contains the data from the Cost Analysis report we created earlier. Let's see what the data looks like:

SELECT * FROM azure_costmanagement_views LIMIT 1;

Focus on the properties column, which looks like this if formatted nicely:

As you can see this only includes metadata about our report. Report contents are nowhere to be seen here. For that, we need to look at the azure_costmanagement_view_queries table. Let's see what the data looks like:

SELECT * FROM azure_costmanagement_view_queries LIMIT 1;

Again, if we focus on the properties column and format it in JSON Viewer:

Looks like the data we're interested in is sitting nicely in properties.

We need to run one more thing before we can start correlating away though.

The Azure Resources View #

The azure_resources view is useful for seeing all your Azure resources in one place or finding a specific resource, by id or name. It's a view, so it's not synced to the database, but we can create it by running the queries provided here. First query will drop the view if it exists, and the second query will create it. Run these queries in your PostgreSQL database.

Correlating the data #

First Steps #

As the first query we should correlate our specific named report with the data in the azure_costmanagement_view_queries table. We can do this by using the azure_costmanagement_views table to get the _cq_id of our report, and then using that cq_id (matching it with _cq_parent_id) to find the data in the azure_costmanagement_view_queries table. Something like:

SELECT v.*, q.* FROM azure_costmanagement_views v, azure_costmanagement_view_queries q WHERE v.name = 'cost-matching' AND v._cq_id = q._cq_parent_id;

Keep in mind that the cost-matching name is the name we gave our report when we created it. If you named it something else, you'll need to change it here.

Deeper Dive #

After seeing actual data it will become apparent that we'll need to figure out the column indexes for the data we're interested in. We can do this by looking at the properties.columns data in the azure_costmanagement_view_queries table. We can use JSONB_ARRAY_ELEMENTS WITH ORDINALITY to match column names to indexes. Something like JSONB_ARRAY_ELEMENTS(q.properties->'columns') WITH ORDINALITY cid(col, pos) ON cid.col->>'name'='ResourceId' will give us the index of the ResourceId column as cid.pos. A full query to return Resource Id vs. Cost (USD) might look like:

SELECT (r->>(cid.pos::int - 1))::text AS res_id, (r->>(ccost.pos::int - 1))::numeric AS cost_usd
FROM azure_costmanagement_view_queries q
JOIN JSONB_ARRAY_ELEMENTS(q.properties->'rows') AS r ON TRUE
JOIN JSONB_ARRAY_ELEMENTS(q.properties->'columns') WITH ORDINALITY cid(col, pos) ON cid.col->>'name'='ResourceId'
JOIN JSONB_ARRAY_ELEMENTS(q.properties->'columns') WITH ORDINALITY ccost(col, pos) ON ccost.col->>'name'='CostUSD'
JOIN azure_costmanagement_views v ON v._cq_id=q._cq_parent_id
WHERE v.name='cost-matching'

Let's break it down:

SELECT (r->>(cid.pos::int - 1))::text AS res_id, (r->>(ccost.pos::int - 1))::numeric AS cost_usd - This is the meat of the query. We're selecting the ResourceId and CostUSD columns from the azure_costmanagement_view_queries table. We're using the cid.pos and ccost.pos values we got from the previous query to get the correct column indexes. We're also casting the values to the correct types. - 1 because we're using 1-based indexing, and the rows array is 0-based.
FROM azure_costmanagement_view_queries q - We're selecting from the azure_costmanagement_view_queries table, and we're calling it q for the rest of the query.
JOIN JSONB_ARRAY_ELEMENTS(q.properties->'rows') AS r ON TRUE - We're joining the azure_costmanagement_view_queries table to itself, and we're calling the joined table r. We're using JSONB_ARRAY_ELEMENTS to get the rows from the properties column. We're using ON TRUE because we don't need to filter the rows, we just need to join them.
JOIN JSONB_ARRAY_ELEMENTS(q.properties->'columns') WITH ORDINALITY cid(col, pos) ON cid.col->>'name'='ResourceId' - We're joining the azure_costmanagement_view_queries table to itself again, and we're calling the joined table cid. We're using JSONB_ARRAY_ELEMENTS to get the columns from the properties column. We're using WITH ORDINALITY to get the column index as well. We're using ON cid.col->>'name'='ResourceId' to filter the columns to only the ResourceId column.
JOIN JSONB_ARRAY_ELEMENTS(q.properties->'columns') WITH ORDINALITY ccost(col, pos) ON ccost.col->>'name'='CostUSD' - Same as above, but we're filtering to only the CostUSD column.
JOIN azure_costmanagement_views v ON v._cq_id=q._cq_parent_id - We're joining the azure_costmanagement_views table to the azure_costmanagement_view_queries table. We're using the _cq_id column to match the two tables.
WHERE v.name='cost-matching' - We're filtering the azure_costmanagement_views table to only the report we're interested in.

Final Query #

Now that we have a query that returns the res_id and cost_usd columns, we can use that to correlate the data with the azure_resources view. We can do this by using the above query to get the Resource ID, and then using that to find the data in the azure_resources view (match using LOWER(), as the ids don't always match case-wise). Something like:

WITH cost_by_res AS (
    SELECT (r->>(cid.pos::int - 1))::text AS res_id, (r->>(ccost.pos::int - 1))::numeric AS cost_usd
    FROM azure_costmanagement_view_queries q
             JOIN JSONB_ARRAY_ELEMENTS(q.properties->'rows') AS r ON TRUE
             JOIN JSONB_ARRAY_ELEMENTS(q.properties->'columns') WITH ORDINALITY cid(col, pos) ON cid.col->>'name'='ResourceId'
    JOIN JSONB_ARRAY_ELEMENTS(q.properties->'columns') WITH ORDINALITY ccost(col, pos) ON ccost.col->>'name'='CostUSD'
    JOIN azure_costmanagement_views v ON v._cq_id=q._cq_parent_id
WHERE v.name='cost-matching' -- <-- this is the name of your saved view with "resource" field
    )
SELECT
    c.*,
    r.name,
    r.kind,
    r.location
FROM cost_by_res c JOIN azure_resources r ON LOWER(r.full_id)=LOWER(c.res_id);

Summary #

In this blog post we just shared an example of what you can do by combining cost data with your infrastructure state/metadata synced by CloudQuery. The number of use cases around cost (aka "FinOps" :) ) is really infinite and it all depends on what you are trying to achieve and optimize for.

We hope you enjoyed this tutorial and found it useful. If you have any questions or feedback, please reach out to us on our Community or Twitter.

Ready to dive deeper? Contact CloudQuery here or join the CloudQuery Community to connect with other users and experts. You can also try out CloudQuery locally with our quick start guide or explore the CloudQuery Platform (currently in beta) for a more scalable solution.

Want help getting started? Join the CloudQuery community to connect with other users and experts, or message our team directly here if you have any questions.

Written by Kemal Hadimli

Kemal is a senior software engineer at CloudQuery with experience in high performance front-and-backend programming and application design.

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