How Much Does Azure Cost: Introducing Azure Costing | Quisitive

Welcome to the “Introducing” series (check here for the full list of blog posts in this series). In the previous three blog posts, we introduced Azure and what services it provides, next we introduced certifications for Azure and how to get started with Azure and most recently we introduced the structure of Azure. In this blog post, we will introduce how much does Azure cost for resources works.

Costing in Azure:

In an earlier blog post in the series, we introduced how pricing works in the cloud. A quick summary of that blog post is below:

Visualizing Costing information:

If you are looking for a quick high-level view of your current Azure spend in the Azure portal you can open “Subscriptions” in Azure. In this view, you can see a list of what subscriptions you have access to as well as their current cost levels. This view is available by going to All services and typing “subscriptions” as shown below.

Graphic 1: Getting to subscriptions

Graphic 2: Subscriptions and costing

The primary method to view details on costs for resources in Azure is to use the “Cost Management + Billing view”. This view is available by going to All services and typing “cost” as shown below in the Azure portal.

Graphic 3: Getting to Cost Management & Billing

This view can be used to show the accumulated costs for Azure across one or more subscriptions, but it is currently restricted to viewing a single directory at a time.

Graphic 4: Cost Management + Billing

Please note, Azure Sponsorship cost information is not currently available in Cost Management but it’s listed as “coming soon” as of 4/13/2020.

Graphic 5: Extracting data and visualizing in Excel

Below is a simple treemap showcasing how you can easily see which specific subscriptions are using the most Azure from a costing perspective (with the subscription names scrubbed).

Graphic 6: Extracting data and visualizing exported data in Power BI

The treemap approach is also available in Power BI. Below is a quick sample put together in Power BI using the CSV data exported from Azure.

Graphic 7: Extracting data and visualizing PowerShell gathered data in Power BI

If the existing solutions in Azure are not sufficient for your needs, you can also export this data (or gather it via PowerShell scripts) and import the data into Power BI. In the example below I gathered 30 days’ worth of detailed data which could be seen via the type of resource and costs on a daily basis.

Microsoft provides great options directly available in Azure to see Azure costing and to forecast where costing will go. Additionally, the data can be accessed via a CSV export (which can be scheduled) and can also be gathered via PowerShell scripting.

Consumption as a metric for good

In a household, there are two metrics that are heavily dependent upon consumption – electrical and water. Depending on how you are billed, electrical is the closest to a truly consumption-based metric. The more electricity you use, the more it costs every month. Similarly, for water – the more water your household uses the more it costs every month. Speaking from a homeowner’s perspective, I do not begrudge my electrical or water providers what they charge me for the usage of their services – mostly because I have a level of control over my usage of either of these resources. What I do begrudge them is the base charges which occur every month regardless of how much I use their services.

Using a consumption-based metric for pricing at first sounds like it would be the most beneficial to the company that is being consumed from. IE: That the company selling the services wants you to consume more so they are incentivized to have you consume more (possibly even more than you need). This metric, however, works out to be the most beneficial to the consumer because if you are not gaining value from consuming you will not continue to consume. Therefore, it is critical to the vendor providing the services that you as the consumer see benefit from consuming their services.

Thank you to Greg T, Chad S and Beth F for their help on this blog post!

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