Azure Pricing: How to navigate Azure pricing options and resources

In this blog we discussed customer pricing needs and how they match different phases of the cloud journey, and we provided various tools and resources to help you with your cloud pricing questions.

Now, we will dive deeper into how Azure pricing works and how you can learn more about it. We will use the example of Contoso, a hypothetical digital media company, to show how they use Azure pricing resources to guide their migration to the cloud.

Consider the cloud through testing and learning

Contoso is considering moving their on-premises environment to the cloud to meet their growing demand for content, expand their services globally, and reduce their operating costs. Before moving to the cloud, the company wants to learn how Azure pricing works. They need to build confidence and showcase the value of the cloud to their leadership to approve the migration project.

To help gather information, their Dev team created an Azure account to test different free services and started to consume others using the Pay-as-you-go model. They learned that Azure spend falls under operational expenditure (OpEx) because it operates on a consumption-based model. With Azure, they only pay for the IT resources they use, and not for the physical infrastructure, electricity, security, or anything else associated with maintaining a datacenter. If they don’t use any IT resources this month, they don’t pay for them, and they can scale or stop using services at any time. This is comparable to how a household would pay for a utility service. Some factors that impact their cost include resource type, geography location, and amount consumed.

The pay-as-you-go model is different than a commitment-based model such as Azure Reservations and Azure savings plan for compute. With a commitment-based model you pay for services upfront for a set amount of time in exchange for a lower price.

Through testing, their dev team deployed and configured different virtual machines to test scalable media processing; set up an Azure Blob storage to store and retrieve media files; experimented with Azure OpenAI services for media analytics, and migrated a sample database to Azure SQL Database for scalable and managed database solutions. They were also able to monitor and analyze their spend using Microsoft Cost Management.

They took the “Describe factors that can affect costs in Azure” Learning Module and read though the “Cost Management + Billing” documentation to dive deeper into Azure costs and billing.

Building confidence with Azure services and costs

After using these resources, they were able to get a better understanding of how Azure services perform and how they are priced based on usage.

In the next blog we will explore how Contoso will start to estimate their costs for their next Azure projects.