Azure Pricing: How to estimate Azure project costs

In the previous blog we explained how you can learn about Azure pricing with free services and a pay-as-you-go model. Next, lets understand how you can calculate your project costs when migrating or building a new solution in Azure. We will continue to use the example of Contoso, a hypothetical digital media company, and how they use Azure pricing resources to guide their migration to the cloud.

Accurately Estimate Total Cost of Ownership

Now that Contoso has a better understanding of how Azure pricing works, they need to confirm what solutions they want to migrate. This involves understanding their current infrastructure and applications, defining their goals and requirements, and estimating their project costs on Azure.

Through collaboration and internal alignment, the dev team decided to migrate their media content delivery application and their Data Analytics and Business Intelligence solution. They also decided to build an OpenAI chatbot application in Azure.

Azure provides different tools to help you estimate costs before migrating to the cloud. The Total Cost of Ownership (TCO) Calculator lets you compare costs for running an on-premises infrastructure to an Azure Cloud infrastructure. You enter your current infrastructure configuration (ex: number of servers, storage, storage costs, etc.) and the TCO calculator will compare those costs to anticipated costs when running on Azure.

Customers can also leverage Azure Migrate which provides a simplified migration, modernization, and optimization service for Azure. All pre-migration steps such as discovery, assessments, and right-sizing of on-premises resources are included for infrastructure, data, and applications.

For their migration project Contoso decided to use Azure Migrate to take advantage of the business case capability. This capability builds a business proposal that includes data such as on-premises vs. Azure total cost of ownership, year on year cashflow analysis, and resource utilization based on insight to identify servers and workloads ideal for the cloud.

To help build the OpenAI Chatbot application they leveraged the Azure Architecture Center to get guidance for architecting solutions using established patterns and practices. Using this direction, they identified which Azure products and services would be needed to run this application, such as Azure OpenAI Service, Virtual Machines, and Azure Cosmos DB.

(Baseline OpenAI end-to-end chat reference architecture)

Prepare for new project and build a plan

Knowing the TCO of running their environment on-premises vs Azure and which specific products and services are needed to run their applications lets Contoso successfully estimate their project costs. However, there are options to budget and save on these costs by leveraging Azure's pricing calculator and benefits. We will discuss these in the next blog.