Unleash the Power of AI Without Breaking the Bank: A Guide to Azure OpenAI Cost Management
Inspired by Shishir Garde's informative piece on Azure Budgets and Azure OpenAI Cost Management, this blog aims to delve deeper into managing costs effectively while harnessing the power of Azure OpenAI.
Picture yourself as a project manager at a cutting-edge tech start-up. Your mission is to develop an AI-powered chatbot that leverages state-of-the-art models like GPT-4 and Dall-E. While Azure OpenAI offers an array of powerful tools for language, code, and image generation, managing costs is a constant concern.
How can you maximize AI capabilities without busting your budget?
Pay-As-You-Go: Tailored to Your Needs
Azure OpenAI operates on a pay-as-you-go pricing model, allowing you to pay solely for what you use. The cost depends on several factors, including the type and size of the model you select and the number of tokens consumed during each API call. . For instance, if a user queries your chatbot with, "What's the weather like?", this breaks down into the following tokens: ["What", "'", "s", " the", " weather", " like", "?"]. That's 7 tokens in total. Suppose the chatbot replies with, "It's sunny and warm today." This translates to ["It", "'", "s", " sunny", " and", " warm", " today", "."], amounting to 8 tokens. In this interaction, you'd be billed for 15 tokens (7 for the query and 8 for the reply).
Tokenomics: Your Budget's Pulse
Tokens are the basic unit of measurement for Azure OpenAI's pricing. These aren't words or characters but units that can be as short as a single character or as long as a word. Keeping track of token usage is crucial, akin to monitoring the fuel gauge in your car to avoid running on empty.
The Challenge: Controlling the Cash Flow
The need to cap expenses is a common concern among Azure OpenAI users. While the platform doesn't offer a straightforward start/stop feature, a workaround exists: Azure API Management.
Azure API Management: Your Financial Co-Pilot
Inserting an Azure API Management layer before your Azure OpenAI instance provides a control mechanism for your expenses. This layer serves to:
Inspect and act upon incoming and outgoing requests.
Enforce Azure AD authentication for added security.
Log detailed token usage to help you stay on budget.
Budget Alarms and Emergency Brakes
Using Azure API Management, you can set up automatic policies to halt usage once a predefined budget threshold is met. It's like having an alarm in your car that warns you when you're about to run out of fuel.
For example, an Azure automation runbook can enforce an inbound processing policy that stops all incoming API calls if your budget limit is breached. This runbook can be triggered by Azure Budgets, which allows you to set alerts based on both actual and forecasted consumption.
Fortifying Your Financial Walls
To further secure this solution, it's advisable to restrict Azure OpenAI access using Private Endpoints and a Service Firewall. This ensures that only your API Management instance can reach the Azure OpenAI service, thereby preventing any attempts to bypass your cost-control measures.
Charting a Cost-Efficient Course in the World of AI
Azure OpenAI is a potent asset for anyone aiming to harness the full power of AI, offering not just cutting-edge capabilities but also enterprise-grade security and reliability. By understanding its pay-as-you-go pricing, tokenomics, and leveraging Azure API Management, you can navigate your AI projects toward both innovation and cost-efficiency.
Azure OpenAI Workshop
If you want to understand how Azure OpenAI can benefit your organisation’s processes, get in touch with us today about our workshop, where we go through 5 steps to help you understand the asset and develop use cases and a roadmap. Learn more here.