After months of usage, I’ve come to realize that Managing costs in Azure OpenAI is a somewhat complicated process. It’s not just about understanding the pricing model; it’s about strategically planning your usage, optimizing your approach, and leveraging the tools Microsoft provides to keep your expenses in check. So, here is my insight on cost planning and management within Azure.
The cost planning should start before deployment
Before you even spin up your first Azure OpenAI resource, Microsoft encourages you to use the Azure pricing calculator. This handy tool lets you estimate your potential costs based on your anticipated usage. It’s a great way to set a realistic budget and ensure you won’t be caught off guard by unexpected expenses.
It’s also crucial to understand the nuances of Azure OpenAI billing. While the core cost is based on token usage, there are other factors to consider:
- Fine-Tuned Models: If you’re customizing Azure OpenAI models for specific tasks, you’ll incur costs for training, hosting, and inference (the actual use of the model). It’s important to be aware of the hourly hosting cost, as it applies even when your fine-tuned model isn’t actively processing requests.
- Additional Azure Services: Integrating Azure OpenAI with other Azure services, such as Azure Monitor for logging and alerting, will add to your overall costs. It’s essential to factor in these potential expenses when planning your budget.
Fine-Tuning Deep Dive: OpenAI vs. Azure OpenAI
The cost of fine-tuning models can be a major consideration. Initially, I was drawn to Azure OpenAI for its security and privacy features. However, the cost of fine-tuning did give me pause. Let’s take a closer look at the price comparison:
Important Note: OpenAI’s fine-tuning costs are solely per 1,000 tokens, while Azure has both hourly training and hosting fees in addition to per-token costs for input and output.
This comparison reveals that the choice between OpenAI and Azure OpenAI for fine-tuning is nuanced. While OpenAI may seem initially appealing due to its per-token pricing model, Azure OpenAI offers advantages in terms of security, compliance, and scalability, which may be crucial for larger organizations or projects with sensitive data.
Monitoring and Managing Costs: Your Ongoing Responsibility
Once your Azure OpenAI resources are up and running, the cost management journey doesn’t end. Here’s where Microsoft’s robust suite of tools comes in handy:
- Cost Analysis: This tool lets you dive into your Azure OpenAI costs, visualizing them in graphs and tables across different time periods. You can even break down costs by meter (specific usage categories) to pinpoint exactly where your spending is concentrated.
- Budgets and Alerts: Setting budgets and alerts is a proactive way to stay on top of your spending. You’ll receive notifications if your costs start to exceed your predefined thresholds, giving you time to take action.
- Exporting Cost Data: If you need to analyze costs in more depth or share them with other stakeholders, you can easily export your cost data to a storage account for further analysis in tools like Excel or Power BI.
Choosing the Right Platform: OpenAI vs. Azure OpenAI
As you embark on your AI journey, you might wonder whether to go directly with OpenAI’s offering or opt for Azure OpenAI. The choice often depends on your specific needs and scale:
- Smaller-Scale Projects: If you’re just starting out and security isn’t your top priority, OpenAI’s platform might be a cost-effective option initially. It’s relatively inexpensive to get started and can be suitable for smaller projects.
- Growing Usage: However, once you start processing hundreds of millions of tokens or more per month, Azure OpenAI often becomes the more economical choice, especially for fine-tuning larger models. Azure OpenAI provides a more scalable and secure environment for enterprise-grade applications.
Important Considerations:
- Inactive Fine-Tuned Models: To optimize costs, keep in mind that Azure automatically deletes deployments of fine-tuned models that remain inactive for more than 15 days. However, the underlying model itself isn’t deleted, and you can redeploy it anytime.
- Azure Prepayment: If you have Azure credits, you can use them to offset some of your Azure OpenAI costs, but be aware that they can’t be used for third-party products or services within the Azure Marketplace.
Concluding thoughts:
Managing Azure OpenAI costs doesn’t have to be a daunting task. By understanding the pricing model, leveraging Microsoft’s cost management tools, and implementing smart strategies, you can harness the power of AI while keeping your budget under control.
References:
Azure Pricing — https://azure.microsoft.com/en-gb/pricing/details/cognitive-services/openai-service/
