When it comes to AI, businesses confront unprecedented challenges in efficiently managing computational resources. That’s why Azure OpenAI Service is a critical platform for organizations seeking to leverage cutting-edge AI capabilities, and it makes provisioned reservations an essential strategy for intelligent cost savings.
Business needs change, of course, and flexibility in managing these reservations is vital. In this blog, we’ll not only explore what makes Azure OpenAI Service provisioned reservations indispensable for organizations seeking resilience and cost efficiency in their AI operations, but also follow a fictional company, Contoso, to illustrate real-world scenarios where exchanging reservations enhances scalability and budget control.
The crucial role of provisioned reservations in modern AI infrastructure
Azure OpenAI Service provisioned reservations help organizations save money by committing to a month- or yearlong provisioned throughput unit reservation for AI model usage, ensuring guaranteed availability and predictable costs. As mentioned in this article, purchasing a reservation and choosing coverage for an Azure region, quantity, and deployment type, reduces costs as compared to being charged at hourly rates.
Actively managing and monitoring these reservations is paramount to unlocking their full potential. Here's why:
- Optimizing utilization: Regular monitoring ensures that your reservations align with your actual usage, preventing wasted resources.
- Adapting to business changes: As business needs shift, reservations can be adjusted to accommodate evolving requirements.
- Avoiding over-commitment: Proactive management helps prevent over-purchasing reservations, which can lead to unnecessary expenses.
- Enhancing cost control and accountability: By tracking reservation usage and costs, organizations can maintain better control over their AI budgets.
- Leveraging AI usage insights: Analyzing reservation utilization provides valuable insights into AI application performance and usage patterns.
The value of exchanging provisioned reservations
One of the most powerful aspects of provisioned reservations is the ability to exchange them. This flexibility allows businesses to adapt their commitments to better align with their evolving needs. Exchanges can be initiated through the Azure Portal or via the Azure Reservation API, offering seamless adjustments.
Consider Contoso, a global technology firm leveraging Azure OpenAI Service for customer support chatbots and content generation tools. Initially, Contoso’s needs were straightforward, but as their business expanded, their AI requirements changed. This is where the exchange feature proved invaluable.
Types of provisioned reservations exchanges
Contoso leveraged several types of exchanges to optimize their Azure OpenAI Service usage:
- Region exchange: Contoso initially committed to a reservation in the East US region. However, as their operations expanded into Western Europe, they needed to shift their AI workloads. By exchanging reservations, they were able to apply their discounted billing to the West Europe region, ensuring optimal performance for their growing user base.
- Deployment type exchange: There are three types of deployment: Global, Azure geography (or regional), and Microsoft specified data zone. Contoso initially reserved regional deployments for their inference operations, but because of growing demand they switched to global deployment. This means their Azure OpenAI Service prompts and responses will now be processed anywhere that the relevant model is deployed. By exchanging reservations from regional to global, they were able to apply their reservation savings ensuring seamless cost savings for their critical application.
- Term exchange: Contoso initially committed to a one-month reservation. However, they soon realized their need for ongoing service and wanted to allocate resources more efficiently. By exchanging reservations, they switched to a one-year term, allowing them to budget more effectively.
- Payment exchange: Contoso started with an upfront payment model. However, for better cash flow management, they transitioned to a monthly payment plan through a payment exchange.
Changing the scope of provisioned reservations
As Contoso’s use of Azure OpenAI Service expanded across multiple departments, they needed to modify their reservation scope. Azure offers the ability to scope reservations to individual resource groups or subscriptions, to subscriptions within a management group, or to all subscriptions within a billing account or billing profile.
Contoso used Microsoft Cost Management to modify the scope of their reservations, ensuring that each department had the necessary resources.
Setting up automatic renewals for provisioned reservations
To prevent service disruptions and maintain budget predictability, Contoso enabled automatic renewal for their reservations. Automatic renewals offer several benefits:
- Continuous service: Ensures uninterrupted billing for Azure OpenAI Service.
- Budget predictability: Maintains consistent costs over time.
- Reduced administrative overhead: Eliminates the need for manual renewal processes.
Enabling auto-renewal in the Azure Portal is a straightforward process, ensuring that Contoso’s AI operations continue uninterrupted.
Reviewing the provisioned reservation utilization report
Contoso’s finance and IT teams regularly review their provisioned reservation utilization report to ensure they are getting the best value from their investment. These reports, accessible through Azure Cost Management, provide insights into reservation usage and help identify areas for optimization.
Analyzing utilization reports allows Contoso to:
- Identify underutilized resources.
- Adjust reservations to match actual usage.
- Optimize costs and improve efficiency.
Setting up utilization alerts
To proactively monitor their reservation usage, Contoso configured reservation utilization alerts in Microsoft Cost Management. These alerts notify them if usage drops below a set threshold, allowing them to take timely action.
By setting up utilization alerts, Contoso can:
- Receive real-time notifications of usage changes.
- Adjust reservations to avoid waste.
- Maintain optimal resource utilization.
Best practices for managing Azure OpenAI Service provisioned reservations
Azure OpenAI Service provisioned reservations offer a powerful way to control costs, but proactive management is essential for maximizing their value. As we have seen, Contoso implemented several best practices to maximize the benefits of provisioned reservations:
- Regular usage monitoring: Continuously tracking usage to identify trends and optimize resource allocation.
- Strategic adjustments and exchanges: Adapting reservations to match evolving business needs.
- Implementing governance policies: Establishing clear policies for reservation management and usage.
- Automating alerts and reporting: Configuring alerts and reports to proactively monitor reservation usage.
By leveraging the flexibility of reservation exchanges and implementing best practices, any business can optimize their AI investments and drive long-term efficiency. Embracing these strategies will empower your organization to fully capitalize on the transformative potential of Azure OpenAI Service. Find out more by completing the Azure OpenAI Service provisioned reservation learn module.
Additional Resources:
Microsoft