Scaling AI agents to meet high user demand is often seen as a daunting challenge. However, with the right tools and strategies, it can be more straightforward than you might think. In this talk, I offer a fresh perspective on scaling AI agents in the cloud, challenging traditional approaches and introducing innovative solutions.
This talk addresses common challenges in AI agent scaling, including resource management, latency issues, and integration complexities. We'll explore how DAPR's sidecar pattern mitigates these problems by abstracting away infrastructure concerns, while Semantic Kernel's modular approach simplifies AI integration and improves maintainability.
I will demonstrate how DAPR and Semantic Kernel can revolutionize your AI integration strategy. By showcasing code snippets and implementation techniques, you'll gain practical insights into overcoming scalability challenges and transforming your applications.
Key learning objectives include:
- Understanding architectural patterns for scalable AI agents
- Implementing efficient resource management strategies
- Leveraging DAPR and Semantic Kernel for seamless AI integration
Developing resilient and performant cloud-based AI solutions
By the end of this session, you'll have actionable strategies and hands-on knowledge to implement scalable AI agents, enhancing both performance and user experience. Gain the confidence to deploy cloud-based AI solutions effectively and unlock new potential for your applications.

This is a brand new presentation. I am incorporating some of my own experience that I have gained in customer projects.