Chris Ayers: .NET Aspire and AI – Episode 335

Challenges

  • Integrating AI capabilities into .NET applications efficiently
  • Understanding how .NET Aspire enhances cloud-native development
  • Managing scalability and performance in AI-powered applications

Solutions

  • Insights from Chris Ayers on leveraging .NET Aspire for modern AI-driven solutions
  • Best practices for integrating AI into .NET applications with cloud-native architectures
  • Strategies for optimizing performance and scalability when using AI in .NET

Benefits

  • Faster development and deployment of AI-enhanced .NET applications
  • Improved scalability and efficiency with .NET Aspire’s cloud-native features
  • Enhanced application intelligence through seamless AI integration

Chris Ayers is a Senior Site Reliability Engineer on Microsoft’s AzRel Risk SRE team, drawing on years of experience in cloud architecture, software development, and DevOps practices. He’s passionate about continuous improvement, driving reliability, and sharing industry best practices. Outside of work, Chris is a devoted father, technology enthusiast, and avid gamer. Connect with him online to explore insights into cloud operations, agile methodologies, and more. He also organizes DevOpsDays Tampa Bay.

Topics of Discussion:
[02:50] Chris Ayers’s career journey and formative moments in site reliability engineering.
[03:33] The importance of being open to learning and stepping outside your comfort zone.
[08:53] Chris’s talk on Aspire, Azure, and Open AI.
[09:30] How Chris is improving Azure’s reliability through internal innovation.
[10:16] Benefits of Aspire: orchestration, integration, and abstraction for infrastructure.
[12:29] AI extensions in Aspire: how they enable developers to work with different AI models like OpenAI and local models.
[14:09] Using OpenTelemetry for seamless integration and monitoring in Azure.
[18:38] Prompt engineering: crafting prompts as part of business logic.
[20:50] Exploring agentic AI development and multi-agent chatbots.
[21:05] AI use cases in healthcare and responsible AI principles.
[29:22] Simplifying Azure resource management with Aspire and opinionated defaults.
[32:35] Using Honeycomb and other tools for effective telemetry and logging.
[33:39] Hugging Face and KAITO: enabling access to a marketplace of specialized AI models and Kubernetes AI integration.
[34:10] Running Olama models locally: balancing scale, cost, and use cases.
[39:38] AI as a tool to enhance productivity rather than replace people.