Modern AI Agents are becoming increasingly powerful, but their true potential is unlocked when they can interact with external systems. In my previous post, I discussed how to create MCP (Model Context Protocol) servers and the advantages of using MCP to connect AI models to external tools and data sources vs. traditional function callings. In this follow-up post, I will dive into using MCP tools with Azure AI Foundry Agents.
Azure
- The serverless technology has been around for a while now, and it has revolutionized the way we build and deploy applications. Azure Functions, a serverless compute service from Microsoft Azure allows to run code on-demand without having to manage infrastructure. In this article, we will explore how running the Azure Functions on a dedicated Kubernetes cluster, such as Azure Kubernetes Services (AKS), can provide added benefits and flexibility to your applications.
- API Management is a multi-faceted process that involves several teams and stakeholders. The API Management process includes designing, building, publishing APIs. The process is iterative and involves continuous improvement. For instance, it may involve adding new APIs, updating existing APIs, or deprecating APIs. It is important to adopt DevOps techniques to manage the API lifecycle to ensure quality, consistency, and improved productivity.