Managing Data Streaming Infrastructure in the Age of AI - Simplifying Tooling and Integrating with MCP

Learn how to streamline data streaming infrastructure management across Apache Pulsar, Apache Kafka, and StreamNative Cloud by consolidating fragmented tooling and integrating AI capabilities through the Model Context Protocol (MCP). Discover StreamNative's unified CLI approach with SNCTL v1 that eliminates the complexity of juggling multiple command-line interfaces, Terraform providers, and resource operators. Explore how MCP standardizes interactions between AI agents and streaming infrastructure, reducing integration complexity from MxN to M+N connections while providing AI agents with structured, secure interfaces for real-time operations. Master the implementation of access controls through RBAC systems and service accounts, and understand how to expose function logic as MCP tools with proper schema conversion. Gain insights into creating AI-ready infrastructure that maintains security and operational efficiency while enabling seamless AI agent interactions with data streams.