Can Your Observability Stack Handle 24/7 Agentic Query Volume?

With enterprises now rushing to integrate AI agents into their operations and security, the most imperative focus now becomes the AI model itself. However, Eric Tschetter, Chief Architect at Imply, believes the real challenge is within the data infrastructure that supports these systems.In the recent episode of the Tech Transformed podcast, Kevin Petrie, BARC Vice President of Research, sat down with Tschetter to talk about how AI is actually increasing the current needs around scale, performance, and data access.“Agents are always running queries. They’re always doing stuff,” Tschetter stated.Unlike human analysts, AI systems work continuously, producing much higher query volumes and putting more pressure on the data platforms underneath. This leads to a greater demand for observability architectures that can manage more data, more users, and more machine-to-machine interactions without losing speed.For Tschetter, the solution is not to create new observability tools, but to rethink the data layer that supports them.Key TakeawaysAI is transforming observability and security disciplines.The observability warehouse concept is gaining traction.AI agents increase the volume of queries significantly.Data silos remain a major challenge for enterprises.Collaboration between IT and security teams is essential.Observability and security teams often consume the same data.A decoupled architecture can enhance data accessibility.The semantic layer must support multiple query languages.Effective data management is crucial for AI-driven workloads.Data should be stored once and accessed from multiple platforms.Chapters00:00 Introduction to AI and Observability02:08 Challenges in Observability with AI06:44 Modernising Architecture for Observability10:49 Decoupled Observability and Semantic Layers16:31 Collaboration Between IT and Security Teams22:23 Imply's Observability Warehouse and Data LakesFor more information on AI, observability and Imply’s observability warehouse and data lakes, please visit imply.io.For further information on all things B2B Tech, please visit em360tech.comImply LinkedIn: @Imply Imply X: @implydataImply YouTube: @ImplydataEM360Tech YouTube: @enterprisemanagement360EM360Tech LinkedIn: @EM360TechEM360Tech X: @EM360TechFollow: @EM360Tech on YouTube, LinkedIn and XStay connected for more expert insights, podcast episodes, and enterprise data strategy discussions