When OpenAI discovered they could reclaim 30,000 CPU cores simply by tuning the log-forwarding agent Fluent Bit—disabling a single function that ate ~35 % of one server’s cycles—something large and systemic became undeniable. In this episode, F5's Lori MacVittie, Joel Moses, and observability expert, Chris Hain, break down the hidden cost of telemetry in AI-heavy architectures, why “logging is free” is a myth, and how modern systems demand a new breed of high-speed telemetry planes.

Listen in to learn how Fluent Bit’s file-watching overhead compounded at scale, why profiling matters, and what enterprises can do now to control AI observability costs.