Why AI Observability Is Drowning in Noise with Danielle Cook, Akamai

Description

AI workloads create unprecedented noise in observability pipelines. Danielle Cook, Senior Product Marketing Manager at Akamai, explains why treating AI as a workload requires a completely different observability approach. The complexity of Kubernetes combined with AI means teams are drowning in signals. Cook discusses how to identify what actually matters when monitoring AI infrastructure and why the cloud native community is still figuring out how to simplify this challenge. This conversation highlights the critical gap between automation and true intelligence in modern observability practices. Company URL: https://www.akamai.com Read the full story at www.tfir.io #AIObservability #Kubernetes #CloudNative #Akamai #ArtificialIntelligence #DevOps #Infrastructure #Observability #AIWorkloads #PlatformEngineering