Anomaly detection

AI, AIOps & Agentic AI in Data Storage Observability

AI, AIOps & Agentic AI in Data Storage Observability

Prabira Acharya explains that managing data storage without observability is like driving a car without a dashboard. The talk outlines the seven pillars of storage observability, the critical role of AI in analyzing vast amounts of data for anomaly detection and predictive analytics, and the evolution toward agentic AIOps for creating self-healing and self-managing storage infrastructures.

AI Agents: Transforming Anomaly Detection & Resolution

AI Agents: Transforming Anomaly Detection & Resolution

Martin Keen explores how agentic AI can significantly reduce IT downtime and Mean Time To Repair (MTTR) by moving beyond naive data dumps and embracing context-aware analysis. The key lies in using topology-aware correlation to curate relevant data for an AI agent, which can then systematically identify the root cause, provide explainable insights, and generate actionable remediation steps, ultimately augmenting human SREs rather than replacing them.