Explore the shift from reactive to predictive DevSecOps with Akshay Mittal. This discussion covers how AI-Augmented DevSecOps and Agentic Workflows are creating self-healing systems, the critical role of Explainable AI (XAI), and a four-layer architecture for building scalable, enterprise-grade AI solutions.
Akshay Mittal discusses the evolution of enterprise AI, focusing on the crucial shift from reactive to predictive security through AI-augmented DevSecOps. He explores how to productionize agentic AI workflows using AIOps and Kubernetes, and emphasizes the non-negotiable need for explainable AI (XAI) in critical systems.
Rani Radhakrishnan, Principal at PwC, discusses the convergence of MLOps and IT operations, the practicalities of deploying AI agents, and the strategic considerations for scaling and sustaining AI initiatives in the enterprise. The conversation covers the shift from experimentation to ROI, the importance of human-in-the-loop processes, and the evolving skillsets required for future-ready IT.
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.
Shraddha Yeole from Cisco ThousandEyes explains how they are transforming network observability by moving from complex dashboards to AI-augmented storytelling. The session details their use of an LLM-powered agent to interpret vast telemetry data, accelerate fault isolation, and improve MTTR, covering the technical architecture, advanced prompt engineering techniques, evaluation strategies, and key challenges.
Amanda Downie explains the shift from reactive IT firefighting to proactive optimization, detailing how AI agents and LLMs use predictive analytics, topology mapping, and continuous learning loops to anticipate and prevent system issues before they occur.