As cloud environments scale, manual incident triage and resolution become bottlenecks. This session explores how AI-powered automation can transform incident management workflows in cloud-native systems. Using ML models and cloud infrastructure like Azure, we’ll discuss how AI can automate classification, prioritize incidents, and route tasks in real-time, reducing mean time to resolution (MTTR) and ensuring service reliability.

We’ll cover the integration of AI models for incident triage, dynamic SLA management, and real-time prioritization, enabling self-healing systems that scale with cloud demands. Key topics include:
• Automated incident classification and escalation with LLMs.
• AI-driven dynamic routing based on severity levels and historical incident data.
• Predictive scaling to handle high volumes of incidents using cloud-native tools (e.g., Azure, Kubernetes).
• Data privacy and security in AI-driven cloud automation.