From Telemetry to Autonomous Operations: AI-Powered Processing, Self-Healing Kubernetes with F5 WAF

Abstract

Every second, billions of telemetry events flow from connected devices into Kubernetes-based platforms, powering critical business insights, customer experience monitoring, and device health analytics. At this scale, even brief service disruptions, security incidents, or infrastructure failures can create significant operational and business impact. This session explores how we built a cloud-native telemetry platform on Kubernetes designed to process billions of real-time events while maintaining scalability, reliability, security, and low latency. We will demonstrate how AI-powered agents continuously analyze telemetry streams, identify anomalies, assist with root-cause analysis, and trigger automated remediation workflows to enable self-healing operations and minimize downtime. The session will also cover the integration of F5 WAF to protect telemetry APIs and services against OWASP threats while maintaining performance at scale. Attendees will gain practical insights into designing resilient Kubernetes architectures, implementing AI-driven operational automation, and integrating security controls into high-volume data platforms. Through real-world architecture patterns, operational lessons, and automation strategies, this session provides actionable guidance for platform engineers, SREs, and cloud-native practitioners seeking to reduce operational overhead, improve system reliability, strengthen security, and accelerate the adoption of autonomous operations.