ResilienceIQ — Autonomous Cloud Resilience Engineering using Agentic...

ResilienceIQ — Autonomous Cloud Resilience Engineering using Agentic AI and Self-Healing Kubernetes Modern cloud systems fail silently. Servers crash. Networks slow down. Disks fill up. And engineers only find out when real users are already affected. ResilienceIQ solves this. It is an AI-powered platform that deliberately breaks your own cloud infrastructure — in a controlled way — before real failures happen. Here is how it works. We deploy a live application on AWS EKS — Amazon's managed Kubernetes service — running four microservices: login, payment, product, and database, all inside Docker containers managed by Kubernetes pods. Prometheus collects live metrics every five seconds. Grafana displays them as real-time graphs. The moment something goes wrong, alerts fire instantly. Now the intelligent part. Google Gemini AI reads the current system health — CPU usage, memory, disk, network — and autonomously decides which fault to inject. It also predicts the blast radius — which services will be affected — before anything runs. Chaos Mesh then executes the experiment. We perform twenty-one structured fault tests across six categories — pod failures, CPU and memory stress, network delays and packet loss, node shutdowns, disk fill, and application-level errors. The system breaks. Grafana turns red. And then — Kubernetes self-heals. Pods restart automatically. The platform measures exactly how long recovery takes. This is called MTTR — Mean Time To Recover. Finally, Gemini AI writes a complete Root Cause Analysis report, calculates a Resilience Score out of one hundred, and sends a Slack notification — all automatically. The entire cycle — break, detect, recover, report — happens with a single button click. No manual work. No guesswork. ResilienceIQ. Infrastructure tested before it fails.