Source Code:- https://github.com/Priyanshu-ai902/k8s-disaster-recovery-automation
:) I built a Kubernetes disaster recovery and backup automation system to handle real-world failure scenarios like accidental namespace deletion or configuration loss. Kubernetes is self-healing at the pod level, but it does not protect you from human mistakes, so this project focuses on backing up and restoring the actual cluster state.
The system connects directly to the Kubernetes API using Node.js, fetches live resources, and cleans the YAML by removing runtime-specific fields like UID, resourceVersion, timestamps, and status. This makes the backups portable and safe to re-apply on the same or a different cluster. Each backup is stored in a timestamped format so the cluster can be restored to a specific point in time.
To test it properly, I deployed a production-like application, verified it was running, then intentionally deleted the resources to simulate a disaster. The restore logic reads the cleaned YAML files and recreates the resources, and I validated the recovery by watching the deployments and pods come back to a running state.
To make it production-oriented, I containerized the backup logic and ran it inside the cluster using a Kubernetes CronJob. I also implemented RBAC with a dedicated ServiceAccount and least-privilege access so the automation can safely read cluster resources without excessive permissions. This project helped me understand Kubernetes internals, metadata handling, RBAC, and how real disaster recovery systems are designed beyond basic self-healing.
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