Automates the creation and configuration of experimental network slices on the FABRIC testbed using Python-based API patterns.
This skill enables Claude to programmatically design, validate, and deploy complex network experiments on the FABRIC testbed. It guides users through specifying node requirements—such as CPU, RAM, and specialized hardware like GPUs or FPGAs—and handles intricate networking setups including Layer 2 segments and Layer 3 FABnet routing. By providing standardized code patterns for error handling, non-blocking submissions, and persistent storage, it streamlines the experimental lifecycle from initial request to a ready-to-use research environment.
主な機能
01Configurable Layer 2 and Layer 3 (FABnet) network topologies
02Automated node provisioning with custom resource specs (CPU, RAM, Disk)
032 GitHub stars
04Support for post-boot configuration and SSH connectivity management
05Support for specialized hardware components like GPUs, SmartNICs, and NVMe
06Built-in validation and robust error handling for slice deployments
ユースケース
01Creating complex Layer 3 network topologies with automated routing across FABRIC sites
02Deploying a multi-site distributed system for network latency research
03Setting up GPU-accelerated environments for distributed AI/ML experiments