Overcoming Challenges for AI-Fabric with SONiC - Madhu Paluru, Aviz Networks#

Madhu Paluru, Director of Engineering, Aviz Networks

• Why: Operating the network under AI training/inference traffic (elephant flows, incast, config-error sensitivity) is a current, fast-moving problem; this collects the operational requirements and proposes SONiC-based answers.
• What: How GenAI training and inference workloads stress network infrastructure, and proposals to manage AI fabrics on SONiC via config automation to minimize configuration errors and deep-visibility tooling for faster troubleshooting. (from abstract only)
• How: SONiC's open control/data plane as the base, with automation layering to reduce human config errors and visibility tooling for diagnosis in AI-fabric conditions.
• Where applicable: SONiC-based AI fabrics; vendor-presented (Aviz builds a commercial SONiC stack), so treat solution specifics as a pitch-informed roadmap rather than validated deployment results.