Fast Network Notifications Problem Statement#

Jie Dong (Huawei), Mike McBride (Futurewei), François Clad (Cisco), Zhaohui (Jeffrey) Zhang (Juniper), with contributors from China Telecom, China Mobile, China Unicom, Tencent, Telefónica, and Turkcell

• Why: AI training/inference and large-scale cloud services need the network to adapt faster than today's feedback loops allow. This is the anchor problem statement for the whole FANTEL (Fast Notifications for TE and Load Balancing) cluster in RTGWG, carried forward from the IETF 123 BoF with unusual breadth of operator/vendor co-authorship.
• What: A structured problem statement defining what fast network notifications must carry, who must receive them, and how they get delivered — the requirements frame every other fast-notification draft at this meeting builds against.
• How: Tabulates four gaps in current mechanisms: (1) hop-by-hop control-plane distribution and round-trip end-to-end signaling (ECN) are too slow; (2) binary/threshold feedback is too coarse for precise adjustment; (3) decisions are made from a local view, yielding sub-optimal rerouting; (4) naive wide distribution churns the control plane. Proposes an information model (event type, location, fine-grained metrics such as utilization, queue length, delay, jitter, loss, plus path and flow 5-tuple identification), a recipient model (adjacent/non-adjacent routers, ingress nodes, end hosts, controllers/PCE/NMS), and delivery modes (unicast, multicast, hop-by-hop, scoped flooding) with subscription to suppress overhead.
• Where applicable: General IP fabrics — use cases span intra-DC AI/ML, cross-DC training and inference, CDN/DC interconnect, and cloud-edge. Early-stage at the meeting (individual draft -01), but companion drafts now cite it on the WG track as draft-ietf-rtgwg-net-notif-ps, so adoption momentum is real.