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Traffic Engineering in AI DCI/WAN for AI Traffic#

OCP Global Summit 2026 digest Program Core pick 12–15 October 2026

Abstract Recording

Yuanchao SU (Alibaba Cloud), Clarence Filsfils (Cisco)

Play the recording: Traffic Engineering in AI DCI/WAN for AI Traffic

  • Why: Geo-distributed AI training is now the driving WAN workload; this pairs the SRv6 inventor with a hyperscaler that has actually deployed it, covering both the problem framing and two real deployments.
  • What: The traffic-engineering problem and requirements for AI DCI/WAN connecting geographically distributed training data centers — how it was solved for legacy non-AI traffic, why that solution falls short for synchronized, elephant-heavy AI flows, and the AI-specific solution including the data and telemetry collection needed to drive it (from abstract only).
  • How: TE over the WAN for AI job traffic (presumably SRv6-based given the co-author); the abstract emphasizes required telemetry and two real deployment case studies rather than architecture alone.
  • Where applicable: Alibaba Cloud production deployments — org-specific specifics expected; the requirement analysis (bursty synchronized traffic over constrained DCI) generalizes to any multi-DC training operator. Pairs with the scale-across panel below.