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Building Efficient Networks for AI: Cisco and Aviz Networks Bootcamp Recap

Blog date iconJuly 1, 2025Blog category iconONES & SONiC
Building Efficient Networks for AI: Cisco and Aviz Networks Bootcamp Recap

TL;DR

  • How to design lossless, high-performance fabrics for AI/LLM workloads
  • Cisco 8000 series with Silicon One + SONiC explained
  • Techniques for RDMA over Converged Ethernet (RoCE v2), Priority Flow Control (PFC), and Explicit Congestion Notification (ECN)
  • How Aviz ONES delivers multi-vendor observability and real-time congestion insights
  • Validated leaf-spine topologies and blueprints for scalable AI clusters

Overview

As data centers evolve from CPU-centric to GPU-centric architectures, building networks that can handle massive AI workloads has become mission-critical. At the recent Cisco and Aviz Networks joint bootcamp, attendees got an inside look at how to design modern, lossless, high-performance networks for AI and LLM workloads.

Solving AI challenges with SONiC
Figure 1: Solving AI Challenges with SONiC

Cisco 8000 + SONiC for AI fabrics

Satish Surani, Director of Product Management at Cisco, showcased how the Cisco 8000 series, powered by Silicon One and SONiC, delivers a flexible, open networking stack designed for today’s demanding AI clusters. Key topics included the importance of RoCE v2, PFC, and ECN to maintain low latency and lossless traffic under heavy GPU workloads.

Cisco 8000 networking topology diagram
Figure 2: Cisco 8000 Networking Topology Diagram

Observability and blueprints with Aviz ONES

Aviz demonstrated how its Open Networking Enterprise Suite (ONES) and real-time telemetry can monitor and optimize congestion points, validate QoS policies, and provide deep observability across multi-vendor environments.

The session also covered best practices for building scalable, non-blocking leaf-spine topologies and how Cisco and Aviz jointly deliver validated blueprints for large-scale AI infrastructure. As AI clusters grow, open, programmable fabrics with robust congestion management are foundational for faster job completion and predictable performance.

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FAQ

1. What was the main focus of this joint bootcamp?

Designing AI-ready data centers using Cisco 8000 switches running SONiC NOS—and how Aviz ONES delivers observability, congestion management, and telemetry for lossless, high-bandwidth AI workloads.

2. Why is lossless networking so important for AI workloads?

AI clusters require:

  • High bandwidth
  • Low latency
  • Zero packet loss for RDMA flows

Even slight congestion can increase training job completion time. Techniques like PFC and ECN keep traffic lossless and predictable.

3. What is RDMA and why does it matter?

Remote Direct Memory Access (RDMA) allows data transfer directly between server memory without CPU involvement, which reduces latency, increases throughput, and optimizes GPU-centric workloads. RoCE v2 enables RDMA on Ethernet networks.

4. How does ECN help manage congestion?

Explicit Congestion Notification (ECN) marks packets experiencing congestion instead of dropping them. End devices receive feedback to adjust rates, preventing packet loss and stabilizing AI training performance.

5. What is Priority Flow Control (PFC) and how is it used?

PFC provides lossless service for specific traffic classes. In AI networks, PFC:

  • Guarantees no packet drops for RDMA traffic
  • Enables mixed traffic without sacrificing critical flows
  • Works with ECN for robust congestion management
6. How does Cisco’s Silicon One support AI networking?

Cisco’s Silicon One G200 provides:

  • Ultra-low latency
  • High radix (51.2 Tbps capacity)
  • Fully shared packet buffers for burst absorption

These enable massive GPU clusters with efficient load balancing and optimized job completion times.

7. What is the role of SONiC NOS in this architecture?

SONiC is an open, modular NOS customers can customize. Cisco 8000 switches run SONiC with enterprise support, ensuring open standards, rapid feature updates, and community-driven innovation.

8. How does Aviz ONES integrate with Cisco hardware?

ONES acts as an agentless observability and orchestration layer that:

  • Collects multi-vendor telemetry
  • Monitors PFC, ECN, and RDMA health
  • Visualizes real-time AI traffic versus non-AI traffic
  • Automates troubleshooting across leaf-spine and super-spine topologies
9. What was shown in the factory topology demo?

The live demo featured:

  • Cisco 8100 switches configured for PFC and ECN
  • Factory topology with non-blocking bandwidth
  • Real-time visibility of congestion points and queue health via Aviz ONES

This demonstrated keeping AI traffic lossless and optimizing cluster efficiency.

10. How does ONES handle multi-vendor, hybrid networks?

ONES is designed for openness:

  • Supports SONiC, Cisco XR, Arista EOS, and more
  • Uses standard APIs and collectors—no heavy agents
  • Provides a unified observability dashboard for hybrid and AI fabrics
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Tags:aviz onesCiscoCisco 8000Silicon Onesonic Cisco Aviz BootcampRoCE v2 PFC ECNLossless AI Fabric DesignLeaf-Spine TopologySilicon One SONiC