Skip to main content

Aviz Networks outlines AI fabric lifecycle management and RDMA visibility at NVIDIA GTC Berlin 2026

2 companies named across 10 categories, one of 581 articles referencing Nvidia. Previous coverage: Rafay Platform details workload orchestration for AI factories (Aug 2026).

Companies mentioned

Best suited for

Seniority
Architect
Job function
Network / Network Architect
Persona
Network Architect
Buyer role
Architect / Technical Evaluator
Buyer journey
Need to Buy
Adoption curve
Early Majority
Technology maturity
Operational Expansion
Industry
Information Technology / Technology Hardware & Equipment / Communications Equipment / Computer Networking

Our classification, not the publisher's statement. Best suited for, not only for.

Aviz NetworksNVIDIA GTC Berlin 2026 briefing centers on operationalizing AI fabric through open networking, packet-level RDMA visibility, and AI-fabric lifecycle management across NVIDIA Spectrum-X and BlueField-3 DPUs.

Research Overview

The post argues that GPU scale can expose network bottlenecks, especially when low-latency east-west traffic and RDMA or RoCE communications constrain performance.

It states that many monitoring tools provide limited visibility into RDMA traffic, complicating diagnosis when congestion or dropped packets appear and contributing to degraded GPU utilization or longer training times.

Key Findings

The vendor frames network observability and workload-aware automation as requirements for diagnosing congestion patterns and supporting optimization as AI clusters grow.

It also links monitoring gaps to operational outcomes, describing troubleshooting as difficult when east-west and RDMA behavior is not observable, and describing ripple effects from traffic patterns across the fabric.

Technical Breakdown

The briefing describes an approach to RDMA observability using Aviz’s Deep Network Observability Suite running with Service Nodes on NVIDIA BlueField-3 DPUs to provide packet-level visibility.

It states this visibility does not require hardware changes or rewiring, and that it is intended to identify bottlenecks in hours rather than days.

Operational Impact

The post describes Aviz ONES for NVIDIA AI Factory as a lifecycle-management capability for activities such as configuration consistency management, software updates, monitoring, troubleshooting, and optimization.

It says the approach targets end-to-end control of AI fabrics and aims to reduce manual stitching across multiple network toolkits through uniform telemetry and multi-vendor orchestration.

Product and Ecosystem Positioning

For orchestration, the post states that the 2-in-1 solution supports NVIDIA Spectrum-X orchestration down to packet-level visibility enabled by NVIDIA BlueField-3 DPUs.

On open networking, it cites Software for Open Networking in the Cloud (SONiC) as an option that provides hardware-choice flexibility intended to reduce vendor lock-in and allow hardware swaps over time.

Overall, the blog presents an operational model that combines open networking with RDMA packet-level observability and AI-fabric lifecycle management for environments built on NVIDIA Spectrum-X and BlueField-3 DPUs, a fact-based summary of the vendor blog signals brief.

Blog post, originally published by Yohan Kattackel Bobby at aviznetworks.com.