Can AI Networks Be Operated Before They Reach Production?


AI factories have already introduced a completely new way of thinking regarding networking. Network used to serve the purpose of connecting devices. Nowadays, it influences the performance of workload execution, the level of isolation, usage of GPU, troubleshooting speeds, etc.

It has become possible to validate the operational processes by creating a digital twin environment before any changes get implemented. By doing that, it would be possible to test AI fabrics, topology configuration options, create tenants, telemetry gathering, and much more within the environment.

It is important not to forget about switching from automated deployment and management to intelligent operations. It will be possible to analyze alarms, find reasons for network congestion, detect drifts in configuration, examine telemetry information, generate health summaries, and so on. In other words, there won't be such a need to use multiple dashboards and CLI configurations.

To sum up, an AI-friendly network must be designed, tested, and managed within the same process. Validation and testing of both deployment on Day-0 and operations on Day-N would make operators feel more confident when implementing changes in production.

Explore how digital twin environments and AI-assisted operations can help teams build more reliable AI network infrastructure. https://aviznetworks.com/resources/blogs/bringing-ai-network-operations-to-life-in-nvidia-dsx-air-with-aviz-ones-and-network-copilot

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