AI Networking: The Observability Blueprint for Modern AI Workloads

The AI Revolution is Here, and It’s Accelerating

Enterprise adoption of AI agents and applications is scaling rapidly, powering real-time intelligence and operational efficiency. But as organizations move from experimentation to ROI-driven deployments, the networking and operational foundation is under unprecedented strain. A single bottleneck or misconfigured link can stall GPUs, waste millions in compute, and delay innovation. Blind spots in the network are no longer minor inconveniences—they are critical risks.

With agentic AI on the rise, autonomous tools are running businesses faster and smarter than ever. But speed comes with risk: these agents have deep access to sensitive systems. Unlocking AI's full potential hinges on a new imperative: An Optimized Network for AI with Integrated 360° Observability and Security. 

The Hidden Costs of a Blind AI Network

AI training clusters are extremely sensitive to physical-layer issues. Even minor problems—such as poor fiber hygiene, cable disturbances, or aging components—can disrupt synchronization across thousands of GPUs, delaying Job Completion Time (JCT). At scale, failures occur almost daily, and subtle "soft failures" often evade detection, showing up instead as step-time jitter, CCL stalls, or idle GPUs.

A network that "looks fine" can still impair training. This is where "up" isn't the same as "good". Unlike general-purpose workloads, where TCP retransmissions can compensate for lossy or flapping links, distributed training frameworks cannot hide jitter or retries, making robust networking and observability mission-critical.

Multi-Tenant AI Network Challenges

AI workloads push networks to the edge, exposing issues that traditional monitoring misses:

• Congestion & Hotspots: Elephant flows (collectives, shuffles, large reads) on shared links cause spikes and GPU idle time.
• Microbursts: Short bursts overflow buffers, driving tail latency.
• RoCE Misconfigurations: Incorrect ECN/DCQCN or PFC tuning leads to retransmits, jitter, pause storms, and starvation.
• Config Drift (MTU/DSCP/VLAN): Inconsistencies break jumbo RDMA, raising latency or forcing TCP fallback.
• Path Asymmetry & Job Placement: Jobs spanning racks experience reduced performance due to suboptimal workload distribution.

At scale, these inefficiencies waste millions. Networking optimized for AI and deep observability isn't optional—it's the backbone of AI success.

Arista's Transformative Approach

High-Performance AI Networking

Arista Etherlink AI platforms with Arista EOS redefine AI networking by maximizing bandwidth, eliminating bottlenecks, and reducing tail latency for congestion-free, high-performance AI jobs at lower cost. 

360° Observability

Arista CloudVision (CV AI) adds AI-driven, 360° observability, unifying job, network, and system data into a single view. It delivers multi-tenant aware real-time insights, pinpoints bottlenecks, detects hardware issues, and accelerates resolution.

Integrated Security

360° Observability also strengthens security. CV’s Compliance and Vulnerability Tracking provides a single pane to monitor bugs, CVEs, and compliance, with automated updates and clear remediation guidance. Advanced agentic monitoring enables intelligent protection by spotting unusual outbound connections, unexpected ports and services, and anomalous timing patterns in real-time.

Here’s a look at how Arista's CV AI platform is building this comprehensive observability framework

A Comprehensive Observability Framework with CV AI

The Foundation: Ensuring a Balanced Network Traffic

The Traffic Overview Dashboard in CV delivers a real-time, end-to-end view of network utilization across the entire fabric, while also providing granular insights at the device and interface level. By instantly visualizing traffic distribution and load-balancing health, it enables network teams to spot emerging hot spots early and take action before they affect critical jobs.

Beyond Metrics: Correlating Network Health

In a complex network, events and alerts can be overwhelming. A link flap, a routing change, or a port discard can generate a cascade of notifications, making it difficult to pinpoint the root cause of a problem.

“A customer’s large AI deployment had ~15,000 network events / day; the scale of which is impossible for the NetOps team to troubleshoot. CV AI filters out the noise and shows the actionable alerts to quickly help resolve critical issues.” 

The Network Health Dashboard centralizes these alerts and categorizes them by network layer or function. Want to just see all BGP-related events in your data center? You can do that. Want to change the severity of a specific event on your core spines? It's all configurable, giving you complete control over your network’s health signals.

The Game-Changer: Observability at the AI Job Level

The biggest challenge in AI infrastructure is the disconnect between the network and the application layer. Arista CV AI’s AI Jobs Dashboard solves this by providing a unified view that links network and system performance directly to the AI job. By drilling down on “unhealthy” jobs, an administrator can see a timeline of drops, congestion, and related events, instantly understanding not just that a problem exists, but which job was impacted, why, and where on the network the issue originated.

“AI engineers don’t know much about the network. NetOps teams don’t know much about AI applications. This makes troubleshooting hard especially when things don’t work as planned. CloudVision’s AI Jobs based workflows with a 360° observability are a life-saver. ” - Network Admin at an American AI Startup

Seize the Future of AI Networking

CV AI delivers end-to-end visibility, intelligence, and security, from the physical network and systems to job-level performance. Network teams become active partners in AI success, preventing costly inefficiencies and enabling safe, autonomous operations at scale.

By combining high-performance AI networking with integrated observability and security, organizations can unlock AI’s full potential, accelerate innovation, and reduce operational risk.

Don’t let hidden network issues stall your AI journey. Explore Arista Etherlink AI platforms and CloudVision AI to see how observability drives performance, security, and efficiency at scale.

References:

Blog - Powering All Ethernet AI Networking

Blog - Faster, Smarter, Cheaper: The Networking Revolution Powering Generative AI

AI White Paper