SMALL BYTES: #5 - Engineering Resilience: Preparing Network Infrastructure for Lossless AI Workloads

AI workloads demand more than just bandwidth — they require deterministic, lossless, and low-jitter network performance across distributed compute environments. From GPU clusters to multi-cloud data pipelines, even minor packet loss or latency variation can disrupt model accuracy and performance. In this 15-minute technical session and live product demo, we’ll explore how to build a resilient network foundation that meets the strict delivery requirements of modern AI. Learn how to: • Monitor and maintain lossless data transfer between GPU nodes • Identify microbursts, buffer pressure, and congestion in real time • Correlate traffic anomalies with application and infrastructure metrics • Validate end-to-end performance across hybrid and edge architectures If you’re architecting for AI at scale, resilient transport isn’t optional — it’s mission-critical. Join us and see how advanced network observability helps you meet the challenge head-on.