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Tech Bytes: Network Observability AIOps Tips For Success (Sponsored)
Apr 21, 2025
23:39
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Quick takeaways
- Building resilient networks capable of supporting high-performance AI workloads is crucial, emphasizing the need for near-zero latency and minimal packet loss.
- Effective data management and advanced observability tools are essential for accurate root cause analysis, ensuring AI systems receive relevant information without overwhelming the network.
Deep dives
Building Resilient Networks for AI
Preparing network infrastructure for AI workloads requires building resilient networks capable of supporting high performance. AI workloads are expected to demand near-perfect network performance, including near-zero latency and minimal packet loss, as demonstrated by Meta's statistics showing that 57% of AI workload time is spent on their network. Network resilience is essential for managing these demands, and proactive measures should be taken even in the early stages of AI implementation. Key strategies for achieving this include eliminating network noise and effectively correlating events and alarms to simplify troubleshooting and maintenance.
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