In this talk from the recent OCP Global Summit, Aldrin Isaac, eBay, describes the challenge, AI clusters operate most efficiently over lossless networks for optimum job completion times which can be significantly impacted by dropped packets. Although networks can be designed to minimize packet loss by choosing the right network topology, optimizing network devices and protocols, an effective monitoring and troubleshooting network performance tool is still required. Such tool should capture packet drops, raise notifications and identify various drop reasons and pin point where the drops caused congestions. In turn, it allows the governing management application to tune configurations of relevant infrastructure components, including switches, NICs and GPU servers.
The talk shares the results and best practices of a TAM (Telemetry and Monitoring) solution being prepared for deployment at eBay. It leverages OCP’s SAI and open sFlow drop notification technologies as part of eBay’s ongoing initiatives to adopt open networking hardware and community SONiC for its data centers.
The sFlow Dropped Packet Notification Structures extension mentioned in the talk adds real-time packet drop notifications (including dropped packet header and drop reason) as part of an industry standard sFlow telemetry feed, making the data available to open source and commercial sFlow analytics tools.
For example, Dropped packet metrics with Prometheus and Grafana describes how to incorporate sFlow dropped packet notifications into operational dashboards using current implementations by Arista Networks, VyOS, FD.io / VPP, and Linux servers. Current network hardware is capable of reporting on dropped packets, so ask your network equipment vendor about their plains to support the sFlow extension so that you can befit from this transformational capability.
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