Industry standard sFlow telemetry is widely supported by network equipment vendors and network management platforms. However, the advent of real-time sFlow analytics has opened up a range of new applications for sFlow. The map above shows the proportion of sFlow-RT instances running in each of the over 70 countries in which it is deployed.
The following use cases are driving current deployments:
- Augmenting observability dashboards with real-time network analytics, see Flow metrics with Prometheus and Grafana
- Monitoring Internet Exchange Points, see Internet eXchange Provider (IXP) Metrics
- Automated DDoS mitigation, see DDoS protection quickstart guide
Addressing the challenge of operating AI / ML clusters is the emerging application for sFlow visibility. High speed (400/800G) data center switches needed to handle machine learning traffic flows include sFlow agents and real-time analytics are essential to optimize the network so that expensive GPU and compute resources are fully utilized, see Leveraging open technologies to monitor packet drops in AI cluster fabrics.
If you would like to see how real-time network analytics can transform network operations, Getting Started describes how to download and configure sFlow-RT analytics software for use in your network, or how to try it out using an emulator, or pre-captured data.
