Prometheus exporter

Prometheus is an open source time series database optimized to collect large numbers of metrics from cloud infrastructure. This article will explore how industry standard sFlow telemetry streaming supported by network devices (Arista, Aruba, Cisco, Dell, Huawei, Juniper, etc.) and Host sFlow agents (Linux, Windows, FreeBSD, AIX, Solaris, Docker, Systemd, Hyper-V, KVM, Nutanix AHV, Xen) can be integrated with Prometheus to extend visibility into the network.

The diagram above shows the elements of the solution: sFlow telemetry streams from hosts and switches to an instance of sFlow-RT. The sFlow-RT analytics software converts the raw measurements into metrics that are accessible through a REST API. The sflow-rt/prometheus application extends the REST API to include native Prometheus exporter functionality allowing Prometheus to retrieve metrics. Prometheus stores metrics in a time series database that can be queries by Grafana to build dashboards.

The Docker sflow/prometheus image provides a simple way to run the application:

docker run --name sflow-rt -p 8008:8008 -p 6343:6343/udp -d sflow/prometheus

Configure sFlow agents to send data to the collector, 10.0.0.70, on port 6343.

Verify that the metrics are available using cURL:

$ curl http://10.0.0.70:8008/app/prometheus/scripts/export.js/dump/ALL/ALL/txt
ifinucastpkts{agent="10.0.0.30",datasource="2",host="server",ifname="enp3s0"} 9.44
ifoutdiscards{agent="10.0.0.30",datasource="2",host="server",ifname="enp3s0"} 0
ifoutbroadcastpkts{agent="10.0.0.30",datasource="2",host="server",ifname="enp3s0"} 0
ifinerrors{agent="10.0.0.30",datasource="2",host="server",ifname="enp3s0"} 0

If the sFlow agents don't provide host and ifname information, enable SNMP to retrieve sysName and ifName data to populate these fields:

docker run --name sflow-rt -p 8008:8008 -p 6343:6343/udp -d sflow/prometheus \
-Dsnmp.ifname=yes

By default SNMP version 2c will be used with the public community string. Additional System Properties can be used to override these defaults.
Now define a metrics "scraping" job in the Prometheus configuration file, prometheus.yml

global:
  scrape_interval:     15s
  evaluation_interval: 15s

rule_files:
  # - "first.rules"
  # - "second.rules"

scrape_configs:
  - job_name: 'sflow-rt'
    metrics_path: /app/prometheus/scripts/export.js/dump/ALL/ALL/txt
    static_configs:
      - targets: ['10.0.0.70:8008']

Now start Prometheus:

docker run --name prometheus --rm -v $PWD/data:/prometheus \
-v $PWD/prometheus.yml:/etc/prometheus/prometheus.yml \
-p 9090:9090 -d prom/prometheus

The screen capture above shows the Prometheus web interface (accessed on port 9090).
Grafana is open source time series analysis software. The ability to pull data from many data sources and the extensive range of charting options makes Grafana an attractive tool for building operations dashboards.

The following command shows how to run Grafana under Docker:

docker run --name grafana -v $PWD/data:/var/lib/grafana \
-p 3000:3000 -d grafana/grafana

Access the Grafana web interface on port 3000, configure a data source for the Prometheus database, and start building dashboards. The screen capture above shows the same chart built earlier using the native Prometheus interface.