InfluxDB 2.0 released

InfluxData advances possibilities of time series data with general availability of InfluxDB 2.0 announced the production release of InfluxDB 2.0. This article demonstrates how to import sFlow data into InfluxDB 2.0 using sFlow-RT in order to provide visibility into network traffic.

Real-time network and system metrics as a service describes how to use Docker Desktop to replay previously captured sFlow data. Follow the instructions in the article to start an instance of sFlow-RT.

Create a directory for InfluxDB to use to store data and configuration settings:

mkdir data

Now start InfluxDB using the pre-built influxdb image:

docker run --rm --name=influxdb -p 8086:8086 \
-v  $PWD/data:/var/lib/influxdb2 influxdb:alpine \
--nats-max-payload-bytes=10000000

Note: sFlow-RT is collecting metrics for all the sFlow agents embedded in switches, routers, and servers. The default value of nats-max-payload-bytes (1048576) may be too small to hold all the metrics returned when sFlow-RT is queried. The error,  nats: maximum payload exceeded, in InfluxDB logs indicates that the limit needs to be increased. In this example, the value has been increased to 10000000.

Now access the InfluxDB web interface at http://localhost:8086/

The screen capture above shows three scrapers configured in InfluxDB 2.0:

1. sflow-analyzer
   URL: http://host.docker.internal:8008/prometheus/analyzer/txt
2. sflow-metrics
   URL: http://host.docker.internal:8008/prometheus/metrics/ALL/ALL/txt
3. sflow-flow-src-dst
   URL: http://host.docker.internal:8008/app/prometheus/scripts/export.js/flows/ALL/txt?metric=flow_src_dst_bps&key=ipsource,ipdestination&value=bytes&aggMode=max&maxFlows=100&minValue=1000&scale=8

The first collects metrics about the performance of the sFlow-RT analytics engine, the second, all the metrics exported by the sFlow agents, and the third, is a flow metric.

InfluxDB 2.0 now includes the data exploration and dashboard building capabilities that were previously in the separate Chronograf application. The screen capture above shows a simple chart trending the flow metric.