This is a first prototype of a datacentre latency map using RIPE Atlas.
It consists of:
- A script to start measurements: start_measurements.py
- A script to pull measurement data from RIPE Atlas and visualise it: process.py
To start using this, one would need:
- A RIPE Atlas account with enough credits to run measurements, and an api-key for that, stored in ~/.atlas/auth
- A configuration file for the measurements conf.yaml , an example configuration is available in conf.yaml.example.
- After running start_measurements.py, a summary of measurement metadata is written to msm.json in the local directory.
- Once measurements are actually done (allow some 10-15 minutes for that), one can process the measurement data with process.py. process.py needs a local all-probes.geoloc.txt file (example format in all-probes.geoloc.txt.example), with RIPE Atlas probe IDs, with lat,lon,v4ASN,v6ASN and country information. You can run the getallprobes.py command to query the RIPE Atlas probe API to generate a recent file like this. process.py will create a ./map/geodata.js javascript file which has the relevant measurement data in a geojson-compatible format.
- Point a browser at ./map/map.html to see the result.