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Python prometheus client

Gauge and Python multiprocess mode

If you look at https://github.com/prometheus/client_python#multiprocess-mode-gunicorn, there are various modes for gauge:

Gauges have several modes they can run in, which can be selected with the multiprocess_mode parameter.

'all': Default. Return a timeseries per process alive or dead. 'liveall': Return a timeseries per process that is still alive. 'livesum': Return a single timeseries that is the sum of the values of alive processes. 'max': Return a single timeseries that is the maximum of the values of all processes, alive or dead. 'min': Return a single timeseries that is the minimum of the values of all processes, alive or dead.

If you see your gauge metrics being reported with a PID label, try using one of the other modes (based on https://github.com/prometheus/client_python/blob/master/prometheus_client/multiprocess.py)

StatsD Exporter

Things to keep in mind

The following are things to keep in mind while using the statsd exporter:

  • No persistent storage in statsd exporter, it dies, you don't get metrics
  • When using multiple statsd exporter instances, you may want to use a prometheus histogram rather than summary (This blog post explains why)

If you are using the DogStatsd Python client:

  • Report all timing metrics in milliseconds
  • If you are using the timed() context manager, initialize the statstd client using use_ms

For timing data, statsd exporter converts the data into seconds before exporting. So when you plot in grafana, the units for timing data is always in seconds. (PR updating README for statsd exporter)