ChiaMon

Example using mtail to collect metrics from Chia logs, with docker-compose stack to collect data with Prometheus and graph in Grafana.

mtail program

The mtail program is in mtail/chialog.mtail. Currently it only collects harvester metrics:

• chia_harvester_blocks_total: cumulative number of block challenges attempted
• chia_harvester_plots_total: current number of plots
• chia_harvester_plots_eligible: cumulative number of plots that passed filter
• chia_harvester_proofs_total: cumulative number of proofs won
• chia_harvester_search_time: histogram of proof search times

Grafana dashboard

The Grafana dashboard is in grafana/dashboards/Chia.json. It assumed the Prometheus datasource is named Prometheus, that the plotting drive is mounted at /chia_tmp and that the farming drives are mounted at /farm* (if your setup is different, change the dashboard, not your setup!).

Stack

The docker-compose file will mount the Chia log from $HOME/.chia/mainnet/log/debug.log, verify that this location is correct and set the log level to INFO in the Chia configuration (usually at $HOME/.chia/mainnet/config/config.yaml):

    log_level: INFO

Run:

docker-compose up -d

This will do the following:

• Build container image with configuration for mtail from source
• Download node_exporter, prometheus, and grafana images from docker hub
• Run containers in the background

The grafana service provisions the prometheus datasource and a basic dashboard that displays harvester and node metrics.

Access Grafana at http://localhost:3000 and login with the default admin/admin username and password (you'll be prompted to change the password).

Note

This is not a production-ready deployment; there's no persistence of Prometheus data or the Grafana database, so changes will be lost when the services are recreated. To do that you'd want to bind-mount local paths to the respective data directories; consult each project's documentation for details.