ChiaMon

Example using mtail to collect metrics from Chia logs, chia_exporter to collect metrics from the Chia node, with a 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

chia_exporter

The chia_exporter is used to collect metrics from the Chia node RPC API.

Grafana dashboard

The Grafana dashboard is in grafana/dashboards/Chia.json. It defines a number of variables that will be auto-populated from the node metrics; use the dropdowns to customize to show show the drives, mounts, etc that you're interested in monitoring.

Stack

This stack was created for development on Linux. See notes below for other platforms.*

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).

Run:

docker-compose up -d

This will do the following:

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

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).

Notes

• 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.

• It's highly encouraged to run the node exporter natively rather than in docker - see the discussion in the node_exporter docs. If you do run it in Docker, you'll need to bind-mount in any other volumes you want to monitor (add them to the volumes list in docker-compose.yml, e.g. - '/scratch:/scratch).

• To run this on Windows, you'll need to use the Windows exporter instead of the node_exporter, and change the dashboard appropriately. See issue #2.

• On Mac you'll need to run node_exporter natively, not under Docker: brew install node_exporter