MAAS services can provide Prometheus endpoints for collecting performance metrics.
- TFTP server file transfer latency
- HTTP requests latency
- Websocket requests latency
- RPC calls (beween MAAS services) latency
- Per request DB queries counts
All available metrics are prefixed with
maas_, to make it easier to look them
up in Prometheus and Grafana UIs.
Prometheus endpoints are exposed over HTTP by the
processes under the default
/metrics path, whenever the
python3-prometheus-client library is installed.
For a snap-based MAAS installation, the library is already included in the snap, so metrics will be available out of the box.
For a Debian-based MAAS installation, install the library and restart MAAS services as follows:
sudo apt install python3-prometheus-client sudo systemctl restart maas-rackd sudo systemctl restart maas-regiond
MAAS also provides optional stats about resources registered with the MAAS server itself.
- Number of nodes by type, arch, ...
- Number of networks, spaces, fabrics, vlans and subnets
- Total counts for machines CPU cores, memory and storage
- Counters for KVM pods resources
After installing the
python3-prometheus-client library as describe above, run
the following to enable stats:
maas $PROFILE maas set-config name=prometheus_enabled value=true
/metrics endpoint is available in MAAS services, Prometheus can be
confiured to scrape metric values from these. This can be done by adding a
stanza like the following to the prometheus configuration:
- job_name: maas static_configs: - targets: - <maas-host1-IP>:5239 # for regiond - <maas-host1-IP>:5249 # for rackd - <maas-host2-IP>:5239 # regiond-only - <maas-host3-IP>:5249 # rackd-only
If the MAAS installation includes multiple nodes, the
targets entries must be
adjusted accordingly, to match services deployed on each node.
If MAAS stats have also been enabled, an additional Prometheus job must added to the config:
- job_name: maas metrics_path: /MAAS/metrics static_configs: - targets: - <maas-host-IP>:5240
In case of a multi-host deploy, adding a single IP for any of the MAAS hosts
regiond will suffice.
The MAAS performance repo repository provides a sample
deploy-stack script that will deploy and configure the stack on LXD
First, juju must be installed via
sudo snap install --classic juju
Then, the script from the repo can be run as
To follow the progress of the deployment, run
watch -c juju status --color
Once everything is deployed, the the Grafana UI will be accessible on port
3000 with the credentials
grafana. The Prometheus UI will be
accessible on port
The repository also provides some sample dashboard covering the most common use
cases for graphs. These are available under
grafana/dashboards and can be
imported from the Grafana UI or API.