63 lines
1.9 KiB
ReStructuredText
63 lines
1.9 KiB
ReStructuredText
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Monitoring
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==========
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ILMO should, like every other software, be easy to monitor. Therefore a basic metrics are exposed to `https://notfellchen.org/metrics`.
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The data is encoded in JSON format and is therefore suitable to bea read by humans and it is easy to use it as data source for further processing.
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Exposed Metrics
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---------------
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.. code::
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users: number of users (all roles combined)
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staff: number of users with staff status
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adoption_notices: number of adoption notices
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adoption_notices_by_status: number of adoption notices by major status
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adoption_notices_without_location: number of location notices that are not geocoded
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Example workflow
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----------------
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To use the exposed metrics you will usually need a time series database and a visualization tool.
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As time series database we will utilize InfluxDB, the visualization tool will be Grafana.
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InfluxDB and Telegraf
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^^^^^^^^^^^^^^^^^^^^^
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First we install InfluxDB (e.g. with docker, be aware of the security risks!).
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.. code::
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# Pull the image
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$ sudo docker pull influxdb
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# Start influxdb
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$ sudo docker run -d -p 8086:8086 -v influxdb:/var/lib/influxdb --name influxdb influxdb
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# Start influxdb console
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$ docker exec -it influxdb influx
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Connected to http://localhost:8086 version 1.8.3
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InfluxDB shell version: 1.8.3
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> create database monitoring
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> create user "telegraf" with password 'mypassword'
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> grant all on monitoring to telegraf
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.. note::
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When creating the user telegraf check the double and single quotes for username an password.
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Now install telegraf and configure `etc/telegraf/telegraf.conf`. Modify the domain and your password for the InfluxDB database.
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.. literalinclude:: example.telegraf.conf
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:linenos:
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:language: python
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Graphana
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^^^^^^^^
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Now we can simply use the InfluxDB as data source in Grafana and configure until you have
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beautiful plots!
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.. image:: monitoring_grafana.png
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