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Grafana is a very powerful visualization platform.
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We can build nice representation of our data with graphs, goals, charts, tables and many more possibilities.
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The first thing that Grafana needs is a connection to a database in Grafana.
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It's called datasource.
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There are already many predefined connections to these sources, and obviously in our situation we're
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going to use the source called Influxdb.
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From there, Grafana proposes a configuration web page where we can fill in all the information of our
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database.
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So let's do it.
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We can provide a name for the data source.
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Let's call it "influxdb", for the query language,
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we're going to use "flux" because it's more powerful.
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But anyway, the queries will be generated, so we won't have to bother much about that.
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Then comes the database location.
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So here we need to provide the URL where influxdb has been installed.
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In my case I can provide my server name Iot-app.univ-lorawan.fr on port 8086.
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Now for all the other information, everything has been filled in in the Docker compose configuration
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file.
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As often I used "admin" for the username and "univ-lorawan" for the password.
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The organization is "training-usmb".
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The token is this one, but you might have change it.
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And the bucket is "iot-platform".
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Once everything is done we can test the database connection.
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So we click on the save and test button and it should return a green message saying that the datasource
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is working.
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Now we want to explore the database to create a graph with the temperature.
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So we go on the explore section and there we can provide a script with the queries for the database.
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So we'll provide a corresponding bucket where the data needs to be extracted, the measurement and the
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field we want to plot.
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But of course the script is a specific language and we are not going to learn this in this course.
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And we actually don't need because if we come back to influxdb, in the Data Explorer section we left
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a few minutes ago, then let's say that we selected a temperature for this device called device1-otaa.
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Or in my case, then we just need to click on script editor and influxdb generates the query.
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This is exactly this query that we need to provide to Grafana.
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So I just copy it and I paste it in Grafana.
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Now, if I auto update this page, then each time a new value is sent from one device, it's stored
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in the database
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thanks to Node-RED and it's displayed here thanks to Grafana.
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So that's our temperature.
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If we're happy with this chart, then we can add it to our dashboard by clicking on "Add to Dashboard."
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I haven't created any dashboard yet, so I will add it in a new one.
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And I can save it.
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I call it lorawan sensors.
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For the RSSI.
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It's exactly the same story.
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In Influxdb I go back in the query builder.
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Select the query I want to create.
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I select the RSSIvalue.
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I can verify if it's what I expected.
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Then I copy the query from the script editor.
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Okay, now I go in Grafana explorer and I past the query.
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Great.
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And if it's fine, then we can add it to the existing dashboard.
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There we go.
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We are done.
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Now you can explore Grafana and see which representations fits you the best.
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We can quickly switch between visualization using the edit button.
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And in the top right corner.
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Change the option.
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For example, you can use a gauge if you want to see only the last value.
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There are hundreds of plugins and different settings that will make your dashboard very nice.