5.9 KiB
Getting Started with Prometheus and Grafana
Export metrics from the application
It is highly recommended to go over the getting-started doc before following along this document.
Create a new console application and run it:
dotnet new console --output getting-started-prometheus
cd getting-started-prometheus
dotnet run
Add a reference to Prometheus Exporter:
dotnet add package OpenTelemetry.Exporter.Prometheus --version 1.2.0-rc2
Now, we are going to make some small tweaks to the example in the
getting-started metrics Program.cs to make the metrics available via
OpenTelemetry Prometheus Exporter.
First, copy and paste everything from getting-started metrics example to the Program.cs file of the new console application (getting-started-prometheus) we've created.
And replace the below line:
.AddConsoleExporter()
with
.AddPrometheusExporter(options => { options.StartHttpListener = true; })
With AddPrometheusExporter(), OpenTelemetry PrometheusExporter will export
data via the endpoint defined by
PrometheusExporterOptions.HttpListenerPrefixes,
which is http://localhost:9464/ by default.
Also, for our learning purpose, use a while-loop to keep increasing the counter value until any key is pressed.
Console.WriteLine("Press any key to exit");
while (!Console.KeyAvailable)
{
Thread.Sleep(1000);
MyFruitCounter.Add(1, new("name", "apple"), new("color", "red"));
MyFruitCounter.Add(2, new("name", "lemon"), new("color", "yellow"));
MyFruitCounter.Add(1, new("name", "lemon"), new("color", "yellow"));
...
...
...
}
After the above modifications, now our Program.cs should look like this.
Check results in the browser
Start the application and keep it running. Now we should be able to see the metrics at http://localhost:9464/metrics from a web browser:
Now, we understand how we can configure PrometheusExporter to export metrics.
Next, we are going to learn about how to use Prometheus to collect the metrics.
Collect metrics using Prometheus
Follow the first steps to download the latest release of Prometheus.
Configuration
After finished downloading, extract it to a local location that's easy to
access. We will find the default Prometheus configuration YAML file in the
folder, named prometheus.yml.
Let's create a new file in the same location as where prometheus.yml locates,
and named the new file as otel.yml for this exercise. Then, copy and paste the
entire content below into the otel.yml file we have created just now.
global:
scrape_interval: 10s
evaluation_interval: 10s
scrape_configs:
- job_name: "otel"
static_configs:
- targets: ["localhost:9464"]
Start Prometheus
Follow the instructions from starting-prometheus to start the Prometheus server and verify it has been started successfully.
Please note that we will need pass in otel.yml file as the argument:
./prometheus --config.file=otel.yml
View results in Prometheus
To use the graphical interface for viewing our metrics with Prometheus, navigate
to http://localhost:9090/graph, and type
MyFruitCounter in the expression bar of the UI; finally, click the execute
button.
We should be able to see the following chart from the browser:
From the legend, we can see that the instance name and the job name are the
values we have set in otel.yml.
Congratulations!
Now we know how to configure Prometheus server and deploy OpenTelemetry
PrometheusExporter to export our metrics. Next, we are going to explore a tool
called Grafana, which has powerful visualizations for the metrics.
Explore metrics using Grafana
Start the standalone Grafana server (grafana-server.exe or
./bin/grafana-server, depending on the operating system). Then, use the
browser to navigate to http://localhost:3000/.
Follow the instructions in the Grafana getting started doc to log in.
After successfully logging in, click on the explore option on the left panel of the website - we should be able to write some queries to explore our metrics now!
Feel free to find some handy PromQL here.
In the below example, the query targets to find out what is the per-second rate of increase of myFruitCounter over the past 5 minutes:
