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