Grant Limberg fbac205e65 add otel library to ext		3 сар өмнө
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BUILD	fbac205e65 add otel library to ext	3 сар өмнө
CMakeLists.txt	fbac205e65 add otel library to ext	3 сар өмнө
README.md	fbac205e65 add otel library to ext	3 сар өмнө
main.cc	fbac205e65 add otel library to ext	3 сар өмнө
prometheus.yml	fbac205e65 add otel library to ext	3 сар өмнө
run.sh	fbac205e65 add otel library to ext	3 сар өмнө

Getting Started with Prometheus and Grafana

Export metrics from the application
- Check results in the browser
Collect metrics using Prometheus
Explore metrics using Grafana
Learn more

Export metrics from the application

Run the application with:

bazel run //examples/prometheus:prometheus_example

OpenTelemetry PrometheusExporter will export data via the endpoint defined by metrics_exporter::PrometheusExporterOptions::url, which is http://localhost:9464/ by default.

graph LR

subgraph SDK
  MeterProvider
  MetricReader["PrometheusExporter<br/>(http://localhost:9464/)"]
end

subgraph API
  Instrument["Meter(#quot;prometheus_metric_example#quot;, #quot;1.0#quot;)<br/>Histogram(#quot;prometheus_metric_example_histogram#quot;)"]
end

Instrument --> | Measurements | MeterProvider

MeterProvider --> | Metrics | MetricReader

Also, for our learning purpose, we use a while-loop to keep recoring random values until the program stops.

while (true)
{
    double val = (rand() % 700) + 1.1;
    std::map<std::string, std::string> labels = get_random_attr();
    auto labelkv = opentelemetry::common::KeyValueIterableView<decltype(labels)>{labels};
    histogram_counter->Record(val, labelkv, context);
    std::this_thread::sleep_for(std::chrono::milliseconds(50));
}

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. It is also possible to use prom/prometheus docker image.

Configuration

After 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.

global:
  scrape_interval: 5s
  scrape_timeout: 2s
  evaluation_interval: 5s
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 prometheus.yml file as the argument or mount as volume:

./prometheus --config.file=prometheus.yml
# OR:
docker run -p 9090:9090 -v $(pwd):/etc/prometheus --network="host" prom/prometheus

View results in Prometheus

To use the graphical interface for viewing our metrics with Prometheus, navigate to http://localhost:9090/graph, and type prometheus_metric_example_histogram_bucket 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 prometheus.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

Install 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/. It is also possible to run grafana/grafana container:

docker run -d -p 3000:3000 --network="host" grafana/grafana

Follow the instructions in the Grafana getting started doc to log in.

After successfully logging in, click on the Configuration icon on the panel at the left hand side, and click on Prometheus. Type in the default endpoint of Prometheus as suggested by the UI as the value for the URI.

http://localhost:9090

Then, click on the Explore icon 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.

graph TD

subgraph Prometheus
  PrometheusScraper
  PrometheusDatabase
end

PrometheusExporter["PrometheusExporter<br/>(listening at #quot;http://localhost:9464/#quot;)"] -->|HTTP GET| PrometheusScraper{{"Prometheus scraper<br/>(polling #quot;http://localhost:9464/metrics#quot; every 5 seconds)"}}
PrometheusScraper --> PrometheusDatabase[("Prometheus TSDB (time series database)")]
PrometheusDatabase -->|http://localhost:9090/graph| PrometheusUI["Browser<br/>(Prometheus Dashboard)"]
PrometheusDatabase -->|http://localhost:9090/api/| Grafana[Grafana Server]
Grafana -->|http://localhost:3000/dashboard| GrafanaUI["Browser<br/>(Grafana Dashboard)"]

README.md