Go

Host metrics refer to the metrics collected from the operating system of the host where your applications are running. These metrics include CPU, memory, disk, and network usage. Understanding host metrics is crucial as it helps you identify potential problems or bottlenecks that could affect the overall performance of your applications.

In this tutorial, we will show you how to collect host metrics, send them to GreptimeDB and visualize them.

Create Service

To experience the full power of GreptimeCloud, you need to create a service which contains a database with authentication. Open the GreptimeCloud console, signup and login. Then click the New Service button and config the following:

  • Service Name: The name you want to describe your service.
  • Description: More information about your service.
  • Region: Select the region where the database is located.
  • Plan: Select the pricing plan you want to use.

Now create the service and we are ready to write some metrics to it.

Write data

In this section, we will create a quick start demo and showcase the core code to collect host metrics and send them to GreptimeDB. The demo is based on OTLP/HTTP. For reference, you can obtain the entire demo on GitHub.

To begin, create a new directory named quick-start-go to host our project. Then, run the command go mod init quick-start in the directory from your terminal. This will generate a go.mod file, which is used by Go to manage imports.

Next, create new file named app.go and install the required OpenTelemetry packages:

  1. go get go.opentelemetry.io/[email protected] \
  2.     go.opentelemetry.io/contrib/instrumentation/[email protected] \
  3.     go.opentelemetry.io/otel/exporters/otlp/otlpmetric/[email protected]

Once the required packages are installed, write the code to create a metric export object that sends metrics to GreptimeDB in app.go. For the configuration about the exporter, please refer to OTLP integration documentation in GreptimeDB or GreptimeCloud.

  1. auth := base64.StdEncoding.EncodeToString([]byte(fmt.Sprintf("%s:%s", *username, *password)))
  2. exporter, err := otlpmetrichttp.New(
  3.  context.Background(),
  4.  otlpmetrichttp.WithEndpoint(*dbHost),
  5.  otlpmetrichttp.WithURLPath("/v1/otlp/v1/metrics"),
  6.  otlpmetrichttp.WithHeaders(map[string]string{
  7.   "x-greptime-db-name": *db,
  8.   "Authorization":      "Basic " + auth,
  9.  }),
  10.  otlpmetrichttp.WithTimeout(time.Second*5),
  11. )
  13. if err != nil {
  14.  panic(err)
  15. }
  17. reader := metric.NewPeriodicReader(exporter, metric.WithInterval(time.Second*2))

Then attach the exporter to the MeterProvider and start the host metrics collection:

  1. res := resource.NewWithAttributes(
  2.  semconv.SchemaURL,
  3.  semconv.ServiceName("quick-start-go"),
  4. )
  6. meterProvider := metric.NewMeterProvider(
  7.  metric.WithResource(res),
  8.  metric.WithReader(reader),
  9. )
  11. log.Print("Sending metrics...")
  12. err = appHost.Start(appHost.WithMeterProvider(meterProvider))
  13. if err != nil {
  14.  log.Fatal(err)
  15. }

For more details about the code, you can refer to the OpenTelemetry Documentation.

Congratulations on successfully completing the core section of the demo! You can now run the complete demo by following the instructions in the README.md file on the GitHub repository.

The connection information can be found on the service page of GreptimeCloud console.

Visualize Data

Visualizing data in panels and monitoring metrics is important in a developer’s daily work. From the GreptimeCloud console, click on Open Prometheus Workbench, then click on + New Ruleset and Add Group. Name the group host-monitor and add panels.

To add panels for all the tables you’re concerned with, select a table and click on Add Panel one by one. Once you’ve added all the necessary panels, click on the Save button to save them. You can then view the panels in your daily work to monitor the metrics. Additionally, you can set up alert rules for the panels to be notified when the metrics exceed the threshold.