Small knowledge, big challenge! This article is participating in the creation activity of “Essential Tips for Programmers”

This article also participated in the “Digitalstar Project” to win a creative gift package and creative incentive money

introduce

Add Prometheus monitoring to the Gin framework microservice with a complete example.

The Gin framework monitors middleware and will be covered in a future article.

We will use RK-boot to start the Gin framework microservice.

Please visit the following address for the full tutorial:

• rkdocs.netlify.app/cn

The installation

go get github.com/rookie-ninja/rk-boot
Copy the code

Quick start

1. Create the boot. Yaml

The boot.yaml file describes the raw information for Gin framework startup. Rk-boot starts Gin by reading boot.yaml.

---
gin:
  - name: greeter
    port: 8080
    enabled: true
    prom:
      enabled: true      # Enable prometheus client
# path: "metrics" # Default value is "metrics", set path as needed.
Copy the code

2. Create a main. Go

package main

import (
	"context"
	"github.com/rookie-ninja/rk-boot"
)

// Application entrance.
func main(a) {
	// Create a new boot instance.
	boot := rkboot.NewBoot()

	// Bootstrap
	boot.Bootstrap(context.Background())

	// Wait for shutdown sig
	boot.WaitForShutdownSig(context.Background())
}
Copy the code

3. Start the main. Go

$ go run main.go
Copy the code

4. Verify

Visit: http://localhost:8080/metrics

Add monitoring to the Prometheus client

We need to understand the following concepts from Prometheus.

1. Add monitoring items in main.go

package main

import (
	"context"
	"github.com/rookie-ninja/rk-boot"
	"github.com/rookie-ninja/rk-prom"
)

// Application entrance.
func main(a) {
	// Create a new boot instance.
	boot := rkboot.NewBoot()

	// Bootstrap
	boot.Bootstrap(context.Background())

	// Create a metrics set into prometheus.Registerer
	set := rkprom.NewMetricsSet("rk"."demo", boot.GetGinEntry("greeter").PromEntry.Registerer)

	// Register counter, gauge, histogram, summary
	set.RegisterCounter("my_counter"."label")
	set.RegisterGauge("my_gauge"."label")
	set.RegisterHistogram("my_histogram"And []float64{}, "label")
	set.RegisterSummary("my_summary", rkprom.SummaryObjectives, "label")

	// Increase counter, gauge, histogram, summary with label value
	set.GetCounterWithValues("my_counter"."value").Inc()
	set.GetGaugeWithValues("my_gauge"."value").Add(1.0)
	set.GetHistogramWithValues("my_histogram"."value").Observe(0.1)
	set.GetSummaryWithValues("my_summary"."value").Observe(0.1)

	// Wait for shutdown sig
	boot.WaitForShutdownSig(context.Background())
}
Copy the code

2. Start the main. Go

$ go run main.go
Copy the code

3. Verify

Visit: http://localhost:8080/metrics

Pushed to the pushgateway

Next, let’s look at how to automatically push monitoring data to the remote PushGateway.

1. Boot. Yaml Starts pusher

---
gin:
  - name: greeter
    port: 8080
    enabled: true
    prom:
      enabled: true                         # Enable prometheus client
      pusher:
        enabled : true                      # Enable backend job push metrics to remote pushgateway
        jobName: "demo"                     # Name of current push job
        remoteAddress: "localhost:9091"     # Remote address of pushgateway
        intervalMs: 2000                    # Push interval in milliseconds
# basicAuth: "user:pass" # Basic auth of pushgateway
# cert:
# ref: "ref" # Cert reference defined in CertEntry. Please see advanced user guide for details.
Copy the code

2. Start pushGateway on the local PC

We use Docker to launch pushGateway

$ docker run prom/pushgateway -p 9091:9091
Copy the code

3. Start the main. Go

$ go run main.go
Copy the code

4. Verify

Visit: http://localhost:9091/metrics

Complete options