docker / go-metrics

Instrumenting Your Go Application

To monitor a Go application using the github.com/docker/go-metrics library, first ensure that your Go module is correctly set up. You can create a new Go module or use an existing one.

Step 1: Importing the Library

Start by importing the go-metrics package in your Go application:

import (
    "github.com/docker/go-metrics"
)

Step 2: Initializing Metrics

Initialize a metrics registry to start collecting and reporting metrics:

var registry = metrics.NewRegistry()

Step 3: Setting Up Metrics

You can collect different types of metrics, such as counters, gaugers, timers, and histograms. Below is how to set up and increment a counter:

counter := metrics.NewCounter()
registry.Register("my_counter", counter)

func incrementCounter() {
    counter.Inc(1)
}

Step 4: Reporting Metrics

You may want to report your metrics to a variety of back-ends. Here is an example of how to report metrics using a StatsD reporter:

import (
    "github.com/docker/go-metrics/statsd"
)

reporter, err := statsd.New("127.0.0.1:8125", "my_app")
if err != nil {
    log.Fatal(err)
}

go metrics.Log(registry, 1*time.Second, "my_app")

if err := metrics.Register("statsd", reporter); err != nil {
    log.Fatal(err)
}

Step 5: Running in Docker

When running your Go application in Docker, ensure that your application has network access to the StatsD server you have set up. Create a Dockerfile for your application:

FROM golang:1.17-alpine

WORKDIR /app
COPY . .

RUN go build -o my_app .

CMD ["./my_app"]

Step 6: Docker Compose Configuration

If you are using Docker Compose, configure the environment as follows to link the application with the StatsD service:

version: '3'
services:
  my_app:
    build: .
    ports:
      - "8080:8080"
    networks:
      - metrics_network

  statsd:
    image: statsd/statsd
    ports:
      - "8125:8125/udp"
    networks:
      - metrics_network

networks:
  metrics_network:

Step 7: Monitoring the Application

Ensure you have monitoring tools in place that can visualize the collected metrics. Tools like Grafana can be used to visualize StatsD metrics. Simply configure Grafana to pull data from your StatsD endpoint.

Example Code Snippet

Putting it all together, a simplified version of the application with monitoring could look like this:

package main

import (
    "github.com/docker/go-metrics"
    "github.com/docker/go-metrics/statsd"
    "log"
    "time"
)

var registry = metrics.NewRegistry()

func main() {
    counter := metrics.NewCounter()
    registry.Register("requests", counter)

    reporter, err := statsd.New("127.0.0.1:8125", "my_app")
    if err != nil {
        log.Fatal(err)
    }
    
    metrics.Register("statsd", reporter)
    go metrics.Log(registry, 1*time.Second, "my_app")

    for {
        counter.Inc(1)
        time.Sleep(1 * time.Second)
    }
}

Conclusion

Using github.com/docker/go-metrics provides a solid foundation for monitoring your Go applications in production. Ensure that network configurations allow for metrics to be sent to your desired endpoint, and use monitoring tools effectively to visualize this data.

References