Monitoring Go (Golang) Applications: Libraries and Tools |…

Monitoring Go (Golang) Applications: Tools and Libraries

Monitoring is an integral part of production operation for any service. For Go (Golang) applications, the ecosystem offers both built-in solutions and powerful external tools. In this article, we will cover the main approaches: from basic profiling to metric collection and tracing.

1. Built-in Tools: The `expvar` Package

The expvar package provides a simple HTTP endpoint for publishing application state variables. It requires no external dependencies and is ideal for quick diagnostics.

Setup and Usage

package main

import (    "expvar"    "net/http")

var requestsCount = expvar.NewInt("total_requests")

func handler(w http.ResponseWriter, r *http.Request) {    requestsCount.Add(1)    w.Write([]byte("OK"))}

func main() {    http.HandleFunc("/api", handler)    // The /debug/vars endpoint will be available automatically    http.ListenAndServe(":8080", nil)}

After starting, navigate to /debug/vars — you will see a JSON with metrics, including request count, GC data, and memory.

2. Prometheus — The De Facto Standard for Metrics

Prometheus is the most popular monitoring system for Go. The prometheus/client_golang library allows you to export metrics in a format understandable by the Prometheus server.

Installation

go get github.com/prometheus/client_golang/prometheusgo get github.com/prometheus/client_golang/prometheus/promhttp

Example: Counter and Histogram

package main

import (    "net/http"    "time"

    "github.com/prometheus/client_golang/prometheus"    "github.com/prometheus/client_golang/prometheus/promhttp")

var (    requestCount = prometheus.NewCounterVec(        prometheus.CounterOpts{            Name: "http_requests_total",            Help: "Total number of HTTP requests",        },        []string{"method", "endpoint"},    )    requestDuration = prometheus.NewHistogramVec(        prometheus.HistogramOpts{            Name:    "http_request_duration_seconds",            Help:    "Histogram of request durations",            Buckets: prometheus.DefBuckets,        },        []string{"method"},    ))

func init() {    prometheus.MustRegister(requestCount, requestDuration)}

func handler(w http.ResponseWriter, r *http.Request) {    start := time.Now()    requestCount.WithLabelValues(r.Method, r.URL.Path).Inc()    w.Write([]byte("Hello"))    requestDuration.WithLabelValues(r.Method).Observe(time.Since(start).Seconds())}

func main() {    http.Handle("/metrics", promhttp.Handler())    http.HandleFunc("/", handler)    http.ListenAndServe(":8080", nil)}

Prometheus will collect metrics from the /metrics endpoint. You can add alerts in Alertmanager based on this data.

3. Profiling with `pprof`

The net/http/pprof package adds endpoints to the application for profiling CPU, memory, goroutines, and blocking. This is an indispensable tool for finding bottlenecks.

Quick Start

package main

import (    "log"    "net/http"    _ "net/http/pprof" // registers handlers)

func main() {    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {        w.Write([]byte("Hello, pprof!"))    })    log.Fatal(http.ListenAndServe(":6060", nil))}

Now the following endpoints are available: