What tools and technologies do you use to collect data for system monitoring and analysis?

For monitoring and analyzing system performance in Go, the following tools and technologies are often used:

• Prometheus — a monitoring system with support for collecting metrics via HTTP. In Go applications, you can use the client library prometheus/client_golang to export metrics.
• Grafana — data visualization, often used together with Prometheus to build dashboards.
• pprof — a built-in profiler in Go that allows collecting data on CPU, memory, locks, and goroutines.
• OpenTelemetry — a standard for collecting traces and metrics, with support for Go.

Example of exporting metrics with Prometheus in Go:

import (
    "github.com/prometheus/client_golang/prometheus"
    "github.com/prometheus/client_golang/prometheus/promhttp"
    "net/http"
)

var opsProcessed = prometheus.NewCounter(prometheus.CounterOpts{
    Name: "myapp_processed_ops_total",
    Help: "The total number of processed events",
})

func init() {
    prometheus.MustRegister(opsProcessed)
}

func main() {
    http.Handle("/metrics", promhttp.Handler())
    go func() {
        for {
            opsProcessed.Inc() // increment the counter
            time.Sleep(time.Second)
        }
    }()
    http.ListenAndServe(":2112", nil)
}

This approach allows collecting and analyzing performance in real-time.