How to implement a system for tracking application state and performance?

To implement a system for monitoring the application's state and performance, a combination of monitoring, logging, and alerting is usually used.

1. Monitoring: Use tools like Prometheus, Grafana, Datadog, or New Relic to collect metrics (CPU, memory, response time, request count).

2. Logging: Set up centralized logging with ELK stack (Elasticsearch, Logstash, Kibana) or Fluentd to analyze application logs and identify errors.

3. Alerting: Configure notifications (e.g., via PagerDuty, Slack, or email) based on metrics and logs to respond promptly to issues.

4. Tracing: For complex distributed systems, use distributed tracing (Jaeger, Zipkin) to analyze delays and bottlenecks.

Example of setting up metrics with Prometheus in a Go application:

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

var (
    httpRequests = prometheus.NewCounterVec(
        prometheus.CounterOpts{
            Name: "http_requests_total",
            Help: "Number of HTTP requests",
        },
        []string{"path"},
    )
)

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

func handler(w http.ResponseWriter, r *http.Request) {
    httpRequests.WithLabelValues(r.URL.Path).Inc()
    w.Write([]byte("Hello, world!"))
}

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

Thus, you will be able to collect and visualize application data and respond quickly to deviations.