Мониторинг производительности прокси: задержка, процент успеха и алерты

Зачем мониторить производительность прокси

Прокси-инфраструктура отказывает незаметно. Ваш скрапер может работать часами с процентом успеха 40%, прежде чем кто-то заметит. Время ответа растёт, процент блокировок увеличивается, качество данных деградирует — и всё это без очевидных ошибок. Мониторинг превращает эти невидимые проблемы в действенные алерты.

Это руководство показывает, как инструментировать прокси-запросы, собирать значимые метрики, строить дашборды и настраивать алерты, которые поймают деградацию до того, как она повлияет на ваш конвейер данных. Все примеры используют резидентные прокси ProxyHat и готовы к использованию в продакшне.

Если вы не измеряете производительность прокси, вы угадываете. Угадывание в масштабе стоит денег и производит ненадёжные данные.

Ключевые метрики для отслеживания

Python: Инструментированный прокси-клиент

Этот клиент оборачивает каждый запрос замерами времени, отслеживанием статусов и структурированным логированием.

import time
import uuid
import logging
import statistics
from dataclasses import dataclass, field
from collections import defaultdict
from typing import Optional
import requests
logger = logging.getLogger("proxy_monitor")
@dataclass
class ProxyMetrics:
    """Collects and aggregates proxy performance metrics."""
    total_requests: int = 0
    successful: int = 0
    failed: int = 0
    retries: int = 0
    latencies: list = field(default_factory=list)
    status_codes: dict = field(default_factory=lambda: defaultdict(int))
    errors_by_type: dict = field(default_factory=lambda: defaultdict(int))
    bytes_transferred: int = 0
    requests_by_target: dict = field(default_factory=lambda: defaultdict(lambda: {"success": 0, "failed": 0}))
    @property
    def success_rate(self) -> float:
        return (self.successful / self.total_requests * 100) if self.total_requests > 0 else 0.0
    @property
    def p50_latency(self) -> float:
        return statistics.median(self.latencies) if self.latencies else 0.0
    @property
    def p95_latency(self) -> float:
        if not self.latencies:
            return 0.0
        sorted_lat = sorted(self.latencies)
        idx = int(len(sorted_lat) * 0.95)
        return sorted_lat[min(idx, len(sorted_lat) - 1)]
    @property
    def p99_latency(self) -> float:
        if not self.latencies:
            return 0.0
        sorted_lat = sorted(self.latencies)
        idx = int(len(sorted_lat) * 0.99)
        return sorted_lat[min(idx, len(sorted_lat) - 1)]
    def summary(self) -> dict:
        return {
            "total_requests": self.total_requests,
            "success_rate": f"{self.success_rate:.1f}%",
            "p50_latency": f"{self.p50_latency:.3f}s",
            "p95_latency": f"{self.p95_latency:.3f}s",
            "p99_latency": f"{self.p99_latency:.3f}s",
            "retries": self.retries,
            "bytes_transferred": self.bytes_transferred,
            "top_errors": dict(sorted(
                self.errors_by_type.items(),
                key=lambda x: x[1], reverse=True
            )[:5]),
            "status_distribution": dict(self.status_codes),
        }
class MonitoredProxyClient:
    """HTTP client with built-in proxy monitoring."""
    def __init__(self, max_retries: int = 3):
        self.metrics = ProxyMetrics()
        self.max_retries = max_retries
        self._alert_callbacks = []
    def on_alert(self, callback):
        """Register a callback for metric alerts."""
        self._alert_callbacks.append(callback)
    def _check_alerts(self):
        if self.metrics.total_requests < 10:
            return
        alerts = []
        if self.metrics.success_rate < 90:
            alerts.append(f"Low success rate: {self.metrics.success_rate:.1f}%")
        if self.metrics.p95_latency > 10:
            alerts.append(f"High p95 latency: {self.metrics.p95_latency:.1f}s")
        if self.metrics.retries / max(self.metrics.total_requests, 1) > 0.3:
            alerts.append(f"High retry rate: {self.metrics.retries}/{self.metrics.total_requests}")
        for alert in alerts:
            logger.warning(f"ALERT: {alert}")
            for cb in self._alert_callbacks:
                cb(alert)
    def fetch(self, url: str, country: Optional[str] = None) -> Optional[requests.Response]:
        from urllib.parse import urlparse
        target_domain = urlparse(url).netloc
        for attempt in range(self.max_retries + 1):
            session_id = uuid.uuid4().hex[:8]
            username = f"USERNAME-session-{session_id}"
            if country:
                username += f"-country-{country}"
            proxy = f"http://{username}:PASSWORD@gate.proxyhat.com:8080"
            self.metrics.total_requests += 1
            if attempt > 0:
                self.metrics.retries += 1
            start = time.time()
            try:
                response = requests.get(
                    url,
                    proxies={"http": proxy, "https": proxy},
                    timeout=30,
                )
                latency = time.time() - start
                self.metrics.latencies.append(latency)
                self.metrics.status_codes[response.status_code] += 1
                if response.status_code >= 400:
                    self.metrics.errors_by_type[f"HTTP_{response.status_code}"] += 1
                    self.metrics.requests_by_target[target_domain]["failed"] += 1
                    if response.status_code in (403, 429, 503) and attempt < self.max_retries:
                        time.sleep(2 ** attempt)
                        continue
                    self.metrics.failed += 1
                else:
                    self.metrics.successful += 1
                    self.metrics.bytes_transferred += len(response.content)
                    self.metrics.requests_by_target[target_domain]["success"] += 1
                self._check_alerts()
                return response
            except requests.exceptions.Timeout:
                self.metrics.errors_by_type["timeout"] += 1
                self.metrics.latencies.append(time.time() - start)
                self.metrics.requests_by_target[target_domain]["failed"] += 1
            except requests.exceptions.ConnectionError:
                self.metrics.errors_by_type["connection_error"] += 1
                self.metrics.latencies.append(time.time() - start)
                self.metrics.requests_by_target[target_domain]["failed"] += 1
            except Exception as e:
                self.metrics.errors_by_type[type(e).__name__] += 1
                self.metrics.latencies.append(time.time() - start)
            if attempt < self.max_retries:
                time.sleep(2 ** attempt)
        self.metrics.failed += 1
        self._check_alerts()
        return None
# Usage
client = MonitoredProxyClient(max_retries=3)
client.on_alert(lambda msg: print(f"[ALERT] {msg}"))
urls = [f"https://example.com/product/{i}" for i in range(100)]
for url in urls:
    response = client.fetch(url)
print(client.metrics.summary())

Node.js: Инструментированный прокси-клиент

const crypto = require('crypto');
const { HttpsProxyAgent } = require('https-proxy-agent');
const { EventEmitter } = require('events');
class ProxyMetrics {
  constructor() {
    this.totalRequests = 0;
    this.successful = 0;
    this.failed = 0;
    this.retries = 0;
    this.latencies = [];
    this.statusCodes = {};
    this.errorsByType = {};
    this.bytesTransferred = 0;
    this.requestsByTarget = {};
  }
  get successRate() {
    return this.totalRequests > 0
      ? ((this.successful / this.totalRequests) * 100).toFixed(1)
      : '0.0';
  }
  percentile(p) {
    if (this.latencies.length === 0) return 0;
    const sorted = [...this.latencies].sort((a, b) => a - b);
    const idx = Math.min(
      Math.floor(sorted.length * (p / 100)),
      sorted.length - 1
    );
    return sorted[idx];
  }
  summary() {
    return {
      totalRequests: this.totalRequests,
      successRate: `${this.successRate}%`,
      p50Latency: `${this.percentile(50).toFixed(3)}s`,
      p95Latency: `${this.percentile(95).toFixed(3)}s`,
      p99Latency: `${this.percentile(99).toFixed(3)}s`,
      retries: this.retries,
      bytesTransferred: this.bytesTransferred,
      statusDistribution: { ...this.statusCodes },
      topErrors: Object.entries(this.errorsByType)
        .sort(([, a], [, b]) => b - a)
        .slice(0, 5)
        .reduce((obj, [k, v]) => ({ ...obj, [k]: v }), {}),
    };
  }
}
class MonitoredProxyClient extends EventEmitter {
  constructor({ maxRetries = 3 } = {}) {
    super();
    this.metrics = new ProxyMetrics();
    this.maxRetries = maxRetries;
  }
  _checkAlerts() {
    if (this.metrics.totalRequests < 10) return;
    if (parseFloat(this.metrics.successRate) < 90) {
      this.emit('alert', `Low success rate: ${this.metrics.successRate}%`);
    }
    if (this.metrics.percentile(95) > 10) {
      this.emit('alert', `High p95 latency: ${this.metrics.percentile(95).toFixed(1)}s`);
    }
  }
  async fetch(url, { country } = {}) {
    const targetDomain = new URL(url).hostname;
    for (let attempt = 0; attempt <= this.maxRetries; attempt++) {
      const sessionId = crypto.randomBytes(4).toString('hex');
      let username = `USERNAME-session-${sessionId}`;
      if (country) username += `-country-${country}`;
      const agent = new HttpsProxyAgent(
        `http://${username}:PASSWORD@gate.proxyhat.com:8080`
      );
      this.metrics.totalRequests++;
      if (attempt > 0) this.metrics.retries++;
      const startTime = Date.now();
      try {
        const response = await fetch(url, {
          agent,
          signal: AbortSignal.timeout(30000),
        });
        const latency = (Date.now() - startTime) / 1000;
        this.metrics.latencies.push(latency);
        this.metrics.statusCodes[response.status] =
          (this.metrics.statusCodes[response.status] || 0) + 1;
        if (response.status >= 400) {
          this.metrics.errorsByType[`HTTP_${response.status}`] =
            (this.metrics.errorsByType[`HTTP_${response.status}`] || 0) + 1;
          if ([403, 429, 503].includes(response.status) && attempt < this.maxRetries) {
            await new Promise(r => setTimeout(r, 1000 * Math.pow(2, attempt)));
            continue;
          }
          this.metrics.failed++;
        } else {
          this.metrics.successful++;
          const body = await response.text();
          this.metrics.bytesTransferred += body.length;
        }
        this._checkAlerts();
        return response;
      } catch (err) {
        const latency = (Date.now() - startTime) / 1000;
        this.metrics.latencies.push(latency);
        this.metrics.errorsByType[err.name] =
          (this.metrics.errorsByType[err.name] || 0) + 1;
        if (attempt < this.maxRetries) {
          await new Promise(r => setTimeout(r, 1000 * Math.pow(2, attempt)));
          continue;
        }
        this.metrics.failed++;
      }
    }
    this._checkAlerts();
    return null;
  }
}
// Usage
const client = new MonitoredProxyClient({ maxRetries: 3 });
client.on('alert', msg => console.warn(`[ALERT] ${msg}`));
const urls = Array.from({ length: 100 }, (_, i) =>
  `https://example.com/product/${i + 1}`
);
for (const url of urls) {
  await client.fetch(url);
}
console.log(client.metrics.summary());

Go: Инструментированный прокси-клиент

package main
import (
	"crypto/rand"
	"encoding/hex"
	"fmt"
	"io"
	"math"
	"net/http"
	"net/url"
	"sort"
	"sync"
	"time"
)
type Metrics struct {
	mu             sync.Mutex
	TotalRequests  int
	Successful     int
	Failed         int
	Retries        int
	Latencies      []float64
	StatusCodes    map[int]int
	ErrorsByType   map[string]int
	BytesTransferred int64
}
func NewMetrics() *Metrics {
	return &Metrics{
		StatusCodes:  make(map[int]int),
		ErrorsByType: make(map[string]int),
	}
}
func (m *Metrics) RecordSuccess(latency float64, status int, bytes int) {
	m.mu.Lock()
	defer m.mu.Unlock()
	m.TotalRequests++
	m.Successful++
	m.Latencies = append(m.Latencies, latency)
	m.StatusCodes[status]++
	m.BytesTransferred += int64(bytes)
}
func (m *Metrics) RecordFailure(latency float64, errType string) {
	m.mu.Lock()
	defer m.mu.Unlock()
	m.TotalRequests++
	m.Failed++
	m.Latencies = append(m.Latencies, latency)
	m.ErrorsByType[errType]++
}
func (m *Metrics) Percentile(p float64) float64 {
	m.mu.Lock()
	defer m.mu.Unlock()
	if len(m.Latencies) == 0 {
		return 0
	}
	sorted := make([]float64, len(m.Latencies))
	copy(sorted, m.Latencies)
	sort.Float64s(sorted)
	idx := int(math.Min(float64(len(sorted)-1), float64(len(sorted))*p/100))
	return sorted[idx]
}
func (m *Metrics) SuccessRate() float64 {
	m.mu.Lock()
	defer m.mu.Unlock()
	if m.TotalRequests == 0 {
		return 0
	}
	return float64(m.Successful) / float64(m.TotalRequests) * 100
}
func (m *Metrics) Summary() string {
	return fmt.Sprintf(
		"Requests: %d | Success: %.1f%% | p50: %.3fs | p95: %.3fs | p99: %.3fs | Retries: %d",
		m.TotalRequests, m.SuccessRate(),
		m.Percentile(50), m.Percentile(95), m.Percentile(99),
		m.Retries,
	)
}
type MonitoredClient struct {
	metrics    *Metrics
	maxRetries int
}
func NewMonitoredClient(maxRetries int) *MonitoredClient {
	return &MonitoredClient{
		metrics:    NewMetrics(),
		maxRetries: maxRetries,
	}
}
func (c *MonitoredClient) Fetch(target string) (*http.Response, error) {
	for attempt := 0; attempt <= c.maxRetries; attempt++ {
		b := make([]byte, 4)
		rand.Read(b)
		sessionID := hex.EncodeToString(b)
		proxyStr := fmt.Sprintf(
			"http://USERNAME-session-%s:PASSWORD@gate.proxyhat.com:8080",
			sessionID,
		)
		proxyURL, _ := url.Parse(proxyStr)
		client := &http.Client{
			Transport: &http.Transport{Proxy: http.ProxyURL(proxyURL)},
			Timeout:   30 * time.Second,
		}
		if attempt > 0 {
			c.metrics.mu.Lock()
			c.metrics.Retries++
			c.metrics.mu.Unlock()
		}
		start := time.Now()
		resp, err := client.Get(target)
		latency := time.Since(start).Seconds()
		if err != nil {
			c.metrics.RecordFailure(latency, "connection_error")
			if attempt < c.maxRetries {
				time.Sleep(time.Duration(math.Pow(2, float64(attempt))) * time.Second)
				continue
			}
			return nil, err
		}
		body, _ := io.ReadAll(resp.Body)
		resp.Body.Close()
		if resp.StatusCode >= 400 {
			c.metrics.RecordFailure(latency, fmt.Sprintf("HTTP_%d", resp.StatusCode))
			if attempt < c.maxRetries {
				time.Sleep(time.Duration(math.Pow(2, float64(attempt))) * time.Second)
				continue
			}
		} else {
			c.metrics.RecordSuccess(latency, resp.StatusCode, len(body))
		}
		return resp, nil
	}
	return nil, fmt.Errorf("all retries exhausted for %s", target)
}
func main() {
	client := NewMonitoredClient(3)
	for i := 0; i < 50; i++ {
		url := fmt.Sprintf("https://example.com/product/%d", i+1)
		client.Fetch(url)
	}
	fmt.Println(client.metrics.Summary())
}

Структурированное логирование прокси-запросов

JSON-структурированные логи упрощают агрегацию и анализ производительности прокси в распределённых скраперах.

import json
import logging
import time
import uuid
import requests
class JSONProxyLogger:
    """Logs every proxy request as structured JSON."""
    def __init__(self, log_file: str = "proxy_requests.jsonl"):
        self.logger = logging.getLogger("proxy_json")
        handler = logging.FileHandler(log_file)
        handler.setFormatter(logging.Formatter("%(message)s"))
        self.logger.addHandler(handler)
        self.logger.setLevel(logging.INFO)
    def log_request(self, entry: dict):
        self.logger.info(json.dumps(entry))
    def fetch(self, url: str, country: str = None) -> requests.Response:
        session_id = uuid.uuid4().hex[:8]
        username = f"USERNAME-session-{session_id}"
        if country:
            username += f"-country-{country}"
        proxy = f"http://{username}:PASSWORD@gate.proxyhat.com:8080"
        start = time.time()
        try:
            response = requests.get(
                url,
                proxies={"http": proxy, "https": proxy},
                timeout=30,
            )
            latency = time.time() - start
            self.log_request({
                "timestamp": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
                "url": url,
                "status": response.status_code,
                "latency_ms": round(latency * 1000),
                "bytes": len(response.content),
                "session_id": session_id,
                "country": country,
                "success": response.status_code < 400,
            })
            return response
        except Exception as e:
            latency = time.time() - start
            self.log_request({
                "timestamp": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
                "url": url,
                "error": str(e),
                "error_type": type(e).__name__,
                "latency_ms": round(latency * 1000),
                "session_id": session_id,
                "country": country,
                "success": False,
            })
            raise
# Usage — logs produce JSONL like:
# {"timestamp":"2026-02-26T10:30:00Z","url":"https://...","status":200,"latency_ms":1234,...}
proxy_logger = JSONProxyLogger("proxy_requests.jsonl")
response = proxy_logger.fetch("https://example.com/data", country="us")

Периодические отчёты о состоянии

Для долго работающих скраперов генерируйте периодические отчёты о состоянии, суммирующие производительность за фиксированные окна.

import time
import threading
from datetime import datetime
class PeriodicReporter:
    """Generates periodic performance reports from proxy metrics."""
    def __init__(self, metrics: ProxyMetrics, interval_seconds: int = 60):
        self.metrics = metrics
        self.interval = interval_seconds
        self._running = False
        self._thread = None
        self._last_snapshot = None
    def start(self):
        self._running = True
        self._last_snapshot = self._snapshot()
        self._thread = threading.Thread(target=self._report_loop, daemon=True)
        self._thread.start()
    def stop(self):
        self._running = False
    def _snapshot(self) -> dict:
        return {
            "total": self.metrics.total_requests,
            "success": self.metrics.successful,
            "failed": self.metrics.failed,
            "retries": self.metrics.retries,
            "time": time.time(),
        }
    def _report_loop(self):
        while self._running:
            time.sleep(self.interval)
            current = self._snapshot()
            prev = self._last_snapshot
            elapsed = current["time"] - prev["time"]
            requests_delta = current["total"] - prev["total"]
            success_delta = current["success"] - prev["success"]
            failed_delta = current["failed"] - prev["failed"]
            rps = requests_delta / elapsed if elapsed > 0 else 0
            window_success_rate = (
                (success_delta / requests_delta * 100)
                if requests_delta > 0 else 0
            )
            report = {
                "window": f"{self.interval}s",
                "timestamp": datetime.utcnow().isoformat(),
                "requests": requests_delta,
                "rps": round(rps, 1),
                "success_rate": f"{window_success_rate:.1f}%",
                "failed": failed_delta,
                "cumulative_success_rate": f"{self.metrics.success_rate:.1f}%",
                "p95_latency": f"{self.metrics.p95_latency:.3f}s",
            }
            print(f"[REPORT] {report}")
            self._last_snapshot = current
# Usage with MonitoredProxyClient
client = MonitoredProxyClient(max_retries=3)
reporter = PeriodicReporter(client.metrics, interval_seconds=30)
reporter.start()
# Scrape away — reports print every 30 seconds
for url in urls:
    client.fetch(url)
reporter.stop()

Правила алертов и пороги

Настройте интеллектуальные алерты, которые избегают ложных срабатываний во время прогрева и транзиентных всплесков.

Хороший мониторинг — это разница между конвейером скрапинга, который работает надёжно месяцами, и тем, который незаметно производит мусорные данные. Инвестируйте в инструментирование заранее — оно окупится при первом продакшн-инциденте, который вы поймаете рано.

Для создания middleware, который питает эти метрики, смотрите Создание промежуточного слоя прокси. Для оптимизации пропускной способности вместе с мониторингом читайте Масштабирование прокси-запросов с контролем конкурентности. Для полного проектирования системы смотрите Проектирование надёжной архитектуры скрапинга.

Изучите Python SDK, Node SDK и Go SDK для интеграции с прокси, или ознакомьтесь с тарифами ProxyHat и документацией для начала работы.

Часто задаваемые вопросы