Verdict: HolySheep delivers sub-50ms latency with ¥1=$1 flat-rate pricing—85%+ cheaper than official APIs—for production-grade error tracking and intelligent retry logic. If you're building enterprise LLM pipelines that cannot afford blind spots on rate limits or server errors, this is the monitoring stack you need.
HolySheep vs Official APIs vs Competitors: Feature & Pricing Comparison
| Feature | HolySheep AI | Official OpenAI API | Official Anthropic API | Generic Proxy Services |
|---|---|---|---|---|
| Pricing Model | ¥1 = $1 flat rate | Variable USD tiers | Variable USD tiers | Variable + markup |
| Cost Savings | 85%+ vs Chinese market | Baseline | 2-3x OpenAI | 20-40% markup |
| Latency (P99) | <50ms | 200-500ms (CN) | 300-600ms (CN) | 100-300ms |
| Error Monitoring | Real-time dashboard + webhooks | Basic logging only | Basic logging only | None or paid tier |
| Rate Limit Alerts | Automated 429 tracking | No native alerting | No native alerting | Paid feature |
| Auto-Retry Logic | Built-in exponential backoff | DIY implementation | DIY implementation | Basic retry only |
| Payment Methods | WeChat, Alipay, USDT | Credit card only | Credit card only | Limited options |
| Model Coverage | GPT-4.1, Claude Sonnet 4.5, Gemini 2.5 Flash, DeepSeek V3.2 | GPT series only | Claude series only | Varies |
| Free Credits | Yes, on signup | $5 trial (limited) | None | Rarely |
| Best For | China-market teams, cost-sensitive enterprises | US-based teams | US-based teams | Simple use cases |
Who This Is For — And Who Should Look Elsewhere
Perfect Fit For:
- China-based development teams needing reliable LLM access without VPN dependencies or international payment friction
- High-volume API consumers running 10,000+ requests/day who need real-time error rate visibility
- Production systems where 502/503 errors cause business disruption and require automated incident response
- Cost-optimization teams comparing ¥7.3+ per dollar alternatives against HolySheep's ¥1=$1 flat rate
- DevOps engineers building monitoring dashboards with Prometheus/Grafana integration
Not The Best Fit For:
- Projects requiring only occasional API calls (under 100/month) where monitoring overhead outweighs benefits
- Teams already locked into specific vendor contracts without migration flexibility
- Non-production development environments where basic error logging suffices
Why Choose HolySheep for Error Monitoring
I've implemented monitoring stacks across three major LLM providers, and the gap between HolySheep's built-in observability and manual implementations is substantial. While official APIs give you raw response codes and expect you to build everything else, HolySheep provides:
- Unified error taxonomy: 429 (rate limit), 502 (upstream timeout), 503 (service unavailable) with timestamps, request IDs, and context
- Alert channels: Webhook integrations for Slack, PagerDuty, DingTalk, and WeCom out of the box
- Retry state machine: Exponential backoff with jitter, circuit breaker patterns, and dead letter queues
- Cost attribution: Track which endpoints, models, or teams trigger the most retries (and wasted tokens)
Pricing and ROI Analysis
2026 Model Pricing Reference (Output $/M tokens)
| Model | Standard Price | With HolySheep (¥1=$1) | Chinese Market Average |
|---|---|---|---|
| GPT-4.1 | $8.00 | $8.00 (¥56) | ¥120-180 |
| Claude Sonnet 4.5 | $15.00 | $15.00 (¥105) | ¥280-420 |
| Gemini 2.5 Flash | $2.50 | $2.50 (¥17.5) | ¥42-63 |
| DeepSeek V3.2 | $0.42 | $0.42 (¥2.94) | ¥8.4-12.6 |
ROI Calculation for Monitoring Investment
Consider a team processing 500,000 API calls/month with a 3% error rate (15,000 errors). Without monitoring:
- Average 2-hour detection time × 15,000 errors = 30,000 hours of failed requests
- At $0.001 per request in wasted tokens = $15,000/month in direct losses
With HolySheep's real-time alerting and auto-retry:
- Sub-minute error detection via webhook alerts
- Intelligent retry reduces failed requests by 85%+
- Net savings: $12,750/month against $200/month monitoring cost = 6,375% ROI
Technical Implementation: Real-Time Error Tracking & Auto-Retry
Architecture Overview
Our monitoring stack consists of three components:
- Request Layer: HolySheep SDK with built-in retry logic
- Monitoring Layer: Real-time error rate aggregation
- Alerting Layer: Webhook-based incident management
Complete Python Implementation
#!/usr/bin/env python3
"""
HolySheep AI: Real-time Error Monitoring with Auto-Retry
base_url: https://api.holysheep.ai/v1
"""
import asyncio
import httpx
import json
import time
import hashlib
from datetime import datetime, timedelta
from typing import Optional, Dict, Any, List
from dataclasses import dataclass, field
from collections import defaultdict
import logging
Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("holysheep_monitor")
============================================================
CONFIGURATION
============================================================
HOLYSHEEP_CONFIG = {
"base_url": "https://api.holysheep.ai/v1",
"api_key": "YOUR_HOLYSHEEP_API_KEY", # Replace with your key
"timeout": 30.0,
"max_retries": 5,
"retry_base_delay": 1.0,
"retry_max_delay": 60.0,
"jitter_factor": 0.1,
}
Alert thresholds
ALERT_THRESHOLDS = {
"429_rate_percent": 5.0, # Alert if 429 errors exceed 5%
"502_503_rate_percent": 1.0, # Alert if 502/503 exceed 1%
"error_window_seconds": 300, # Rolling 5-minute window
"min_requests_for_alert": 50, # Minimum requests before alerting
}
============================================================
DATA STRUCTURES
============================================================
@dataclass
class RequestMetrics:
"""Metrics for a single API request"""
timestamp: datetime
endpoint: str
model: str
status_code: int
response_time_ms: float
error_type: Optional[str] = None
retry_count: int = 0
tokens_used: Optional[int] = None
@dataclass
class AlertPayload:
"""Webhook alert payload structure"""
alert_type: str
severity: str # "warning", "critical"
metric_name: str
current_value: float
threshold: float
window_seconds: int
affected_endpoints: List[str]
triggered_at: str
recommended_action: str
class ErrorRateTracker:
"""Real-time error rate tracker with rolling window"""
def __init__(self, window_seconds: int = 300):
self.window_seconds = window_seconds
self.requests: List[RequestMetrics] = []
self.error_counts = defaultdict(int)
self.total_counts = defaultdict(int)
self._lock = asyncio.Lock()
async def record_request(self, metrics: RequestMetrics):
"""Record a request and update error rates"""
async with self._lock:
self.requests.append(metrics)
self.total_counts[metrics.endpoint] += 1
if metrics.status_code == 429:
self.error_counts["rate_limit"] += 1
elif metrics.status_code in (502, 503):
self.error_counts["upstream_error"] += 1
elif metrics.status_code >= 400:
self.error_counts["other_error"] += 1
# Clean old entries outside window
cutoff = datetime.utcnow() - timedelta(seconds=self.window_seconds)
self.requests = [r for r in self.requests if r.timestamp > cutoff]
async def get_error_rates(self) -> Dict[str, float]:
"""Calculate current error rates by type"""
async with self._lock:
if not self.requests:
return {
"rate_limit_429_percent": 0.0,
"upstream_502_503_percent": 0.0,
"total_error_percent": 0.0,
"total_requests": 0,
}
total = len(self.requests)
rate_limit_429 = sum(1 for r in self.requests if r.status_code == 429)
upstream_errors = sum(1 for r in self.requests if r.status_code in (502, 503))
all_errors = sum(1 for r in self.requests if r.status_code >= 400)
return {
"rate_limit_429_percent": (rate_limit_429 / total) * 100,
"upstream_502_503_percent": (upstream_errors / total) * 100,
"total_error_percent": (all_errors / total) * 100,
"total_requests": total,
}
============================================================
HOLYSHEEP API CLIENT WITH RETRY LOGIC
============================================================
class HolySheepClient:
"""HolySheep API client with exponential backoff and circuit breaker"""
def __init__(self, config: Dict[str, Any], tracker: ErrorRateTracker):
self.config = config
self.tracker = tracker
self.circuit_open = False
self.circuit_open_time: Optional[float] = None
self.circuit_reset_timeout = 30.0 # Seconds before attempting reset
self.client = httpx.AsyncClient(
base_url=config["base_url"],
headers={
"Authorization": f"Bearer {config['api_key']}",
"Content-Type": "application/json",
},
timeout=config["timeout"],
)
def _calculate_retry_delay(self, attempt: int, base_error: Optional[str] = None) -> float:
"""Calculate exponential backoff delay with jitter"""
# Special handling for 429 errors - respect Retry-After header
if base_error == "rate_limit":
return self.config["retry_base_delay"] * (2 ** min(attempt, 3))
# Standard exponential backoff for other errors
delay = self.config["retry_base_delay"] * (2 ** attempt)
# Cap at max delay
delay = min(delay, self.config["retry_max_delay"])
# Add jitter (±10%)
import random
jitter = delay * self.config["jitter_factor"]
delay += random.uniform(-jitter, jitter)
return delay
def _classify_error(self, status_code: int) -> str:
"""Classify HTTP error for appropriate handling"""
if status_code == 429:
return "rate_limit"
elif status_code == 502:
return "bad_gateway"
elif status_code == 503:
return "service_unavailable"
elif status_code == 504:
return "gateway_timeout"
elif 400 <= status_code < 500:
return "client_error"
elif status_code >= 500:
return "server_error"
return "unknown"
async def _check_circuit_breaker(self) -> bool:
"""Check if circuit breaker should trip or reset"""
if self.circuit_open:
if self.circuit_open_time and \
time.time() - self.circuit_open_time > self.circuit_reset_timeout:
logger.info("Circuit breaker: attempting reset")
self.circuit_open = False
self.circuit_open_time = None
return False # Allow request attempt
return True # Block request
return False
async def _trip_circuit_breaker(self):
"""Trip the circuit breaker on repeated failures"""
self.circuit_open = True
self.circuit_open_time = time.time()
logger.warning("Circuit breaker TRIPPED - blocking requests for 30s")
async def chat_completions(
self,
model: str,
messages: List[Dict[str, str]],
temperature: float = 0.7,
max_tokens: int = 2048,
**kwargs
) -> Dict[str, Any]:
"""
Send chat completion request with automatic retry and monitoring
Args:
model: Model identifier (e.g., "gpt-4.1", "claude-sonnet-4.5")
messages: List of message dicts with "role" and "content"
temperature: Sampling temperature (0-2)
max_tokens: Maximum output tokens
**kwargs: Additional parameters (stream, top_p, etc.)
Returns:
API response as dictionary
Raises:
httpx.HTTPStatusError: After all retries exhausted
"""
# Check circuit breaker
if await self._check_circuit_breaker():
raise Exception("Circuit breaker is open - service degraded")
payload = {
"model": model,
"messages": messages,
"temperature": temperature,
"max_tokens": max_tokens,
**kwargs
}
retry_count = 0
last_error: Optional[str] = None
while retry_count <= self.config["max_retries"]:
start_time = time.time()
try:
response = await self.client.post(
"/chat/completions",
json=payload,
headers={"X-Request-ID": hashlib.md5(str(time.time()).encode()).hexdigest()[:16]}
)
response_time_ms = (time.time() - start_time) * 1000
error_type = self._classify_error(response.status_code)
# Record metrics
await self.tracker.record_request(RequestMetrics(
timestamp=datetime.utcnow(),
endpoint="/chat/completions",
model=model,
status_code=response.status_code,
response_time_ms=response_time_ms,
error_type=error_type if response.status_code >= 400 else None,
))
# Handle different status codes
if response.status_code == 200:
return response.json()
elif response.status_code == 429:
last_error = "rate_limit"
if retry_count < self.config["max_retries"]:
delay = self._calculate_retry_delay(retry_count, "rate_limit")
logger.warning(
f"Rate limited (429). Retry {retry_count + 1}/{self.config['max_retries']} "
f"in {delay:.2f}s"
)
await asyncio.sleep(delay)
retry_count += 1
continue
elif response.status_code in (502, 503, 504):
last_error = f"upstream_{response.status_code}"
retry_count += 1
if retry_count <= self.config["max_retries"]:
delay = self._calculate_retry_delay(retry_count, last_error)
logger.warning(
f"Upstream error ({response.status_code}). "
f"Retry {retry_count}/{self.config['max_retries']} in {delay:.2f}s"
)
# Trip circuit breaker after 3 consecutive failures
if retry_count >= 3:
await self._trip_circuit_breaker()
await asyncio.sleep(delay)
continue
else:
# Client errors (4xx except 429) - don't retry
response.raise_for_status()
except httpx.TimeoutException as e:
last_error = "timeout"
logger.warning(f"Request timeout. Retry {retry_count + 1}/{self.config['max_retries']}")
if retry_count < self.config["max_retries"]:
delay = self._calculate_retry_delay(retry_count)
await asyncio.sleep(delay)
retry_count += 1
continue
raise
# All retries exhausted
raise Exception(
f"Request failed after {self.config['max_retries']} retries. "
f"Last error: {last_error}"
)
============================================================
ALERTING SYSTEM
============================================================
class AlertManager:
"""Manage and dispatch alerts based on monitoring thresholds"""
def __init__(self, webhook_url: str, tracker: ErrorRateTracker):
self.webhook_url = webhook_url
self.tracker = tracker
self.alert_history: List[AlertPayload] = []
self.last_alert_time: Dict[str, datetime] = {}
self.alert_cooldown_seconds = 300 # 5-minute cooldown between same alerts
def _should_suppress_alert(self, alert_type: str) -> bool:
"""Suppress duplicate alerts within cooldown period"""
if alert_type not in self.last_alert_time:
return False
elapsed = (datetime.utcnow() - self.last_alert_time[alert_type]).total_seconds()
return elapsed < self.alert_cooldown_seconds
async def check_and_alert(self, error_rates: Dict[str, float]) -> Optional[AlertPayload]:
"""Check thresholds and dispatch alerts if exceeded"""
alert: Optional[AlertPayload] = None
# Check 429 rate limit threshold
if error_rates["rate_limit_429_percent"] > ALERT_THRESHOLDS["429_rate_percent"]:
if error_rates["total_requests"] >= ALERT_THRESHOLDS["min_requests_for_alert"]:
if not self._should_suppress_alert("rate_limit_429"):
alert = AlertPayload(
alert_type="RATE_LIMIT_THRESHOLD_EXCEEDED",
severity="warning",
metric_name="429_error_rate_percent",
current_value=error_rates["rate_limit_429_percent"],
threshold=ALERT_THRESHOLDS["429_rate_percent"],
window_seconds=ALERT_THRESHOLDS["error_window_seconds"],
affected_endpoints=["/chat/completions", "/completions"],
triggered_at=datetime.utcnow().isoformat(),
recommended_action="Implement request queuing or scale horizontally. "
"Consider upgrading to higher rate limit tier.",
)
# Check 502/503 upstream error threshold
elif error_rates["upstream_502_503_percent"] > ALERT_THRESHOLDS["502_503_rate_percent"]:
if error_rates["total_requests"] >= ALERT_THRESHOLDS["min_requests_for_alert"]:
if not self._should_suppress_alert("upstream_502_503"):
alert = AlertPayload(
alert_type="UPSTREAM_ERROR_THRESHOLD_EXCEEDED",
severity="critical",
metric_name="upstream_error_rate_percent",
current_value=error_rates["upstream_502_503_percent"],
threshold=ALERT_THRESHOLDS["502_503_rate_percent"],
window_seconds=ALERT_THRESHOLDS["error_window_seconds"],
affected_endpoints=["/chat/completions"],
triggered_at=datetime.utcutnow().isoformat(),
recommended_action="HolySheep infrastructure issue detected. "
"Check status.holysheep.ai. Enable circuit breaker fallback.",
)
if alert:
await self._dispatch_alert(alert)
return alert
async def _dispatch_alert(self, alert: AlertPayload):
"""Send alert to webhook endpoint"""
self.last_alert_time[alert.alert_type] = datetime.utcnow()
self.alert_history.append(alert)
async with httpx.AsyncClient() as client:
try:
response = await client.post(
self.webhook_url,
json={
"alert_id": hashlib.md5(
f"{alert.alert_type}_{alert.triggered_at}".encode()
).hexdigest()[:16],
**vars(alert),
},
headers={"Content-Type": "application/json"},
timeout=10.0,
)
response.raise_for_status()
logger.info(f"Alert dispatched: {alert.alert_type}")
except Exception as e:
logger.error(f"Failed to dispatch alert: {e}")
============================================================
MONITORING DAEMON
============================================================
async def monitoring_loop(
client: HolySheepClient,
alert_manager: AlertManager,
check_interval: int = 30
):
"""Background monitoring loop - run alongside your main application"""
while True:
try:
error_rates = await client.tracker.get_error_rates()
logger.info(
f"Monitoring stats - Requests: {error_rates['total_requests']}, "
f"429 Rate: {error_rates['rate_limit_429_percent']:.2f}%, "
f"502/503 Rate: {error_rates['upstream_502_503_percent']:.2f}%"
)
await alert_manager.check_and_alert(error_rates)
except Exception as e:
logger.error(f"Monitoring loop error: {e}")
await asyncio.sleep(check_interval)
============================================================
USAGE EXAMPLE
============================================================
async def main():
"""Example usage with all monitoring features enabled"""
# Initialize components
tracker = ErrorRateTracker(window_seconds=ALERT_THRESHOLDS["error_window_seconds"])
client = HolySheepClient(HOLYSHEEP_CONFIG, tracker)
alert_manager = AlertManager(
webhook_url="https://your-slack-webhook.com/hook/xxx",
tracker=tracker
)
# Start monitoring background task
monitor_task = asyncio.create_task(
monitoring_loop(client, alert_manager, check_interval=30)
)
try:
# Example: Chat completion with all models
test_models = [
("gpt-4.1", [{"role": "user", "content": "Explain monitoring in 50 words"}]),
("claude-sonnet-4.5", [{"role": "user", "content": "What is observability?"}]),
("gemini-2.5-flash", [{"role": "user", "content": "Define alerting"}]),
("deepseek-v3.2", [{"role": "user", "content": "Describe retry logic"}]),
]
for model, messages in test_models:
try:
response = await client.chat_completions(
model=model,
messages=messages,
max_tokens=100
)
print(f"✓ {model}: {response.get('choices', [{}])[0].get('message', {}).get('content', '')[:50]}...")
except Exception as e:
print(f"✗ {model}: {e}")
# Keep monitoring for a while
await asyncio.sleep(60)
finally:
monitor_task.cancel()
await client.client.aclose()
if __name__ == "__main__":
asyncio.run(main())
JavaScript/TypeScript Implementation for Node.js
/**
* HolySheep AI: Node.js Error Monitoring & Auto-Retry Client
* base_url: https://api.holysheep.ai/v1
*/
const https = require('https');
const http = require('http');
// Configuration
const HOLYSHEEP_CONFIG = {
baseUrl: 'https://api.holysheep.ai/v1',
apiKey: process.env.HOLYSHEEP_API_KEY || 'YOUR_HOLYSHEEP_API_KEY',
timeout: 30000,
maxRetries: 5,
retryBaseDelay: 1000,
retryMaxDelay: 60000,
circuitBreakerThreshold: 3,
circuitBreakerResetTimeout: 30000,
};
// Metrics storage
class MetricsCollector {
constructor(windowSeconds = 300) {
this.windowMs = windowSeconds * 1000;
this.requests = [];
this.errorCounts = {
rateLimit: 0,
upstream: 0,
other: 0,
};
this.totalRequests = 0;
}
recordRequest(statusCode, endpoint, responseTimeMs) {
const now = Date.now();
// Add to rolling window
this.requests.push({ statusCode, endpoint, responseTimeMs, timestamp: now });
// Clean old entries
const cutoff = now - this.windowMs;
this.requests = this.requests.filter(r => r.timestamp > cutoff);
// Update counters
this.totalRequests++;
if (statusCode === 429) {
this.errorCounts.rateLimit++;
} else if ([502, 503, 504].includes(statusCode)) {
this.errorCounts.upstream++;
} else if (statusCode >= 400) {
this.errorCounts.other++;
}
}
getErrorRates() {
const total = this.requests.length;
if (total === 0) {
return { rateLimit: 0, upstream: 0, total: 0, count: 0 };
}
const rateLimit = (this.errorCounts.rateLimit / total) * 100;
const upstream = (this.errorCounts.upstream / total) * 100;
const totalError = ((this.errorCounts.rateLimit + this.errorCounts.upstream + this.errorCounts.other) / total) * 100;
return {
rateLimit: rateLimit.toFixed(2),
upstream: upstream.toFixed(2),
total: totalError.toFixed(2),
count: total,
};
}
}
// Circuit breaker implementation
class CircuitBreaker {
constructor(threshold, resetTimeout) {
this.state = 'CLOSED';
this.failureCount = 0;
this.threshold = threshold;
this.resetTimeout = resetTimeout;
this.lastFailureTime = null;
}
recordSuccess() {
this.failureCount = 0;
this.state = 'CLOSED';
}
recordFailure() {
this.failureCount++;
this.lastFailureTime = Date.now();
if (this.failureCount >= this.threshold) {
this.state = 'OPEN';
console.log(⚠️ Circuit breaker OPENED after ${this.failureCount} failures);
}
}
canAttempt() {
if (this.state === 'CLOSED') return true;
if (this.state === 'OPEN') {
const elapsed = Date.now() - this.lastFailureTime;
if (elapsed >= this.resetTimeout) {
this.state = 'HALF_OPEN';
console.log('🔄 Circuit breaker entering HALF_OPEN state');
return true;
}
return false;
}
return this.state === 'HALF_OPEN';
}
}
// HolySheep API Client
class HolySheepClient {
constructor(config, metrics) {
this.config = config;
this.metrics = metrics;
this.circuitBreaker = new CircuitBreaker(
config.circuitBreakerThreshold,
config.circuitBreakerResetTimeout
);
}
calculateRetryDelay(attempt, errorType) {
let delay;
if (errorType === 'rate_limit') {
delay = this.config.retryBaseDelay * Math.pow(2, Math.min(attempt, 3));
} else {
delay = this.config.retryBaseDelay * Math.pow(2, attempt);
}
delay = Math.min(delay, this.config.retryMaxDelay);
// Add jitter (±10%)
const jitter = delay * 0.1;
delay += (Math.random() * 2 - 1) * jitter;
return delay;
}
makeRequest(method, path, body = null) {
return new Promise((resolve, reject) => {
const url = new URL(${this.config.baseUrl}${path});
const options = {
hostname: url.hostname,
port: 443,
path: url.pathname,
method: method,
headers: {
'Authorization': Bearer ${this.config.apiKey},
'Content-Type': 'application/json',
},
timeout: this.config.timeout,
};
const startTime = Date.now();
const req = https.request(options, (res) => {
let data = '';
res.on('data', (chunk) => { data += chunk; });
res.on('end', () => {
const responseTime = Date.now() - startTime;
this.metrics.recordRequest(res.statusCode, path, responseTime);
if (res.statusCode === 200) {
this.circuitBreaker.recordSuccess();
try {
resolve(JSON.parse(data));
} catch {
resolve(data);
}
} else if (res.statusCode === 429) {
this.circuitBreaker.recordFailure();
reject({
statusCode: 429,
error: 'rate_limit',
message: 'Rate limit exceeded',
retryable: true
});
} else if ([502, 503, 504].includes(res.statusCode)) {
this.circuitBreaker.recordFailure();
reject({
statusCode: res.statusCode,
error: 'upstream_error',
message: Upstream error: ${res.statusCode},
retryable: true
});
} else {
reject({
statusCode: res.statusCode,
error: 'api_error',
message: data,
retryable: false
});
}
});
});
req.on('error', (err) => {
this.circuitBreaker.recordFailure();
reject({
statusCode: 0,
error: 'network_error',
message: err.message,
retryable: true
});
});
req.on('timeout', () => {
req.destroy();
this.circuitBreaker.recordFailure();
reject({
statusCode: 0,
error: 'timeout',
message: 'Request timeout',
retryable: true
});
});
if (body) {
req.write(JSON.stringify(body));
}
req.end();
});
}
async chatCompletion(model, messages, options = {}) {
if (!this.circuitBreaker.canAttempt()) {
throw new Error('Circuit breaker is open - too many recent failures');
}
const payload = {
model,
messages,
temperature: options.temperature || 0.7,
max_tokens: options.maxTokens || 2048,
...options,
};
let lastError;
for (let attempt = 0; attempt <= this.config.maxRetries; attempt++) {
try {
const response = await this.makeRequest('POST', '/chat/completions', payload);
return response;
} catch (error) {
lastError = error;
if (!error.retryable || attempt === this.config.maxRetries) {
throw new Error(Request failed: ${error.message});
}
const delay = this.calculateRetryDelay(attempt, error.error);
console.log(⏳ Retry ${attempt + 1}/${this.config.maxRetries} in ${delay.toFixed(0)}ms - ${error.error});
await new Promise(resolve => setTimeout(resolve, delay));
}
}
throw new Error(All retries exhausted. Last error: ${lastError.message});
}
}
// Alert manager
class AlertManager {
constructor(webhookUrl, metrics) {
this.webhookUrl = webhookUrl;
this.metrics = metrics;
this.lastAlert = {};
this.cooldownMs = 300000; // 5 minutes
}
shouldSuppressAlert(type) {
if (!this.lastAlert[type]) return false;
return Date.now() - this.lastAlert[type] < this.cooldownMs;
}
async sendAlert(alert) {
this.lastAlert[alert.type] = Date.now();
try {
await fetch(this.webhookUrl, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
alert_id: ${alert.type}_${Date.now()},
...alert,
sent_at: new Date().toISOString(),
}),
});
console.log(🚨 ALERT SENT: ${alert.type} - ${alert.severity});
} catch (err) {
console.error('Failed to send alert:', err);
}
}
checkThresholds() {
const rates = this.metrics.getErrorRates