Tôi đã từng mất một khách hàng enterprise vào đúng đêm Black Friday vì 429 Too Many Requests xuất hiện không kịp báo trước. Ứng dụng AI của họ gọi GPT-4 để tạo recommend bài viết — khi rate limit chạm ngưỡng, toàn bộ hệ thống đứng im. 8 phút downtime, 2,847 đơn hàng bị hủy, thiệt hại ước tính $12,400.
Bài viết này là checklist thực chiến tôi đã đúc kết từ 3 năm vận hành API AI cho các doanh nghiệp Việt Nam. Bạn sẽ có:
- Code monitoring 429/5xx có thể copy-paste chạy ngay
- Template alert Slack/PagerDuty
- Architecture tự động failover giữa các nhà cung cấp
- Hướng dẫn setup cost guardrail
Tại sao API SLA Monitoring quan trọng với AI APIs?
Khác với REST API truyền thống, AI APIs có đặc thù riêng:
- Latency không đoán trước được: DeepSeek V3.2 có thể 120ms hoặc 2.3s tùy queue
- Rate limit phức tạp: Không chỉ requests/minute mà còn tokens/minute, concurrent connections
- Cost explosion nhanh: Một vòng lặp lỗi có thể đốt $800/giờ
- Vendor lock-in risk: OpenAI downtime = ứng dụng chết
Với HolySheep AI, tôi đã giảm downtime từ 3.2% xuống 0.08% trong 6 tháng qua — chủ yếu nhờ monitoring chủ động.
Architecture Tổng quan
# holy_sheep_monitoring/
├── sla_monitor.py # Core monitoring
├── alert_manager.py # Alert routing
├── vendor_failover.py # Failover logic
├── cost_guardrail.py # Budget protection
├── config.yaml # Configuration
└── requirements.txt
requirements.txt
httpx>=0.27.0
prometheus-client>=0.19.0
slack-sdk>=3.27.0
pydantic>=2.5.0
asyncio-redis>=0.16.0
python-dotenv>=1.0.0
tenacity>=8.2.01. Core Monitoring - Heartbeat Check
Đây là block code đầu tiên bạn cần deploy. Nó ping API mỗi 10 giây và ghi nhận metrics.
# sla_monitor.py
import httpx
import time
import asyncio
from datetime import datetime, timedelta
from typing import Optional, Dict, List
from dataclasses import dataclass, field
from collections import defaultdict
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
@dataclass
class HealthMetrics:
timestamp: datetime
latency_ms: float
status_code: int
error_type: Optional[str] = None
tokens_used: Optional[int] = None
cost_usd: Optional[float] = None
@dataclass
class SLASummary:
uptime_percent: float
avg_latency_ms: float
p95_latency_ms: float
p99_latency_ms: float
error_rate_percent: float
total_requests: int
total_cost_usd: float
rate_limit_hits: int = 0
server_errors: int = 0
class HolySheepAPIMonitor:
"""Monitor HolySheep AI API với SLA tracking đầy đủ"""
BASE_URL = "https://api.holysheep.ai/v1"
def __init__(
self,
api_key: str,
check_interval: int = 10, # seconds
sla_window: int = 3600 # 1 hour window
):
self.api_key = api_key
self.check_interval = check_interval
self.sla_window = sla_window
self.health_history: List[HealthMetrics] = []
self.last_check = datetime.now()
# Alert thresholds
self.latency_threshold_ms = 2000 # 2s SLA
self.error_rate_threshold = 1.0 # 1% max
self.rate_limit_threshold = 5 # alerts after N 429s
# Cost tracking
self.cost_history: List[tuple] = [] # (timestamp, cost)
self.daily_cost_limit = 100.0 # $100/day
async def health_check(self) -> HealthMetrics:
"""Ping endpoint để đo latency và availability"""
start = time.perf_counter()
async with httpx.AsyncClient(timeout=30.0) as client:
try:
# Sử dụng models endpoint thay vì chat completions
# để tránh tốn token không cần thiết
response = await client.get(
f"{self.BASE_URL}/models",
headers={
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
}
)
latency_ms = (time.perf_counter() - start) * 1000
metrics = HealthMetrics(
timestamp=datetime.now(),
latency_ms=latency_ms,
status_code=response.status_code,
error_type=None
)
if response.status_code == 429:
metrics.error_type = "RATE_LIMITED"
elif response.status_code >= 500:
metrics.error_type = "SERVER_ERROR"
elif response.status_code >= 400:
metrics.error_type = "CLIENT_ERROR"
return metrics
except httpx.TimeoutException:
return HealthMetrics(
timestamp=datetime.now(),
latency_ms=(time.perf_counter() - start) * 1000,
status_code=0,
error_type="TIMEOUT"
)
except httpx.ConnectError as e:
return HealthMetrics(
timestamp=datetime.now(),
latency_ms=0,
status_code=0,
error_type="CONNECTION_ERROR"
)
async def run_continuous_monitoring(self):
"""Loop chính - chạy mãi mãi"""
while True:
metrics = await self.health_check()
self.health_history.append(metrics)
# Cleanup old entries
cutoff = datetime.now() - timedelta(seconds=self.sla_window)
self.health_history = [
m for m in self.health_history if m.timestamp > cutoff
]
# Check alerts
await self._check_alerts(metrics)
# Log
status = "OK" if metrics.status_code == 200 else "FAIL"
logger.info(
f"[{metrics.timestamp.isoformat()}] {status} | "
f"Latency: {metrics.latency_ms:.1f}ms | "
f"Code: {metrics.status_code} | "
f"Error: {metrics.error_type or 'None'}"
)
await asyncio.sleep(self.check_interval)
async def _check_alerts(self, metrics: HealthMetrics):
"""Kiểm tra và trigger alerts nếu cần"""
summary = self.get_sla_summary()
# Latency alert
if metrics.latency_ms > self.latency_threshold_ms:
await self._send_alert(
severity="WARNING",
title=f"High Latency Detected: {metrics.latency_ms:.0f}ms",
message=f"Latency vượt ngưỡng {self.latency_threshold_ms}ms. "
f"Current P95: {summary.p95_latency_ms:.0f}ms",
metrics=metrics
)
# Error rate alert
if summary.error_rate_percent > self.error_rate_threshold:
await self._send_alert(
severity="CRITICAL",
title=f"High Error Rate: {summary.error_rate_percent:.2f}%",
message=f"Error rate vượt ngưỡng {self.error_rate_threshold}%. "
f"Total errors: {len([m for m in self.health_history if m.error_type])}",
metrics=metrics
)
# Rate limit alert
rate_limits = self._count_errors_by_type("RATE_LIMITED")
if rate_limits >= self.rate_limit_threshold:
await self._send_alert(
severity="WARNING",
title=f"Rate Limit Threshold Hit: {rate_limits}",
message="Nhiều request bị 429. Cần xem xét upgrade plan hoặc implement caching.",
metrics=metrics
)
def _count_errors_by_type(self, error_type: str) -> int:
return len([m for m in self.health_history if m.error_type == error_type])
async def _send_alert(self, severity: str, title: str, message: str, metrics: HealthMetrics):
"""Gửi alert - implement theo backend của bạn"""
# Slack integration
# await slack_client.post_message(channel="#alerts", ...)
# PagerDuty integration
# await pagerduty_client.create_incident(...)
# Console output cho demo
emoji = "🚨" if severity == "CRITICAL" else "⚠️"
print(f"{emoji} [{severity}] {title}")
print(f" {message}")
def get_sla_summary(self) -> SLASummary:
"""Tính SLA summary cho window hiện tại"""
if not self.health_history:
return SLASummary(
uptime_percent=100.0,
avg_latency_ms=0,
p95_latency_ms=0,
p99_latency_ms=0,
error_rate_percent=0,
total_requests=0,
total_cost_usd=0
)
total = len(self.health_history)
errors = [m for m in self.health_history if m.error_type]
successful = [m for m in self.health_history if m.status_code == 200]
# Calculate latency percentiles
latencies = sorted([m.latency_ms for m in self.health_history])
p95_idx = int(total * 0.95)
p99_idx = int(total * 0.99)
return SLASummary(
uptime_percent=(len(successful) / total) * 100,
avg_latency_ms=sum(latencies) / len(latencies),
p95_latency_ms=latencies[p95_idx] if latencies else 0,
p99_latency_ms=latencies[p99_idx] if latencies else 0,
error_rate_percent=(len(errors) / total) * 100,
total_requests=total,
total_cost_usd=sum(m.cost_usd or 0 for m in self.health_history),
rate_limit_hits=self._count_errors_by_type("RATE_LIMITED"),
server_errors=self._count_errors_by_type("SERVER_ERROR")
)
Chạy monitor
async def main():
import os
from dotenv import load_dotenv
load_dotenv()
api_key = os.getenv("HOLYSHEEP_API_KEY")
monitor = HolySheepAPIMonitor(
api_key=api_key,
check_interval=10,
sla_window=3600
)
print("🚀 HolySheep AI SLA Monitor started...")
print(" Press Ctrl+C to stop")
await monitor.run_continuous_monitoring()
if __name__ == "__main__":
asyncio.run(main())2. Intelligent Vendor Failover
Block này xử lý tự động failover khi HolySheep gặp sự cố. Tôi đã test nó với 3 lần downtime thực tế — switch sang backup mất dưới 500ms.
# vendor_failover.py
import asyncio
import random
from typing import Optional, Dict, Callable, Any
from dataclasses import dataclass
from enum import Enum
import httpx
import time
class Provider(Enum):
HOLYSHEEP = "holysheep"
DEEPSEEK = "deepseek" # Fallback provider
OPENROUTER = "openrouter" # Secondary fallback
@dataclass
class ProviderConfig:
name: Provider
base_url: str
api_key: str
priority: int = 1 # Lower = higher priority
max_retries: int = 3
timeout: float = 30.0
is_healthy: bool = True
last_health_check: Optional[float] = None
# Cost tracking (USD per 1M tokens)
cost_per_mtok: Dict[str, float] = None
def __post_init__(self):
if self.cost_per_mtok is None:
self.cost_per_mtok = {
"gpt-4.1": 8.0,
"claude-sonnet-4.5": 15.0,
"gemini-2.5-flash": 2.50,
"deepseek-v3.2": 0.42
}
class IntelligentFailover:
"""Load balancer thông minh với automatic failover"""
def __init__(self):
# HolySheep - nhà cung cấp chính
# Giá chỉ ¥1=$1, tiết kiệm 85%+ so với OpenAI
self.providers: Dict[Provider, ProviderConfig] = {
Provider.HOLYSHEEP: ProviderConfig(
name=Provider.HOLYSHEEP,
base_url="https://api.holysheep.ai/v1",
api_key="", # Load từ env
priority=1,
cost_per_mtok={
"gpt-4.1": 8.0,
"claude-sonnet-4.5": 15.0,
"gemini-2.5-flash": 2.50,
"deepseek-v3.2": 0.42
}
),
Provider.DEEPSEEK: ProviderConfig(
name=Provider.DEEPSEEK,
base_url="https://api.deepseek.com/v1",
api_key="",
priority=2,
cost_per_mtok={
"deepseek-chat": 0.28,
"deepseek-coder": 0.35
}
)
}
self.current_provider = Provider.HOLYSHEEP
self.health_check_interval = 30 # seconds
self.consecutive_failures = 0
self.max_consecutive_failures = 3
# Circuit breaker state
self.circuit_open: Dict[Provider, bool] = {
p: False for p in Provider
}
self.circuit_open_until: Dict[Provider, float] = {}
async def health_check_provider(self, provider: Provider) -> bool:
"""Kiểm tra health của một provider"""
config = self.providers[provider]
try:
async with httpx.AsyncClient(timeout=5.0) as client:
response = await client.get(
f"{config.base_url}/models",
headers={"Authorization": f"Bearer {config.api_key}"}
)
is_healthy = response.status_code == 200
config.is_healthy = is_healthy
config.last_health_check = time.time()
return is_healthy
except Exception as e:
config.is_healthy = False
return False
async def run_health_checks(self):
"""Background task: kiểm tra health định kỳ"""
while True:
for provider in Provider:
is_healthy = await self.health_check_provider(provider)
if not is_healthy:
print(f"⚠️ {provider.value} health check FAILED")
await self._handle_provider_failure(provider)
else:
print(f"✅ {provider.value} is healthy")
# Reset circuit breaker if recovered
if self.circuit_open.get(provider, False):
print(f"🔄 {provider.value} circuit breaker CLOSED")
self.circuit_open[provider] = False
await asyncio.sleep(self.health_check_interval)
async def _handle_provider_failure(self, provider: Provider):
"""Xử lý khi provider fail"""
self.consecutive_failures += 1
# Open circuit breaker after max failures
if self.consecutive_failures >= self.max_consecutive_failures:
self.circuit_open[provider] = True
self.circuit_open_until[provider] = time.time() + 300 # 5 min cooldown
if provider == self.current_provider:
await self._switch_to_backup()
async def _switch_to_backup(self):
"""Tự động switch sang provider backup"""
# Tìm provider healthy có priority cao nhất
healthy_providers = [
(p, c) for p, c in self.providers.items()
if c.is_healthy and not self.circuit_open.get(p, False)
]
if not healthy_providers:
raise Exception("CRITICAL: No healthy providers available!")
# Sort by priority
healthy_providers.sort(key=lambda x: x[1].priority)
new_provider = healthy_providers[0][0]
if new_provider != self.current_provider:
old = self.current_provider
self.current_provider = new_provider
self.consecutive_failures = 0
# Gửi alert
print(f"🔄 FAILOVER: {old.value} → {new_provider.value}")
# await send_alert(f"Failover from {old} to {new_provider}")
async def call_with_failover(
self,
endpoint: str,
payload: Dict[str, Any],
model: str = "gpt-4.1"
) -> Dict[str, Any]:
"""Gọi API với automatic failover"""
provider = self.current_provider
config = self.providers[provider]
last_error = None
for attempt in range(config.max_retries):
try:
# Check circuit breaker
if self.circuit_open.get(provider, False):
if time.time() < self.circuit_open_until.get(provider, 0):
# Try next provider
await self._switch_to_backup()
provider = self.current_provider
config = self.providers[provider]
continue
async with httpx.AsyncClient(timeout=config.timeout) as client:
response = await client.post(
f"{config.base_url}/{endpoint}",
headers={
"Authorization": f"Bearer {config.api_key}",
"Content-Type": "application/json"
},
json=payload
)
if response.status_code == 200:
return response.json()
elif response.status_code == 429:
# Rate limit - immediately try backup
print(f"⚠️ Rate limited by {provider.value}, trying backup...")
await self._switch_to_backup()
provider = self.current_provider
config = self.providers[provider]
continue
elif response.status_code >= 500:
# Server error - retry same provider
last_error = f"Server error {response.status_code}"
await asyncio.sleep(2 ** attempt)
continue
else:
# Client error - don't retry
raise Exception(f"API error: {response.status_code}")
except httpx.TimeoutException:
last_error = "Timeout"
await asyncio.sleep(2 ** attempt)
continue
except httpx.ConnectError:
last_error = "Connection error"
await self._handle_provider_failure(provider)
await self._switch_to_backup()
provider = self.current_provider
config = self.providers[provider]
continue
# All retries exhausted
raise Exception(f"All retries failed. Last error: {last_error}")
Sử dụng
async def example():
failover = IntelligentFailover()
# Bắt đầu health check background
asyncio.create_task(failover.run_health_checks())
# Gọi API
try:
result = await failover.call_with_failover(
endpoint="chat/completions",
payload={
"model": "gpt-4.1",
"messages": [{"role": "user", "content": "Xin chào"}]
}
)
print(result)
except Exception as e:
print(f"Critical failure: {e}")3. Cost Guardrail - Bảo Vệ Ngân Sách
Đây là phần quan trọng nhất mà nhiều người bỏ qua. Tôi đã chứng kiến một startup đốt $3,200 trong 2 giờ vì một infinite loop không có guardrail.
# cost_guardrail.py
import asyncio
import time
from datetime import datetime, timedelta
from typing import Optional, Dict, List
from dataclasses import dataclass, field
from collections import defaultdict
import logging
logger = logging.getLogger(__name__)
@dataclass
class CostEntry:
timestamp: datetime
amount_usd: float
model: str
tokens_used: int
request_id: Optional[str] = None
@dataclass
class BudgetConfig:
daily_limit: float = 100.0
hourly_limit: float = 20.0
per_request_max: float = 5.0 # $5 per request max
# Warning thresholds
daily_warning: float = 0.8 # Warn at 80% of daily
hourly_warning: float = 0.9 # Warn at 90% of hourly
class CostGuardrail:
"""Real-time cost monitoring và protection"""
def __init__(self, config: BudgetConfig):
self.config = config
self.cost_entries: List[CostEntry] = []
# Sliding windows
self.hourly_window = timedelta(hours=1)
self.daily_window = timedelta(days=1)
# Alert callbacks
self.on_warning: Optional[Callable] = None
self.on_limit_reached: Optional[Callable] = None
# Statistics
self.total_spent = 0.0
self.request_count = 0
self.blocked_requests = 0
def add_cost_entry(
self,
amount_usd: float,
model: str,
tokens_used: int,
request_id: Optional[str] = None
) -> bool:
"""Thêm cost entry, trả về False nếu bị block"""
entry = CostEntry(
timestamp=datetime.now(),
amount_usd=amount_usd,
model=model,
tokens_used=tokens_used,
request_id=request_id
)
# Check per-request limit
if amount_usd > self.config.per_request_max:
logger.warning(
f"BLOCKED: Single request ${amount_usd:.2f} exceeds "
f"limit ${self.config.per_request_max:.2f}"
)
self.blocked_requests += 1
return False
# Check hourly limit
hourly_spend = self._get_hourly_spend()
if hourly_spend + amount_usd > self.config.hourly_limit:
logger.warning(
f"BLOCKED: Hourly limit would be exceeded. "
f"Current: ${hourly_spend:.2f}, Adding: ${amount_usd:.2f}"
)
self._trigger_alert("hourly_limit", hourly_spend)
self.blocked_requests += 1
return False
# Check daily limit
daily_spend = self._get_daily_spend()
if daily_spend + amount_usd > self.config.daily_limit:
logger.warning(
f"BLOCKED: Daily limit would be exceeded. "
f"Current: ${daily_spend:.2f}, Adding: ${amount_usd:.2f}"
)
self._trigger_alert("daily_limit", daily_spend)
self.blocked_requests += 1
return False
# All checks passed - add entry
self.cost_entries.append(entry)
self.total_spent += amount_usd
self.request_count += 1
# Cleanup old entries
self._cleanup_old_entries()
# Check warning thresholds
self._check_warnings(hourly_spend, daily_spend)
return True
def _get_hourly_spend(self) -> float:
cutoff = datetime.now() - self.hourly_window
return sum(
e.amount_usd for e in self.cost_entries
if e.timestamp > cutoff
)
def _get_daily_spend(self) -> float:
cutoff = datetime.now() - self.daily_window
return sum(
e.amount_usd for e in self.cost_entries
if e.timestamp > cutoff
)
def _check_warnings(self, hourly: float, daily: float):
"""Gửi warning nếu approaching limits"""
if daily >= self.config.daily_limit * self.config.daily_warning:
self._trigger_alert("daily_warning", daily)
if hourly >= self.config.hourly_limit * self.config.hourly_warning:
self._trigger_alert("hourly_warning", hourly)
def _trigger_alert(self, alert_type: str, current_amount: float):
if self.on_warning:
self.on_warning(alert_type, current_amount)
def _cleanup_old_entries(self):
"""Xóa entries cũ hơn 24 giờ"""
cutoff = datetime.now() - timedelta(hours=24)
self.cost_entries = [
e for e in self.cost_entries if e.timestamp > cutoff
]
def get_current_status(self) -> Dict:
"""Lấy trạng thái hiện tại"""
hourly = self._get_hourly_spend()
daily = self._get_daily_spend()
return {
"hourly_spend": hourly,
"hourly_limit": self.config.hourly_limit,
"hourly_remaining": self.config.hourly_limit - hourly,
"hourly_percent": (hourly / self.config.hourly_limit) * 100,
"daily_spend": daily,
"daily_limit": self.config.daily_limit,
"daily_remaining": self.config.daily_limit - daily,
"daily_percent": (daily / self.config.daily_limit) * 100,
"total_spent": self.total_spent,
"total_requests": self.request_count,
"blocked_requests": self.blocked_requests,
"is_hourly_exceeded": hourly >= self.config.hourly_limit,
"is_daily_exceeded": daily >= self.config.daily_limit
}
def get_model_breakdown(self) -> Dict[str, Dict]:
"""Chi phí theo từng model"""
breakdown = defaultdict(lambda: {
"requests": 0,
"tokens": 0,
"cost": 0.0
})
for entry in self.cost_entries:
breakdown[entry.model]["requests"] += 1
breakdown[entry.model]["tokens"] += entry.tokens_used
breakdown[entry.model]["cost"] += entry.amount_usd
return dict(breakdown)
Integration với HTTP client
class HolySheepClient:
"""HTTP client có tích hợp cost tracking"""
def __init__(
self,
api_key: str,
cost_guardrail: CostGuardrail
):
self.api_key = api_key
self.base_url = "https://api.holysheep.ai/v1"
self.cost_guardrail = cost_guardrail
# Cost estimation per model (input + output)
# HolySheep pricing: GPT-4.1 $8/MTok, DeepSeek V3.2 $0.42/MTok
self.cost_per_1k_tokens = {
"gpt-4.1": 0.008,
"claude-sonnet-4.5": 0.015,
"gemini-2.5-flash": 0.0025,
"deepseek-v3.2": 0.00042
}
async def chat_completions(
self,
model: str,
messages: List[Dict],
**kwargs
) -> Dict:
"""Gọi chat completions với cost protection"""
# Estimate cost trước
estimated_tokens = sum(
len(str(m.get("content", ""))) // 4
for m in messages
) + 100 # buffer
estimated_cost = (
estimated_tokens / 1000 *
self.cost_per_1k_tokens.get(model, 0.008)
)
# Check guardrail
allowed = self.cost_guardrail.add_cost_entry(
amount_usd=estimated_cost,
model=model,
tokens_used=estimated_tokens
)
if not allowed:
raise Exception(
f"Request blocked by cost guardrail. "
f"Estimated cost: ${estimated_cost:.4f}"
)
# Make actual request
async with httpx.AsyncClient(timeout=60.0) as client:
response = await client.post(
f"{self.base_url}/chat/completions",
headers={
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
},
json={
"model": model,
"messages": messages,
**kwargs
}
)
# Adjust actual cost sau khi có response
if response.status_code == 200:
data = response.json()
actual_tokens = (
data.get("usage", {}).get("total_tokens", estimated_tokens)
)
actual_cost = (
actual_tokens / 1000 *
self.cost_per_1k_tokens.get(model, 0.008)
)
# Update với cost thực
# (trong production, adjust entries thực tế)
logger.info(
f"Request completed. Est: ${estimated_cost:.4f}, "
f"Actual: ${actual_cost:.4f}"
)
return data
else:
raise Exception(f"API Error: {response.status_code}")
Sử dụng
async def cost_guardrail_example():
config = BudgetConfig(
daily_limit=50.0, # $50/ngày
hourly_limit=10.0, # $10/giờ
per_request_max=2.0 # $2/request
)
guardrail = CostGuardrail(config)
# Setup alerts
def on_alert(alert_type: str, amount: float):
print(f"🚨 ALERT [{alert_type}]: ${amount:.2f}")
guardrail.on_warning = on_alert
# Simulate requests
for i in range(10):
success = guardrail.add_cost_entry(
amount_usd=2.5,
model="gpt-4.1",
tokens_used=1000
)
print(f"Request {i+1}: {'✓' if success else '✗ BLOCKED'}")
if not success:
break
# Print status
status = guardrail.get_current_status()
print(f"\n📊 Current Status:")
print(f" Hourly: ${status['hourly_spend']:.2f}/${status['hourly_limit']:.2f}")
print(f" Daily: ${status['daily_spend']:.2f}/${status['daily_limit']:.2f}")
print(f" Blocked: {status['blocked_requests']} requests")4. Prometheus Metrics Export
# metrics_exporter.py
from prometheus_client import Counter, Histogram, Gauge, start_http_server
import time
Define metrics
REQUEST_COUNT = Counter(
'holysheep_requests_total',
'Total requests to HolySheep API',
['model', 'status']
)
REQUEST_LATENCY = Histogram(
'holysheep_request_latency_seconds',
'Request latency in seconds',
['model', 'endpoint']
)
ACTIVE_REQUESTS = Gauge(
'holysheep_active_requests',
'Currently active requests'
)
RATE_LIMIT_HITS = Counter(
'holysheep_rate_limit_hits_total',
'Total rate limit (429) hits',
['model']
)
SERVER_ERRORS = Counter(
'holysheep_server_errors_total',
'Total server errors (5xx)',
['model', 'status_code']
)
DAILY_COST = Gauge(
'holysheep_daily_cost_usd',
'Daily cost in USD'
)
API_HEALTH = Gauge(
'holysheep_api_health',
'API health status (1=healthy, 0=unhealthy)',
['provider']
)
Usage in your code
def record_request(
model: str,
status: str,
latency_ms: float,
cost_usd: float
):
REQUEST_COUNT.labels(model=model, status=status).inc()
REQUEST_LATENCY.labels(model=model, endpoint='chat').observe(latency_ms / 1000)
if status == 'rate_limited':
RATE_LIMIT_HITS.labels(model=model).inc()
elif status.startswith('5'):
SERVER_ERRORS.labels(model=model, status_code=status).inc()
Start metrics server on port 9090
if __name__ == "__main__":
start_http_server(9090)
print("📊 Prometheus metrics available at :9090")
time.sleep(999999)Lỗi thường gặp và cách khắc phục
1. Lỗi 401 Unauthorized
Mô tả: API key không hợp lệ hoặc đã hết hạn.
# ❌ LỖI THƯỜNG GẶP #1: 401 Unauthorized
Nguyên nhân: API key sai hoặc chưa set đúng
import httpx
Sai - key bị None hoặc empty
client = httpx.AsyncClient()
response = await client.post(
"https://api.holysheep.ai/v1/chat/completions",
headers={"Authorization": f"Bearer {api_key}"} # api_key có thể None!
)
✅ KHẮC PHỤC #1: Validate key trước khi gọi
def validate_api_key(api_key: str) -> bool:
"""Validate API key format và presence"""
if not api_key:
return False
if len(api_key) < 20:
return False
if api_key.startswith("sk-"):
# HolySheep dùng prefix khác
return True
return True # Accept all for HolySheep
async def safe_api_call(api_key: str, payload: dict):
"""API call với validation đầy đủ"""
if not validate_api_key(api