Chào các bạn, tôi là Minh Đức, Senior DevOps Engineer với 8 năm kinh nghiệm triển khai hệ thống AI production. Trong bài viết này, tôi sẽ chia sẻ kinh nghiệm thực chiến về việc thiết kế quy trình rollback cho AI service, từ những bài học đắt giá khi hệ thống của chúng tôi từng chịu 3 lần downtime nghiêm trọng trong một tháng.
Vì sao cần chiến lược Rollback cho AI Service?
Khác với web service truyền thống, AI service có những đặc thù riêng khiến việc rollback trở nên phức tạp hơn nhiều:
- Model versioning - Mỗi phiên bản model có thể có behavior khác nhau, không chỉ khác về performance
- Latency sensitive - Người dùng AI chat kỳ vọng response dưới 2 giây
- Cost per request cao - Mỗi lần gọi API có thể tốn vài đô la
- Context continuity - Rollback phải đảm bảo conversation history vẫn hoạt động
Kiến trúc Rollback 3 Lớp
Lớp 1: API Gateway với Feature Flag
Tôi đã xây dựng một hệ thống feature flag tại tầng gateway để điều khiển traffic giữa các phiên bản model:
# rollback_manager.py - Hệ thống Rollback cho AI Service
Đặt tại API Gateway hoặc Load Balancer layer
import asyncio
import hashlib
from datetime import datetime, timedelta
from typing import Dict, List, Optional
from dataclasses import dataclass
from enum import Enum
class RollbackStatus(Enum):
STABLE = "stable"
DEGRADED = "degraded"
ROLLBACK_IN_PROGRESS = "rollback_in_progress"
FAILED = "failed"
@dataclass
class ModelVersion:
version_id: str
provider: str # "openai", "anthropic", "holysheep"
endpoint: str
weight: float # Traffic weight (0.0 - 1.0)
status: RollbackStatus
deployed_at: datetime
error_rate: float = 0.0
avg_latency_ms: float = 0.0
p99_latency_ms: float = 0.0
class AIRollbackManager:
"""
Quản lý rollback cho AI service với multi-provider support
"""
def __init__(self):
self.versions: Dict[str, ModelVersion] = {}
self.current_active: Optional[str] = None
self.rollback_history: List[Dict] = []
self.alert_threshold_error_rate = 5.0 # 5%
self.alert_threshold_latency_p99 = 3000 # 3 giây
self.auto_rollback_enabled = True
def register_version(self, version_id: str, provider: str,
api_key: str, weight: float = 1.0) -> bool:
"""Đăng ký một phiên bản model mới"""
# Map provider sang endpoint
endpoints = {
"holysheep": "https://api.holysheep.ai/v1/chat/completions",
"openai": "https://api.openai.com/v1/chat/completions", # fallback only
"anthropic": "https://api.anthropic.com/v1/messages"
}
if provider not in endpoints:
raise ValueError(f"Provider {provider} không được hỗ trợ")
version = ModelVersion(
version_id=version_id,
provider=provider,
endpoint=endpoints[provider],
weight=weight,
status=RollbackStatus.STABLE,
deployed_at=datetime.now()
)
self.versions[version_id] = version
print(f"✅ Đã đăng ký version: {version_id} -> {provider}")
return True
async def health_check(self, version_id: str, test_requests: int = 10) -> Dict:
"""Kiểm tra health của một phiên bản"""
if version_id not in self.versions:
return {"status": "not_found", "version_id": version_id}
version = self.versions[version_id]
errors = 0
latencies = []
for _ in range(test_requests):
start = asyncio.get_event_loop().time()
try:
# Test request đơn giản
response = await self._test_request(version)
latency = (asyncio.get_event_loop().time() - start) * 1000
latencies.append(latency)
except Exception as e:
errors += 1
print(f"❌ Health check failed: {e}")
error_rate = (errors / test_requests) * 100
avg_latency = sum(latencies) / len(latencies) if latencies else 0
p99_latency = sorted(latencies)[int(len(latencies) * 0.99)] if latencies else 0
version.error_rate = error_rate
version.avg_latency_ms = avg_latency
version.p99_latency_ms = p99_latency
health_score = self._calculate_health_score(version)
return {
"version_id": version_id,
"error_rate": f"{error_rate:.2f}%",
"avg_latency_ms": f"{avg_latency:.2f}",
"p99_latency_ms": f"{p99_latency:.2f}",
"health_score": health_score,
"status": "healthy" if health_score > 80 else "degraded"
}
def _calculate_health_score(self, version: ModelVersion) -> float:
"""Tính health score dựa trên error rate và latency"""
# Error rate scoring (0-50 điểm)
error_score = max(0, 50 - (version.error_rate * 10))
# Latency scoring (0-50 điểm) - baseline 500ms
if version.p99_latency_ms < 500:
latency_score = 50
elif version.p99_latency_ms < 2000:
latency_score = 50 - ((version.p99_latency_ms - 500) / 30)
else:
latency_score = max(0, 25 - ((version.p99_latency_ms - 2000) / 100))
return error_score + latency_score
async def initiate_rollback(self, from_version: str, to_version: str,
gradual: bool = True, steps: int = 5) -> Dict:
"""Khởi tạo quy trình rollback"""
if from_version not in self.versions or to_version not in self.versions:
raise ValueError("Version không tồn tại")
print(f"🔄 Bắt đầu rollback: {from_version} -> {to_version}")
rollback_record = {
"id": hashlib.md5(f"{datetime.now().isoformat()}".encode()).hexdigest()[:8],
"from_version": from_version,
"to_version": to_version,
"started_at": datetime.now().isoformat(),
"steps": steps,
"current_step": 0,
"status": "in_progress"
}
self.rollback_history.append(rollback_record)
if gradual:
await self._gradual_rollback(rollback_record)
else:
await self._immediate_rollback(rollback_record)
return rollback_record
async def _gradual_rollback(self, record: Dict, interval_seconds: int = 30):
"""Rollback từ từ theo từng bước"""
to_version = self.versions[record["to_version"]]
steps = record["steps"]
for step in range(steps, 0, -1):
new_weight = (steps - step + 1) / steps
to_version.weight = new_weight
# Cập nhật weight trong nginx/k8s config
await self._update_routing_config(to_version.version_id, new_weight)
record["current_step"] = steps - step + 1
print(f"📊 Step {record['current_step']}/{steps}: Weight = {new_weight:.2f}")
# Monitor trong 30 giây
await asyncio.sleep(interval_seconds)
health = await self.health_check(to_version.version_id)
if health["health_score"] < 50:
print(f"⚠️ Health score thấp: {health['health_score']}, dừng rollback")
record["status"] = "paused"
return
# Hoàn tất rollback
to_version.weight = 1.0
await self._update_routing_config(to_version.version_id, 1.0)
record["status"] = "completed"
record["completed_at"] = datetime.now().isoformat()
print("✅ Rollback hoàn tất!")
async def _immediate_rollback(self, record: Dict):
"""Rollback ngay lập tức"""
to_version = self.versions[record["to_version"]]
to_version.weight = 1.0
await self._update_routing_config(to_version.version_id, 1.0)
record["status"] = "completed"
record["completed_at"] = datetime.now().isoformat()
print("✅ Immediate rollback hoàn tất!")
============== Khởi tạo với HolySheep AI ==============
rollback_manager = AIRollbackManager()
Đăng ký phiên bản production sử dụng HolySheep
rollback_manager.register_version(
version_id="holysheep-gpt4-prod",
provider="holysheep",
api_key="YOUR_HOLYSHEEP_API_KEY",
weight=0.9
)
Phiên bản backup
rollback_manager.register_version(
version_id="holysheep-claude-backup",
provider="holysheep",
api_key="YOUR_HOLYSHEEP_API_KEY",
weight=0.1
)
print("🚀 Hệ thống rollback sẵn sàng với HolySheep AI")
print(f"💰 Chi phí: GPT-4.1 $8/MTok, Claude Sonnet 4.5 $15/MTok, DeepSeek V3.2 $0.42/MTok")Lớp 2: Circuit Breaker Pattern
Đây là thành phần quan trọng giúp tự động phát hiện và cô lập khi API provider gặp sự cố:
# circuit_breaker.py - Circuit Breaker cho AI API Calls
Ngăn chặn cascade failure khi provider gặp vấn đề
import time
import asyncio
from enum import Enum
from typing import Callable, Any, Optional
from dataclasses import dataclass, field
from collections import deque
class CircuitState(Enum):
CLOSED = "closed" # Bình thường, request đi qua
OPEN = "open" # Đang block, không cho request đi
HALF_OPEN = "half_open" # Thử nghiệm, cho một số request đi
@dataclass
class CircuitBreakerConfig:
failure_threshold: int = 5 # Số lần fail để open circuit
success_threshold: int = 3 # Số lần success để close circuit
timeout_seconds: float = 30.0 # Thời gian chuyển từ OPEN sang HALF_OPEN
half_open_max_calls: int = 3 # Số call trong trạng thái half_open
@dataclass
class CircuitMetrics:
total_calls: int = 0
successful_calls: int = 0
failed_calls: int = 0
consecutive_failures: int = 0
consecutive_successes: int = 0
last_failure_time: Optional[float] = None
last_success_time: Optional[float] = None
recent_errors: deque = field(default_factory=lambda: deque(maxlen=20))
latency_p50_ms: float = 0.0
latency_p99_ms: float = 0.0
class CircuitBreaker:
"""
Circuit Breaker Pattern cho AI API Calls
Trạng thái:
- CLOSED: Request bình thường, errors được track
- OPEN: Tất cả request bị reject ngay lập tức
- HALF_OPEN: Cho một số request đi thử nghiệm
"""
def __init__(self, name: str, config: Optional[CircuitBreakerConfig] = None):
self.name = name
self.config = config or CircuitBreakerConfig()
self.state = CircuitState.CLOSED
self.metrics = CircuitMetrics()
self._half_open_calls = 0
self._lock = asyncio.Lock()
# Monitoring callback
self.on_state_change: Optional[Callable] = None
self.on_circuit_open: Optional[Callable] = None
async def call(self, func: Callable, *args, **kwargs) -> Any:
"""Thực hiện call với circuit breaker protection"""
async with self._lock:
# Kiểm tra state trước khi call
if not await self._can_execute():
raise CircuitBreakerOpenError(
f"Circuit '{self.name}' is OPEN. "
f"Last failure: {self.metrics.last_failure_time}"
)
# Trong HALF_OPEN chỉ cho max calls
if self.state == CircuitState.HALF_OPEN:
if self._half_open_calls >= self.config.half_open_max_calls:
raise CircuitBreakerOpenError(
f"Circuit '{self.name}' đang trong HALF_OPEN, "
f"đã đạt max calls"
)
self._half_open_calls += 1
# Thực hiện request với timing
start_time = time.perf_counter()
try:
if asyncio.iscoroutinefunction(func):
result = await func(*args, **kwargs)
else:
result = func(*args, **kwargs)
latency_ms = (time.perf_counter() - start_time) * 1000
await self._record_success(latency_ms)
return result
except Exception as e:
latency_ms = (time.perf_counter() - start_time) * 1000
await self._record_failure(str(e), latency_ms)
raise
async def _can_execute(self) -> bool:
"""Kiểm tra xem có thể thực hiện request không"""
if self.state == CircuitState.CLOSED:
return True
if self.state == CircuitState.OPEN:
# Kiểm tra timeout để chuyển sang HALF_OPEN
if self.metrics.last_failure_time:
time_since_failure = time.time() - self.metrics.last_failure_time
if time_since_failure >= self.config.timeout_seconds:
await self._transition_to_half_open()
return True
return False
# HALF_OPEN: cho phép một số request đi
return True
async def _record_success(self, latency_ms: float):
"""Ghi nhận thành công"""
async with self._lock:
self.metrics.total_calls += 1
self.metrics.successful_calls += 1
self.metrics.consecutive_successes += 1
self.metrics.consecutive_failures = 0
self.metrics.last_success_time = time.time()
# Update latency metrics
self._update_latency_metrics(latency_ms)
if self.state == CircuitState.HALF_OPEN:
if self.metrics.consecutive_successes >= self.config.success_threshold:
await self._transition_to_closed()
async def _record_failure(self, error: str, latency_ms: float):
"""Ghi nhận thất bại"""
async with self._lock:
self.metrics.total_calls += 1
self.metrics.failed_calls += 1
self.metrics.consecutive_failures += 1
self.metrics.consecutive_successes = 0
self.metrics.last_failure_time = time.time()
self.metrics.recent_errors.append({
"error": error,
"timestamp": time.time(),
"latency_ms": latency_ms
})
self._update_latency_metrics(latency_ms)
# Kiểm tra threshold để open circuit
if (self.state == CircuitState.CLOSED and
self.metrics.consecutive_failures >= self.config.failure_threshold):
await self._transition_to_open()
elif self.state == CircuitState.HALF_OPEN:
# Bất kỳ fail nào trong HALF_OPEN đều chuyển về OPEN
await self._transition_to_open()
def _update_latency_metrics(self, latency_ms: float):
"""Cập nhật latency metrics đơn giản"""
# Sử dụng moving average đơn giản
alpha = 0.1
self.metrics.latency_p50_ms = (
(1 - alpha) * self.metrics.latency_p50_ms + alpha * latency_ms
)
self.metrics.latency_p99_ms = (
(1 - alpha * 0.5) * self.metrics.latency_p99_ms + alpha * 0.5 * latency_ms * 1.5
)
async def _transition_to_open(self):
"""Chuyển sang trạng thái OPEN"""
if self.state != CircuitState.OPEN:
old_state = self.state
self.state = CircuitState.OPEN
self._half_open_calls = 0
print(f"🔴 Circuit '{self.name}': {old_state.value} -> OPEN")
if self.on_circuit_open:
await self.on_circuit_open(self)
async def _transition_to_half_open(self):
"""Chuyển sang trạng thái HALF_OPEN"""
old_state = self.state
self.state = CircuitState.HALF_OPEN
self._half_open_calls = 0
print(f"🟡 Circuit '{self.name}': {old_state.value} -> HALF_OPEN")
async def _transition_to_closed(self):
"""Chuyển sang trạng thái CLOSED"""
old_state = self.state
self.state = CircuitState.CLOSED
self.metrics.consecutive_failures = 0
self._half_open_calls = 0
print(f"🟢 Circuit '{self.name}': {old_state.value} -> CLOSED")
def get_status(self) -> dict:
"""Lấy trạng thái circuit breaker"""
return {
"name": self.name,
"state": self.state.value,
"metrics": {
"total_calls": self.metrics.total_calls,
"success_rate": (
self.metrics.successful_calls / self.metrics.total_calls * 100
if self.metrics.total_calls > 0 else 0
),
"consecutive_failures": self.metrics.consecutive_failures,
"latency_p50_ms": round(self.metrics.latency_p50_ms, 2),
"latency_p99_ms": round(self.metrics.latency_p99_ms, 2),
"last_failure": self.metrics.last_failure_time
}
}
async def reset(self):
"""Reset circuit breaker về trạng thái ban đầu"""
async with self._lock:
self.state = CircuitState.CLOSED
self.metrics = CircuitMetrics()
self._half_open_calls = 0
print(f"🔄 Circuit '{self.name}' đã được reset")
class CircuitBreakerOpenError(Exception):
"""Exception khi circuit breaker đang OPEN"""
pass
============== Triển khai với HolySheep AI ==============
Tạo circuit breaker cho từng provider
circuit_holysheep = CircuitBreaker(
name="holysheep-primary",
config=CircuitBreakerConfig(
failure_threshold=3,
success_threshold=2,
timeout_seconds=15.0
)
)
Callback khi circuit open - trigger rollback
async def on_circuit_open(circuit: CircuitBreaker):
print(f"🚨 CIRCUIT OPEN: {circuit.name}")
print(f" Triggering automatic rollback...")
# Gọi rollback manager ở đây
# await rollback_manager.initiate_rollback(...)
circuit_holysheep.on_circuit_open = on_circuit_open
Ví dụ sử dụng trong AI request
async def call_ai_with_protection(prompt: str):
async def make_request():
# Sử dụng HolySheep API
import aiohttp
url = "https://api.holysheep.ai/v1/chat/completions"
headers = {
"Authorization": f"Bearer YOUR_HOLYSHEEP_API_KEY",
"Content-Type": "application/json"
}
data = {
"model": "gpt-4.1",
"messages": [{"role": "user", "content": prompt}]
}
async with aiohttp.ClientSession() as session:
async with session.post(url, json=data, headers=headers) as resp:
return await resp.json()
try:
result = await circuit_holysheep.call(make_request)
return result
except CircuitBreakerOpenError as e:
print(f"⚠️ {e}")
# Fallback sang provider khác hoặc trả cache
return await fallback_to_backup(prompt)
async def fallback_to_backup(prompt: str):
"""Fallback sử dụng DeepSeek qua HolySheep - chi phí thấp hơn"""
print("🔀 Sử dụng fallback DeepSeek V3.2 ($0.42/MTok)")
# Implement fallback logic
pass
Check status
print("📊 Circuit Breaker Status:", circuit_holysheep.get_status())Lớp 3: Automated Monitoring và Alerting
Hệ thống monitoring giúp phát hiện sớm các vấn đề trước khi cần rollback:
# monitoring.py - Real-time Monitoring cho AI Service
Tự động phát hiện anomaly và trigger rollback
import asyncio
import json
from datetime import datetime, timedelta
from typing import Dict, List, Optional
from dataclasses import dataclass
import aiohttp
@dataclass
class AlertRule:
name: str
metric: str
threshold: float
operator: str # "gt", "lt", "eq"
duration_seconds: int
severity: str # "warning", "critical"
action: str # "alert", "auto_rollback"
@dataclass
class Alert:
rule_name: str
severity: str
message: str
timestamp: datetime
current_value: float
threshold: float
class AIMonitoringSystem:
"""
Hệ thống monitoring real-time cho AI service
Tích hợp với HolySheep AI metrics
"""
def __init__(self, webhook_url: Optional[str] = None):
self.metrics_history: Dict[str, List[Dict]] = {}
self.alerts: List[Alert] = []
self.alert_rules: List[AlertRule] = []
self.webhook_url = webhook_url
self.dashboard_data = {
"requests_total": 0,
"requests_success": 0,
"requests_failed": 0,
"total_tokens": 0,
"total_cost_usd": 0.0,
"avg_latency_ms": 0,
"p99_latency_ms": 0
}
# Định nghĩa các alert rules
self._setup_default_rules()
def _setup_default_rules(self):
"""Cài đặt các alert rules mặc định"""
self.alert_rules = [
AlertRule(
name="high_error_rate",
metric="error_rate",
threshold=5.0,
operator="gt",
duration_seconds=60,
severity="critical",
action="auto_rollback"
),
AlertRule(
name="high_latency",
metric="p99_latency_ms",
threshold=3000,
operator="gt",
duration_seconds=120,
severity="warning",
action="alert"
),
AlertRule(
name="cost_anomaly",
metric="cost_per_minute",
threshold=100.0, # $100/phút
operator="gt",
duration_seconds=300,
severity="critical",
action="alert"
),
AlertRule(
name="low_success_rate",
metric="success_rate",
threshold=95.0,
operator="lt",
duration_seconds=300,
severity="critical",
action="auto_rollback"
)
]
async def record_request(self, provider: str, success: bool,
latency_ms: float, tokens_used: int,
cost_usd: float):
"""Ghi nhận một request"""
now = datetime.now()
bucket = now.strftime("%Y-%m-%d %H:%M")
if bucket not in self.metrics_history:
self.metrics_history[bucket] = []
self.metrics_history[bucket].append({
"timestamp": now,
"provider": provider,
"success": success,
"latency_ms": latency_ms,
"tokens": tokens_used,
"cost_usd": cost_usd
})
# Cập nhật dashboard
self.dashboard_data["requests_total"] += 1
if success:
self.dashboard_data["requests_success"] += 1
else:
self.dashboard_data["requests_failed"] += 1
self.dashboard_data["total_tokens"] += tokens_used
self.dashboard_data["total_cost_usd"] += cost_usd
def get_current_metrics(self) -> Dict:
"""Tính toán metrics hiện tại"""
now = datetime.now()
last_5_minutes = now - timedelta(minutes=5)
recent_requests = []
for bucket_data in self.metrics_history.values():
for req in bucket_data:
if req["timestamp"] >= last_5_minutes:
recent_requests.append(req)
if not recent_requests:
return {
"error_rate": 0,
"success_rate": 100,
"avg_latency_ms": 0,
"p99_latency_ms": 0,
"cost_per_minute": 0,
"rpm": 0
}
total = len(recent_requests)
successful = sum(1 for r in recent_requests if r["success"])
total_latency = sum(r["latency_ms"] for r in recent_requests)
total_cost = sum(r["cost_usd"] for r in recent_requests)
# Tính P99 latency
sorted_latencies = sorted(r["latency_ms"] for r in recent_requests)
p99_index = int(len(sorted_latencies) * 0.99)
p99_latency = sorted_latencies[p99_index] if sorted_latencies else 0
# Tính cost per minute (trong 5 phút)
cost_per_minute = (total_cost / 5) if total_cost > 0 else 0
return {
"error_rate": round((total - successful) / total * 100, 2),
"success_rate": round(successful / total * 100, 2),
"avg_latency_ms": round(total_latency / total, 2),
"p99_latency_ms": round(p99_latency, 2),
"cost_per_minute": round(cost_per_minute, 2),
"rpm": round(total / 5, 2), # requests per minute
"total_requests_5min": total
}
async def evaluate_alert_rules(self) -> List[Alert]:
"""Đánh giá tất cả alert rules"""
current_metrics = self.get_current_metrics()
triggered_alerts = []
for rule in self.alert_rules:
value = current_metrics.get(rule.metric, 0)
breached = self._check_threshold(value, rule.threshold, rule.operator)
if breached:
alert = Alert(
rule_name=rule.name,
severity=rule.severity,
message=self._format_alert_message(rule, value),
timestamp=datetime.now(),
current_value=value,
threshold=rule.threshold
)
triggered_alerts.append(alert)
self.alerts.append(alert)
# Thực hiện action
if rule.action == "auto_rollback" and rule.severity == "critical":
await self._trigger_auto_rollback(alert)
# Gửi webhook notification
if self.webhook_url:
await self._send_webhook(alert)
return triggered_alerts
def _check_threshold(self, value: float, threshold: float, operator: str) -> bool:
"""Kiểm tra ngưỡng"""
if operator == "gt":
return value > threshold
elif operator == "lt":
return value < threshold
elif operator == "eq":
return value == threshold
return False
def _format_alert_message(self, rule: AlertRule, value: float) -> str:
"""Format message cho alert"""
operator_symbol = {
"gt": ">",
"lt": "<",
"eq": "="
}.get(rule.operator, rule.operator)
return (
f"🔔 Alert: {rule.name}\n"
f" Severity: {rule.severity.upper()}\n"
f" Current: {value:.2f} {operator_symbol} {rule.threshold}\n"
f" Metric: {rule.metric}\n"
f" Action: {rule.action}"
)
async def _trigger_auto_rollback(self, alert: Alert):
"""Trigger automatic rollback khi alert critical"""
print(f"🚨🚨🚨 AUTO ROLLBACK TRIGGERED 🚨🚨🚨")
print(f" Alert: {alert.rule_name}")
print(f" Value: {alert.current_value} (threshold: {alert.threshold})")
# Gọi rollback manager
# await rollback_manager.initiate_rollback(...)
# Log event
rollback_event = {
"type": "auto_rollback",
"triggered_by": alert.rule_name,
"timestamp": datetime.now().isoformat(),
"alert_details": {
"severity": alert.severity,
"current_value": alert.current_value
}
}
print(f"📝 Rollback event logged: {json.dumps(rollback_event, indent=2)}")
async def _send_webhook(self, alert: Alert):
"""Gửi notification qua webhook"""
try:
payload = {
"alert": {
"name": alert.rule_name,
"severity": alert.severity,
"message": alert.message,
"timestamp": alert.timestamp.isoformat(),
"current_value": alert.current_value,
"threshold": alert.threshold
},
"current_metrics": self.get_current_metrics()
}
async with aiohttp.ClientSession() as session:
await session.post(
self.webhook_url,
json=payload,
headers={"Content-Type": "application/json"}
)
print(f"✅ Webhook sent for alert: {alert.rule_name}")
except Exception as e:
print(f"❌ Failed to send webhook: {e}")
def get_dashboard(self) -> Dict:
"""Lấy dữ liệu dashboard"""
metrics = self.get_current_metrics()
return {
"timestamp": datetime.now().isoformat(),
"service_status": self._calculate_service_status(metrics),
"metrics": metrics,
"cumulated": self.dashboard_data,
"recent_alerts": [
{
"rule": a.rule_name,
"severity": a.severity,
"timestamp": a.timestamp.isoformat()
}
for a in self.alerts[-10:]
]
}
def _calculate_service_status(self, metrics: Dict) -> str:
"""Tính toán trạng thái service tổng thể"""
if metrics["success_rate"] >= 99 and metrics["p99_latency_ms"] < 2000:
return "🟢 HEALTHY"
elif metrics["success_rate"] >= 95 and metrics["p99_latency_ms"] < 3000:
return "🟡 DEGRADED"
else:
return "🔴 CRITICAL"
async def start_monitoring_loop(self, interval_seconds: int = 10):
"""Bắt đầu vòng lặp monitoring"""
print(f"📊 Bắt đầu monitoring loop (interval: {interval_seconds}s)")
while True:
try:
# Evaluate alerts
triggered = await self.evaluate_alert_rules()
if triggered:
for alert in triggered:
print(alert.message)
# Dashboard update
dashboard = self.get_dashboard()
print(f"\n{'='*60}")
print(f"📈 AI Service Dashboard - {dashboard['timestamp']}")
print(f"{'='*60}")
print(f"Status: {dashboard['service_status']}")
print(f"Error Rate: {dashboard['metrics']['error_rate']}%")
print(f"Success Rate: {dashboard['metrics']['success_rate']}%")
print(f"P99 Latency: {dashboard['metrics']['p99_latency_ms']}ms")
print(f"Cost/Min: ${dashboard['metrics']['cost_per_minute']:.2f}")
print(f"{'='*60}\n")
except Exception as e:
print(f"❌ Monitoring error: {e}")
await asyncio.sleep(interval_seconds)
============== Triển khai với HolySheep AI ==============
monitoring = AIMonitoringSystem(
webhook_url="https://your-webhook-endpoint.com/alerts"
)
Thêm custom rule cho HolySheep specific metrics
monitoring.alert_rules.append(
AlertRule(
name="holysheep_quota_warning",
metric="quota_usage_percent",
threshold=80.0,
operator="gt",
duration_seconds=60,
severity="warning",
action="alert"
)
)
Simulate monitoring loop
async def simulate_requests