Xiaoxia AI
9c9818a4b1
- Add PerformanceMonitoringMiddleware for request tracking - Generate unique request ID for each request - Log slow requests (threshold configurable, default 1s) - Add DatabaseQueryLogger for slow query detection - Add X-Request-ID and X-Process-Time headers - Comprehensive performance monitoring documentation - Include optimization strategies and best practices Phase 4 Task 42/68 completed
188 lines
2.8 KiB
Markdown
188 lines
2.8 KiB
Markdown
# 性能监控指南
|
||
|
||
## 📊 概述
|
||
|
||
小虾 SaaS 内置了完整的性能监控系统，帮助识别和优化性能瓶颈。
|
||
|
||
---
|
||
|
||
## 🔍 监控指标
|
||
|
||
### 1. 请求性能监控
|
||
|
||
每个请求自动记录：
|
||
- 响应时间
|
||
- 请求 ID（用于追踪）
|
||
- HTTP 状态码
|
||
- 慢请求告警
|
||
|
||
**响应头：**
|
||
```
|
||
X-Request-ID: 123e4567-e89b-12d3-a456-426614174000
|
||
X-Process-Time: 0.123
|
||
```
|
||
|
||
### 2. 数据库查询监控
|
||
|
||
自动监控：
|
||
- 查询次数
|
||
- 查询耗时
|
||
- 慢查询（>100ms）
|
||
|
||
### 3. 连接池监控
|
||
|
||
实时监控：
|
||
- 活跃连接数
|
||
- 空闲连接数
|
||
- 连接池使用率
|
||
|
||
---
|
||
|
||
## 🚨 慢请求告警
|
||
|
||
### 配置阈值
|
||
|
||
```python
|
||
# apps/api/main.py
|
||
app.add_middleware(
|
||
PerformanceMonitoringMiddleware,
|
||
slow_request_threshold=1.0, # 1 秒
|
||
)
|
||
```
|
||
|
||
### 日志示例
|
||
|
||
```
|
||
WARNING: Slow request detected: GET /api/v1/projects
|
||
took 2.456s (threshold: 1.0s) [request_id=abc123]
|
||
```
|
||
|
||
---
|
||
|
||
## 📈 性能指标接口
|
||
|
||
### 获取连接池状态
|
||
|
||
```http
|
||
GET /api/v1/monitoring/pool-stats
|
||
|
||
Response:
|
||
{
|
||
"active_connections": 5,
|
||
"idle_connections": 3,
|
||
"max_connections": 10,
|
||
"usage_percent": 50.0
|
||
}
|
||
```
|
||
|
||
### 获取性能统计
|
||
|
||
```http
|
||
GET /api/v1/monitoring/performance
|
||
|
||
Response:
|
||
{
|
||
"requests_last_hour": 1523,
|
||
"avg_response_time": 0.045,
|
||
"slow_requests": 12,
|
||
"error_rate": 0.02
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## 🔧 性能优化建议
|
||
|
||
### 1. 识别慢请求
|
||
|
||
查看日志找出慢请求：
|
||
```bash
|
||
grep "Slow request" logs/app.log
|
||
```
|
||
|
||
### 2. 分析数据库查询
|
||
|
||
查看慢查询：
|
||
```bash
|
||
grep "Slow query" logs/app.log
|
||
```
|
||
|
||
### 3. 优化策略
|
||
|
||
**慢请求优化：**
|
||
- 添加缓存（Redis）
|
||
- 优化业务逻辑
|
||
- 使用异步处理
|
||
|
||
**慢查询优化：**
|
||
- 添加数据库索引
|
||
- 优化 SQL 查询
|
||
- 减少 N+1 查询
|
||
|
||
**连接池优化：**
|
||
- 调整 `maxconn` 配置
|
||
- 检查连接泄漏
|
||
- 优化连接复用
|
||
|
||
---
|
||
|
||
## 📊 监控最佳实践
|
||
|
||
### 1. 设置告警
|
||
|
||
```python
|
||
# 慢请求告警
|
||
if process_time > 1.0:
|
||
send_alert(f"Slow request: {request.url}")
|
||
|
||
# 错误率告警
|
||
if error_rate > 0.05: # 5%
|
||
send_alert(f"High error rate: {error_rate}")
|
||
```
|
||
|
||
### 2. 定期审查
|
||
|
||
- 每日检查慢请求日志
|
||
- 每周审查性能趋势
|
||
- 每月优化瓶颈
|
||
|
||
### 3. 压力测试
|
||
|
||
```bash
|
||
# 使用 Apache Bench
|
||
ab -n 1000 -c 10 http://localhost:8000/api/v1/workspaces
|
||
|
||
# 使用 wrk
|
||
wrk -t4 -c100 -d30s http://localhost:8000/api/v1/workspaces
|
||
```
|
||
|
||
---
|
||
|
||
## 🎯 性能目标
|
||
|
||
| 指标 | 目标 | 优秀 |
|
||
|------|------|------|
|
||
| API 平均响应时间 | <200ms | <50ms |
|
||
| 数据库查询平均时间 | <50ms | <10ms |
|
||
| 慢请求比例 | <5% | <1% |
|
||
| 错误率 | <1% | <0.1% |
|
||
| 连接池使用率 | <80% | <60% |
|
||
|
||
---
|
||
|
||
## 🔗 相关工具
|
||
|
||
**APM 工具（推荐）：**
|
||
- New Relic
|
||
- Datadog
|
||
- Sentry
|
||
|
||
**开源方案：**
|
||
- Prometheus + Grafana
|
||
- ELK Stack
|
||
- Jaeger (分布式追踪)
|
||
|
||
---
|
||
|
||
**最后更新:** 2026-06-17
|