Xiaoxia AI
ca0292e37f
- 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
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## 📊 概述
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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。
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---
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## 🔍 监控指标
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### 1. 请求性能监控
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每个请求自动记录：
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- 响应时间
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- 请求 ID（用于追踪）
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- HTTP 状态码
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- 慢请求告警
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**响应头：**
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```
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X-Request-ID: 123e4567-e89b-12d3-a456-426614174000
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X-Process-Time: 0.123
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```
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### 2. 数据库查询监控
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自动监控：
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- 查询次数
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- 查询耗时
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- 慢查询（>100ms）
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### 3. 连接池监控
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实时监控：
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- 活跃连接数
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- 空闲连接数
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- 连接池使用率
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---
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## 🚨 慢请求告警
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### 配置阈值
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```python
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# apps/api/main.py
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app.add_middleware(
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PerformanceMonitoringMiddleware,
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slow_request_threshold=1.0, # 1 秒
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)
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```
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### 日志示例
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```
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WARNING: Slow request detected: GET /api/v1/projects
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took 2.456s (threshold: 1.0s) [request_id=abc123]
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```
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---
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## 📈 性能指标接口
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### 获取连接池状态
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```http
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GET /api/v1/monitoring/pool-stats
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Response:
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{
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"active_connections": 5,
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"idle_connections": 3,
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"max_connections": 10,
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"usage_percent": 50.0
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}
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```
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### 获取性能统计
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```http
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GET /api/v1/monitoring/performance
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Response:
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{
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"requests_last_hour": 1523,
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"avg_response_time": 0.045,
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"slow_requests": 12,
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"error_rate": 0.02
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}
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```
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---
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## 🔧 性能优化建议
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### 1. 识别慢请求
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查看日志找出慢请求：
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```bash
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grep "Slow request" logs/app.log
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```
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### 2. 分析数据库查询
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查看慢查询：
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```bash
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grep "Slow query" logs/app.log
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```
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### 3. 优化策略
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**慢请求优化：**
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- 添加缓存（Redis）
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- 优化业务逻辑
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- 使用异步处理
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**慢查询优化：**
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- 添加数据库索引
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- 优化 SQL 查询
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- 减少 N+1 查询
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**连接池优化：**
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- 调整 `maxconn` 配置
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- 检查连接泄漏
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- 优化连接复用
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---
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## 📊 监控最佳实践
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### 1. 设置告警
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```python
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# 慢请求告警
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if process_time > 1.0:
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send_alert(f"Slow request: {request.url}")
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# 错误率告警
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if error_rate > 0.05: # 5%
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send_alert(f"High error rate: {error_rate}")
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```
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### 2. 定期审查
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- 每日检查慢请求日志
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- 每周审查性能趋势
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- 每月优化瓶颈
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### 3. 压力测试
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```bash
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# 使用 Apache Bench
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ab -n 1000 -c 10 http://localhost:8000/api/v1/workspaces
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# 使用 wrk
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wrk -t4 -c100 -d30s http://localhost:8000/api/v1/workspaces
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```
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---
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## 🎯 性能目标
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| 指标 | 目标 | 优秀 |
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|------|------|------|
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| API 平均响应时间 | <200ms | <50ms |
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| 数据库查询平均时间 | <50ms | <10ms |
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| 慢请求比例 | <5% | <1% |
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| 错误率 | <1% | <0.1% |
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| 连接池使用率 | <80% | <60% |
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---
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## 🔗 相关工具
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**APM 工具（推荐）：**
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- New Relic
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- Datadog
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- Sentry
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**开源方案：**
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- Prometheus + Grafana
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- ELK Stack
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- Jaeger (分布式追踪)
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---
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**最后更新:** 2026-06-17
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