机器学习模型服务质量指标体系

核心监控指标配置

1. 模型性能指标

# 响应时间监控
- metric: model_latency_ms
  threshold: 500ms
  alert_level: warning
  recovery_threshold: 300ms

# 准确率监控
- metric: model_accuracy_rate
  threshold: 0.95
  alert_level: critical
  recovery_threshold: 0.97

# F1分数监控
- metric: model_f1_score
  threshold: 0.90
  alert_level: warning
  recovery_threshold: 0.92

2. 数据质量指标

# 输入数据分布
- metric: input_distribution_drift
  threshold: 0.05
  alert_level: critical
  recovery_threshold: 0.02

# 数据完整性
- metric: data_completeness_rate
  threshold: 0.98
  alert_level: warning
  recovery_threshold: 0.99

告警配置方案

Prometheus告警规则

groups:
- name: model_monitoring
  rules:
  - alert: HighModelLatency
    expr: histogram_quantile(0.95, sum(rate(model_response_time_seconds_bucket[5m])) by (job)) > 0.5
    for: 2m
    labels:
      severity: critical
    annotations:
      summary: "模型响应时间超过阈值"

日志分析配置

通过ELK Stack监控模型推理日志，设置异常模式检测规则，当出现连续10次请求延迟超过300ms时触发告警。