Grafana：如何根据两个事件创建警报？

Posted 2023-02-15

【中文标题】Grafana：如何根据两个事件创建警报？

【英文标题】：Grafana: How create alert based on two events?

【发布时间】：2020-02-18 11:22:14

【问题描述】：

如果 last_hour_mins_average_status > 3.4 和 last_five_mins_requests_to_gateway_gauge_count > 75 每个相同的网关，我需要创建警报。有以下输入：

# HELP last_five_mins_requests_to_gateway_gauge_count labels: gatewayId
# TYPE last_five_mins_requests_to_gateway_gauge_count gauge
last_five_mins_requests_to_gateway_gauge_countgatewayId="34" 1
last_five_mins_requests_to_gateway_gauge_countgatewayId="38" 32
last_five_mins_requests_to_gateway_gauge_countgatewayId="44" 34
last_five_mins_requests_to_gateway_gauge_countgatewayId="51" 23
last_five_mins_requests_to_gateway_gauge_countgatewayId="68" 14
last_five_mins_requests_to_gateway_gauge_countgatewayId="75" 1
last_five_mins_requests_to_gateway_gauge_countgatewayId="76" 71
last_five_mins_requests_to_gateway_gauge_countgatewayId="79" 1

和

# HELP last_hour_mins_average_status Average value by message status by last 60 minutes
# TYPE last_hour_mins_average_status gauge
last_hour_mins_average_statusgatewayId="34" 1.6923
last_hour_mins_average_statusgatewayId="38" 1.5004
last_hour_mins_average_statusgatewayId="44" 1.1569
last_hour_mins_average_statusgatewayId="51" 1.7835
last_hour_mins_average_statusgatewayId="62" 8.0000
last_hour_mins_average_statusgatewayId="68" 1.3075
last_hour_mins_average_statusgatewayId="75" 1.2727
last_hour_mins_average_statusgatewayId="76" 1.3703
last_hour_mins_average_statusgatewayId="78" 1.0000
last_hour_mins_average_statusgatewayId="79" 2.1622

我创建了查询 A：

avg_over_time(lox24_sms_last_five_mins_requests_to_gateway_gauge_count[1m])

和查询 B：

avg_over_time(lox24_sms_last_hour_mins_average_status[1m])

和警报条件（UI形式）：

when avg() of query(A, 5m, now) is above 75
and avg() of query(B, 5m, now) is above 3.4

当 ANY gatewayId 的消息数 > 75 且 ANY gatewayId 的平均状态 > 3.4 时，就会发生警报。

但只有当这两种情况都发生在同一个 gatewayId 上时，我才需要提醒。

【参考方案1】：

这是应该执行此操作的 Prometheus 查询（尚未测试，但应该可以）：

last_five_mins_requests_to_gateway_gauge_count > 75
  and
last_hour_mins_average_status > 3.4