tgo*_*gos 1 monitoring cpu-usage docker grafana prometheus
我的设置:
version: '2'
services:
prometheus_srv:
build: ./prom_serv
image: prom/prometheus
container_name: prometheus_server
hostname: prometheus_server
prometheus_node:
image: prom/node-exporter
container_name: prom_node_exporter
hostname: prom_node_exporter
depends_on:
- prometheus_srv
prometheus_node2:
image: prom/node-exporter
container_name: prom_node_exporter2
hostname: prom_node_exporter2
depends_on:
- prometheus_node
grafana:
image: grafana/grafana
container_name: grafana_server
hostname: grafana_server
depends_on:
- prometheus_node2
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FROM prom/prometheus
ADD prometheus.yml /etc/prometheus/
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# Load and evaluate rules in this file eve
scrape_configs:
# Scrape Prometheus itself
- job_name: 'prometheus'
scrape_interval: 10s
scrape_timeout: 10s
static_configs:
- targets: ['localhost:9090']
# Scrape the Node Exporter
- job_name: 'node'
scrape_interval: 10s
static_configs:
- targets: ['prom_node_exporter:9100']
# Scrape the Node Exporter2
- job_name: 'node2'
scrape_interval: 10s
static_configs:
- targets: ['prom_node_exporter2:9100']
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将 Prometheus 数据源添加到 Grafana 后,我添加了一个新仪表板,其中包含 2 个 CPU 使用情况图,每个节点导出器一个:
100 - (avg by (instance) (irate(node_cpu{job="node",mode="idle"}[5m])) * 100)
100 - (avg by (instance) (irate(node_cpu{job="node2",mode="idle"}[5m])) * 100)
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并尝试为第一个节点导出器生成 CPU 峰值,如下所示:
docker container exec -it prom_node_exporter sh
/ # dd if=/dev/zero of=/dev/null
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我最终发现这两个图看起来非常相似:
我认为使用命令的容器的 CPU 使用率应该高得多。这里出了什么问题?有什么建议么?
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