亿级流量点赞系统第八章

项目地址

GitHub地址💥：https://github.com/tenyon61/likeboom

后端初始化模板💥：https://github.com/tenyon61/springboot3-demo/tree/single

快速开始

✨引入依赖

▼
xml
复制代码
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
    <groupId>io.micrometer</groupId>
    <artifactId>micrometer-registry-prometheus</artifactId>
</dependency>

▼
yaml
复制代码
management:  
  endpoints:  
    web:  
      exposure:  
        include: health, prometheus  
  metrics:  
    distribution:  
      percentiles:  
        http:  
          server:  
            requests: 0.5, 0.75, 0.9, 0.95, 0.99

✨代码改造

ThumbController.java

▼
java
复制代码
private final Counter successCounter;
private final Counter failureCounter;

public ThumbController(MeterRegistry registry) {
    this.successCounter = Counter.builder("thumb.success.count")
            .description("Total sucessful thumb")
            .register(registry);

    this.failureCounter = Counter.builder("thumb.failure.count")
            .description("Total failed thumb")
            .register(registry);
}

✨重启TiDB

执行命令

▼
shell
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tiup playground --tag thumb --without-monitor  --db.host 0.0.0.0

成功执行

✨Redis指标监控

用Redis Exporter监控reids

▼
shell
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docker run --name redis-exporter \
  -p 9121:9121 \
  oliver006/redis_exporter \
  --redis.addr=redis://IP:6379 \
  --redis.password=pwd

执行成功

✨安装Prometheus

创建prometheus.yml，放到/opt/prometheus下面

▼
yaml
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global:  
  scrape_interval:     15s # By default, scrape targets every 15 seconds.  
  
  # Attach these labels to any time series or alerts when communicating with  
  # external systems (federation, remote storage, Alertmanager).  
  external_labels:  
    monitor: 'codelab-monitor'  
  
# A scrape configuration containing exactly one endpoint to scrape:  
# Here it's Prometheus itself.  
scrape_configs:  
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.  
  - job_name: 'prometheus'  
  
    # Override the global default and scrape targets from this job every 5 seconds.  
    scrape_interval: 5s  
  
    static_configs:  
      - targets: ['localhost:9090']  
  - job_name: 'biz'  
    # Override the global default and scrape targets from this job every 5 seconds.  
    scrape_interval: 5s  
    metrics_path: '/api/actuator/prometheus'  
    static_configs:  
      - targets: ['IP:9199']  
        labels:  
          group: 'thumb'  
  - job_name: 'redis'  
    scrape_interval: 5s  
    static_configs:  
      - targets: ['IP:9121']

执行启动命令

▼
shell
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docker run -d \
    --name prometheus \
    -p 9199:9090 \
    -v /opt/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml \
    prom/prometheus

安装成功

✨启动Grafana

▼
shell
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docker run -d -p 3000:3000 --name=grafana \
  --user "$(id -u)" \
  --volume "$PWD/data:/var/lib/grafana" \
  grafana/grafana-enterprise

访问IP:3000admin/admin即可访问

💥配置Prometheus

选择Prometheus

💥连接数据源

连接成功

💥配置各项指标

进入控制面板

给出一些常用配置：

• QPS

▼
shell
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sum(rate(http_server_requests_seconds_count[1m]))

由于是在公网部署的prometheus.yml中定义的biz连接不了本地，因此上面的数据面板是空的，当部署上线后即可看到。

本章总结

搭建 Granfana 作为数据展示平台，应用 Prometheus 作为可观测性解决方案。

项目踩坑

待补充