SpringBoot Admin與Prometheus集成監(jiān)控

更新時(shí)間：2026年01月23日 11:01:32 作者：CarlowZJ

本文深入探討Spring Boot Admin與Prometheus的集成監(jiān)控方案,文中通過示例代碼介紹的非常詳細(xì),對(duì)大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價(jià)值,需要的朋友們下面隨著小編來一起學(xué)習(xí)學(xué)習(xí)吧

摘要

本文深入探討Spring Boot Admin與Prometheus的集成監(jiān)控方案，包括指標(biāo)收集、數(shù)據(jù)導(dǎo)出、可視化展示等關(guān)鍵技術(shù)點(diǎn)。通過詳細(xì)的技術(shù)解析和實(shí)踐示例，幫助開發(fā)者構(gòu)建完整的微服務(wù)監(jiān)控體系。

1. 引言

Prometheus作為開源的系統(tǒng)監(jiān)控和報(bào)警工具包，已經(jīng)成為云原生監(jiān)控的標(biāo)準(zhǔn)。Spring Boot Admin結(jié)合Prometheus可以提供更強(qiáng)大的監(jiān)控能力。本文將詳細(xì)介紹如何實(shí)現(xiàn)兩者的集成。

2. Prometheus基礎(chǔ)

2.1 Prometheus架構(gòu)

Prometheus生態(tài)系統(tǒng)包含以下組件：

Prometheus Server：收集和存儲(chǔ)指標(biāo)數(shù)據(jù)
Client Libraries：用于應(yīng)用代碼中暴露指標(biāo)
Pushgateway：支持批處理作業(yè)的指標(biāo)推送
Alertmanager：處理報(bào)警
可視化工具：如Grafana

2.2 數(shù)據(jù)模型

Prometheus使用時(shí)間序列數(shù)據(jù)模型，每個(gè)時(shí)間序列由指標(biāo)名稱和鍵值對(duì)標(biāo)簽標(biāo)識(shí)。

3. 集成配置

3.1 依賴配置

<dependencies>
    <!-- Spring Boot Admin Server -->
    <dependency>
        <groupId>de.codecentric</groupId>
        <artifactId>spring-boot-admin-starter-server</artifactId>
    </dependency>
    
    <!-- Spring Boot Actuator -->
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-actuator</artifactId>
    </dependency>
    
    <!-- Micrometer Prometheus Registry -->
    <dependency>
        <groupId>io.micrometer</groupId>
        <artifactId>micrometer-registry-prometheus</artifactId>
    </dependency>
    
    <!-- Spring Boot Starter Web -->
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-web</artifactId>
    </dependency>
</dependencies>

3.2 應(yīng)用配置

# application.yml
server:
  port: 8022

spring:
  application:
    name: admin-server-prometheus

# Actuator配置
management:
  endpoints:
    web:
      exposure:
        include: health,info,metrics,prometheus
      base-path: /actuator
  endpoint:
    health:
      show-details: always
    prometheus:
      enabled: true
  metrics:
    export:
      prometheus:
        enabled: true
    distribution:
      percentiles-histogram:
        all: true
      sla:
        http.server.requests: 10ms, 50ms, 100ms, 200ms, 500ms, 1000ms

# Spring Boot Admin配置
boot:
  admin:
    server:
      ui:
        title: 'Prometheus集成監(jiān)控平臺(tái)'
        brand: '<img src="assets/img/icon-spring-boot-admin.svg"><span>Prometheus集成監(jiān)控平臺(tái)</span>'

info:
  app:
    name: ${spring.application.name}
    version: ${project.version}
    description: Spring Boot Admin與Prometheus集成示例

4. 指標(biāo)收集與暴露

4.1 自定義指標(biāo)收集器

package com.springboot.admin.prometheus;

import io.micrometer.core.instrument.Counter;
import io.micrometer.core.instrument.Gauge;
import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.core.instrument.binder.MeterBinder;
import org.springframework.stereotype.Component;

@Component
public class CustomMetricsCollector implements MeterBinder {
    
    private Counter requestCounter;
    private Counter errorCounter;
    
    @Override
    public void bindTo(MeterRegistry registry) {
        // 請(qǐng)求計(jì)數(shù)器
        requestCounter = Counter.builder("http_requests_total")
            .description("Total number of HTTP requests")
            .register(registry);
            
        // 錯(cuò)誤計(jì)數(shù)器
        errorCounter = Counter.builder("http_errors_total")
            .description("Total number of HTTP errors")
            .register(registry);
            
        // 系統(tǒng)指標(biāo)
        Gauge.builder("system_cpu_usage")
            .description("System CPU usage")
            .register(registry, this, obj -> getSystemCpuUsage());
            
        Gauge.builder("system_memory_usage")
            .description("System memory usage")
            .register(registry, this, obj -> getSystemMemoryUsage());
    }
    
    public void incrementRequest() {
        if (requestCounter != null) {
            requestCounter.increment();
        }
    }
    
    public void incrementError() {
        if (errorCounter != null) {
            errorCounter.increment();
        }
    }
    
    private double getSystemCpuUsage() {
        // 獲取系統(tǒng)CPU使用率
        return Math.random() * 100; // 模擬數(shù)據(jù)
    }
    
    private double getSystemMemoryUsage() {
        // 獲取系統(tǒng)內(nèi)存使用率
        long totalMemory = Runtime.getRuntime().totalMemory();
        long freeMemory = Runtime.getRuntime().freeMemory();
        return (double) (totalMemory - freeMemory) / totalMemory * 100;
    }
}

4.2 業(yè)務(wù)指標(biāo)收集

package com.springboot.admin.prometheus;

import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.core.instrument.Tag;
import io.micrometer.core.instrument.Timer;
import org.springframework.stereotype.Service;

import java.util.concurrent.TimeUnit;

@Service
public class BusinessMetricsService {
    
    private final MeterRegistry meterRegistry;
    private final Timer businessOperationTimer;
    
    public BusinessMetricsService(MeterRegistry meterRegistry) {
        this.meterRegistry = meterRegistry;
        
        // 業(yè)務(wù)操作計(jì)時(shí)器
        this.businessOperationTimer = Timer.builder("business.operation.duration")
            .description("Business operation duration")
            .register(meterRegistry);
    }
    
    public <T> T recordBusinessOperation(String operationName, java.util.function.Supplier<T> operation) {
        return businessOperationTimer
            .tag("operation", operationName)
            .recordCallable(operation::get);
    }
    
    public void recordBusinessEvent(String eventType, String service) {
        meterRegistry.counter("business.events.total", 
            Tag.of("type", eventType),
            Tag.of("service", service))
            .increment();
    }
    
    public void recordBusinessGauge(String name, double value, String service) {
        meterRegistry.gauge("business." + name, 
            Tag.of("service", service), 
            value);
    }
}

5. Prometheus配置

5.1 Prometheus配置文件

# prometheus.yml
global:
  scrape_interval: 15s
  evaluation_interval: 15s

rule_files:
  - "alert_rules.yml"

scrape_configs:
  - job_name: 'admin-server'
    static_configs:
      - targets: ['localhost:8022']
    metrics_path: '/actuator/prometheus'
    scrape_interval: 10s
    scrape_timeout: 5s
    honor_labels: true
    relabel_configs:
      - source_labels: [__address__]
        target_label: instance

  - job_name: 'microservices'
    metrics_path: '/actuator/prometheus'
    scrape_interval: 10s
    scrape_timeout: 5s
    static_configs:
      - targets: ['service1:8080', 'service2:8081', 'service3:8082']
    relabel_configs:
      - source_labels: [__address__]
        target_label: instance

alerting:
  alertmanagers:
    - static_configs:
        - targets: ['alertmanager:9093']

5.2 告警規(guī)則配置

# alert_rules.yml
groups:
  - name: admin_server_alerts
    rules:
      - alert: AdminServerDown
        expr: up{job="admin-server"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Admin Server is down"
          description: "Admin Server {{ $labels.instance }} has been down for more than 1 minute."

      - alert: HighCpuUsage
        expr: system_cpu_usage > 80
        for: 2m
        labels:
          severity: warning
        annotations:
          summary: "High CPU usage on {{ $labels.instance }}"
          description: "CPU usage is above 80% on instance {{ $labels.instance }}."

      - alert: HighMemoryUsage
        expr: system_memory_usage > 85
        for: 2m
        labels:
          severity: warning
        annotations:
          summary: "High memory usage on {{ $labels.instance }}"
          description: "Memory usage is above 85% on instance {{ $labels.instance }}."

      - alert: HighErrorRate
        expr: rate(http_errors_total[5m]) > 10
        for: 2m
        labels:
          severity: warning
        annotations:
          summary: "High error rate on {{ $labels.instance }}"
          description: "Error rate is above 10 requests per minute on instance {{ $labels.instance }}."

6. 數(shù)據(jù)導(dǎo)出與格式化

6.1 自定義指標(biāo)格式化

package com.springboot.admin.prometheus;

import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.prometheus.PrometheusMeterRegistry;
import org.springframework.stereotype.Component;

@Component
public class PrometheusCustomFormatter {
    
    public void customizePrometheusRegistry(PrometheusMeterRegistry registry) {
        // 自定義指標(biāo)格式化
        registry.config()
            .meterFilter(new io.micrometer.core.instrument.config.MeterFilter() {
                @Override
                public io.micrometer.core.instrument.Meter.Id map(io.micrometer.core.instrument.Meter.Id id) {
                    // 添加自定義標(biāo)簽
                    if (id.getName().startsWith("http.")) {
                        return id.withTags(io.micrometer.core.instrument.Tag.of("application", "admin-server"));
                    }
                    return id;
                }
            });
    }
}

6.2 指標(biāo)數(shù)據(jù)處理

package com.springboot.admin.prometheus;

import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.core.instrument.Tag;
import org.springframework.stereotype.Component;

import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;

@Component
public class MetricsProcessor {
    
    private final MeterRegistry meterRegistry;
    private final ConcurrentHashMap<String, AtomicLong> customCounters = new ConcurrentHashMap<>();
    
    public MetricsProcessor(MeterRegistry meterRegistry) {
        this.meterRegistry = meterRegistry;
    }
    
    public void incrementCustomCounter(String name, String... tags) {
        String key = buildKey(name, tags);
        AtomicLong counter = customCounters.computeIfAbsent(key, k -> new AtomicLong(0));
        long value = counter.incrementAndGet();
        
        // 同步到Prometheus
        meterRegistry.counter("custom." + name, 
            buildTags(tags))
            .increment();
    }
    
    public void recordCustomGauge(String name, double value, String... tags) {
        meterRegistry.gauge("custom." + name, 
            java.util.Arrays.asList(buildTags(tags)), 
            value);
    }
    
    private String buildKey(String name, String... tags) {
        StringBuilder key = new StringBuilder(name);
        for (String tag : tags) {
            key.append(".").append(tag);
        }
        return key.toString();
    }
    
    private Iterable<Tag> buildTags(String... tags) {
        java.util.List<Tag> tagList = new java.util.ArrayList<>();
        for (int i = 0; i < tags.length; i += 2) {
            if (i + 1 < tags.length) {
                tagList.add(Tag.of(tags[i], tags[i + 1]));
            }
        }
        return tagList;
    }
}

7. 監(jiān)控面板集成

7.1 Grafana配置

{
  "dashboard": {
    "id": null,
    "title": "Admin Server Dashboard",
    "tags": ["admin", "spring-boot", "prometheus"],
    "timezone": "browser",
    "panels": [
      {
        "id": 1,
        "title": "HTTP Requests",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(http_requests_total[1m])",
            "legendFormat": "Requests per second"
          }
        ]
      },
      {
        "id": 2,
        "title": "System CPU Usage",
        "type": "singlestat",
        "targets": [
          {
            "expr": "system_cpu_usage",
            "legendFormat": "CPU Usage"
          }
        ]
      },
      {
        "id": 3,
        "title": "System Memory Usage",
        "type": "graph",
        "targets": [
          {
            "expr": "system_memory_usage",
            "legendFormat": "Memory Usage"
          }
        ]
      }
    ]
  }
}

7.2 監(jiān)控?cái)?shù)據(jù)API

package com.springboot.admin.api;

import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.prometheus.PrometheusMeterRegistry;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.http.ResponseEntity;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
@RequestMapping("/api/metrics")
public class MetricsApiController {
    
    @Autowired
    private MeterRegistry meterRegistry;
    
    @Autowired
    private PrometheusMeterRegistry prometheusRegistry;
    
    @GetMapping("/prometheus")
    public ResponseEntity<String> getPrometheusMetrics() {
        return ResponseEntity.ok(prometheusRegistry.scrape());
    }
    
    @GetMapping("/summary")
    public ResponseEntity<MetricsSummary> getMetricsSummary() {
        MetricsSummary summary = new MetricsSummary();
        
        // 獲取各種指標(biāo)的摘要信息
        summary.setTotalMeters(meterRegistry.getMeters().size());
        summary.setGauges(meterRegistry.find("gauge").meters().size());
        summary.setCounters(meterRegistry.find("counter").meters().size());
        summary.setTimers(meterRegistry.find("timer").meters().size());
        
        return ResponseEntity.ok(summary);
    }
    
    public static class MetricsSummary {
        private int totalMeters;
        private int gauges;
        private int counters;
        private int timers;
        
        // getter和setter方法
        public int getTotalMeters() { return totalMeters; }
        public void setTotalMeters(int totalMeters) { this.totalMeters = totalMeters; }
        public int getGauges() { return gauges; }
        public void setGauges(int gauges) { this.gauges = gauges; }
        public int getCounters() { return counters; }
        public void setCounters(int counters) { this.counters = counters; }
        public int getTimers() { return timers; }
        public void setTimers(int timers) { this.timers = timers; }
    }
}

8. 高級(jí)功能

8.1 指標(biāo)過濾與轉(zhuǎn)換

package com.springboot.admin.prometheus;

import io.micrometer.core.instrument.config.MeterFilter;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class MetricsFilterConfig {
    
    @Bean
    public MeterFilter metricsFilter() {
        return MeterFilter.maximumAllowableMetrics(1000)
            .andThen(MeterFilter.maximumAllowableTags("http.server.requests", "uri", 100))
            .andThen(MeterFilter.denyUnless(meter -> 
                meter.getName().startsWith("http.") || 
                meter.getName().startsWith("jvm.") ||
                meter.getName().startsWith("system.") ||
                meter.getName().startsWith("tomcat.")
            ));
    }
    
    @Bean
    public MeterFilter namingConventionFilter() {
        return MeterFilter.renameTag("http.server.requests", "method", "httpMethod")
            .andThen(MeterFilter.renameTag("http.server.requests", "uri", "httpUri"));
    }
}

8.2 指標(biāo)聚合

package com.springboot.admin.prometheus;

import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.core.instrument.Tag;
import io.micrometer.core.instrument.Timer;
import org.springframework.stereotype.Component;

import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.TimeUnit;

@Component
public class MetricsAggregator {
    
    private final MeterRegistry meterRegistry;
    private final ConcurrentHashMap<String, Timer.Sample> activeOperations = new ConcurrentHashMap<>();
    
    public MetricsAggregator(MeterRegistry meterRegistry) {
        this.meterRegistry = meterRegistry;
    }
    
    public void startOperation(String operationName, String service) {
        Timer.Sample sample = Timer.start(meterRegistry);
        String key = operationName + ":" + service;
        activeOperations.put(key, sample);
    }
    
    public void endOperation(String operationName, String service) {
        String key = operationName + ":" + service;
        Timer.Sample sample = activeOperations.remove(key);
        if (sample != null) {
            sample.stop(Timer.builder("operation.duration")
                .description("Operation duration")
                .tags(Tag.of("operation", operationName), Tag.of("service", service))
                .register(meterRegistry));
        }
    }
    
    public void recordHistogram(String metricName, double value, String... tags) {
        meterRegistry.timer(metricName, buildTags(tags))
            .record((long) value, TimeUnit.MILLISECONDS);
    }
    
    private Iterable<Tag> buildTags(String... tags) {
        java.util.List<Tag> tagList = new java.util.ArrayList<>();
        for (int i = 0; i < tags.length; i += 2) {
            if (i + 1 < tags.length) {
                tagList.add(Tag.of(tags[i], tags[i + 1]));
            }
        }
        return tagList;
    }
}

9. 部署配置

9.1 Docker配置

# Dockerfile
FROM openjdk:8-jre-alpine

# 創(chuàng)建應(yīng)用目錄
RUN addgroup -S spring && adduser -S spring -G spring
USER spring:spring
WORKDIR /app

# 復(fù)制應(yīng)用文件
COPY --chown=spring:spring target/admin-server-prometheus.jar app.jar

# 暴露端口
EXPOSE 8022

# 啟動(dòng)命令
ENTRYPOINT ["java", "-jar", "app.jar"]

9.2 Docker Compose配置

# docker-compose.yml
version: '3.8'

services:
  admin-server:
    build: .
    container_name: admin-server-prometheus
    ports:
      - "8022:8022"
    environment:
      - SPRING_PROFILES_ACTIVE=prometheus
    networks:
      - monitoring

  prometheus:
    image: prom/prometheus:latest
    container_name: prometheus
    ports:
      - "9090:9090"
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml
    command:
      - '--config.file=/etc/prometheus/prometheus.yml'
      - '--storage.tsdb.path=/prometheus'
      - '--web.console.libraries=/etc/prometheus/console_libraries'
      - '--web.console.templates=/etc/prometheus/consoles'
    networks:
      - monitoring

  grafana:
    image: grafana/grafana:latest
    container_name: grafana
    ports:
      - "3000:3000"
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=admin
    volumes:
      - grafana-storage:/var/lib/grafana
    networks:
      - monitoring
    depends_on:
      - prometheus

volumes:
  grafana-storage:

networks:
  monitoring:
    driver: bridge

10. 性能優(yōu)化

10.1 指標(biāo)收集優(yōu)化

package com.springboot.admin.optimization;

import io.micrometer.core.instrument.config.MeterFilter;
import io.micrometer.core.instrument.distribution.DistributionStatisticConfig;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

@Configuration
public class MetricsOptimizationConfig {
    
    @Bean
    public MeterFilter metricsFilter() {
        return MeterFilter.maximumAllowableMetrics(1000)
            .andThen(MeterFilter.denyUnless(meter -> 
                meter.getName().startsWith("http.") || 
                meter.getName().startsWith("jvm.") ||
                meter.getName().startsWith("system.")
            ));
    }
    
    @Bean
    public MeterFilter distributionConfigFilter() {
        return new MeterFilter() {
            @Override
            public DistributionStatisticConfig configure(io.micrometer.core.instrument.Meter.Id id, 
                                                        DistributionStatisticConfig config) {
                if (id.getName().startsWith("http.server.requests")) {
                    return DistributionStatisticConfig.builder()
                        .percentiles(0.5, 0.95, 0.99)
                        .build()
                        .merge(config);
                }
                return config;
            }
        };
    }
}

11. 總結(jié)

本文詳細(xì)介紹了Spring Boot Admin與Prometheus的集成監(jiān)控方案，包括：

Prometheus基礎(chǔ)概念和架構(gòu)
集成配置和依賴管理
指標(biāo)收集與暴露
Prometheus配置和告警規(guī)則
數(shù)據(jù)導(dǎo)出與格式化
監(jiān)控面板集成
高級(jí)功能實(shí)現(xiàn)
部署配置方案
性能優(yōu)化策略

通過合理的集成配置，可以構(gòu)建一個(gè)功能完善的微服務(wù)監(jiān)控體系，為系統(tǒng)運(yùn)維提供有力支持。

13. 參考資料

Prometheus GitHub: https://github.com/prometheus/prometheus
Micrometer GitHub: https://github.com/micrometer-metrics/micrometer
Spring Boot Admin GitHub: https://github.com/codecentric/spring-boot-admin

本文為CSDN博主「Spring Cloud技術(shù)棧」原創(chuàng)文章，轉(zhuǎn)載請(qǐng)附上原文出處鏈接和本聲明。

到此這篇關(guān)于SpringBoot Admin與Prometheus集成監(jiān)控的文章就介紹到這了,更多相關(guān)SpringBoot Prometheus監(jiān)控內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！

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SpringBoot Admin與Prometheus集成監(jiān)控

目錄

摘要

1. 引言

2. Prometheus基礎(chǔ)

2.1 Prometheus架構(gòu)

2.2 數(shù)據(jù)模型

3. 集成配置

3.1 依賴配置

3.2 應(yīng)用配置

4. 指標(biāo)收集與暴露

4.1 自定義指標(biāo)收集器

4.2 業(yè)務(wù)指標(biāo)收集

5. Prometheus配置

5.1 Prometheus配置文件

5.2 告警規(guī)則配置

6. 數(shù)據(jù)導(dǎo)出與格式化

6.1 自定義指標(biāo)格式化

6.2 指標(biāo)數(shù)據(jù)處理

7. 監(jiān)控面板集成

7.1 Grafana配置

7.2 監(jiān)控?cái)?shù)據(jù)API

8. 高級(jí)功能

8.1 指標(biāo)過濾與轉(zhuǎn)換

8.2 指標(biāo)聚合

9. 部署配置

9.1 Docker配置

9.2 Docker Compose配置

10. 性能優(yōu)化

10.1 指標(biāo)收集優(yōu)化

11. 總結(jié)

12. 擴(kuò)展閱讀

13. 參考資料

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SpringBoot Admin與Prometheus集成監(jiān)控

目錄

摘要

1. 引言

2. Prometheus基礎(chǔ)

2.1 Prometheus架構(gòu)

2.2 數(shù)據(jù)模型

3. 集成配置

3.1 依賴配置

3.2 應(yīng)用配置

4. 指標(biāo)收集與暴露

4.1 自定義指標(biāo)收集器

4.2 業(yè)務(wù)指標(biāo)收集

5. Prometheus配置

5.1 Prometheus配置文件

5.2 告警規(guī)則配置

6. 數(shù)據(jù)導(dǎo)出與格式化

6.1 自定義指標(biāo)格式化

6.2 指標(biāo)數(shù)據(jù)處理

7. 監(jiān)控面板集成

7.1 Grafana配置

7.2 監(jiān)控?cái)?shù)據(jù)API

8. 高級(jí)功能

8.1 指標(biāo)過濾與轉(zhuǎn)換

8.2 指標(biāo)聚合

9. 部署配置

9.1 Docker配置

9.2 Docker Compose配置

10. 性能優(yōu)化

10.1 指標(biāo)收集優(yōu)化

11. 總結(jié)

12. 擴(kuò)展閱讀

13. 參考資料

相關(guān)文章

最新評(píng)論

大家感興趣的內(nèi)容

最近更新的內(nèi)容

常用在線小工具

国产无遮挡裸体免费直播视频,久久精品国产蜜臀av,动漫在线视频一区二区,欧亚日韩一区二区三区,久艹在线免费视频,国产精品美女网站免费,正在播放 97超级视频在线观看,斗破苍穹年番在线观看免费,51最新乱码中文字幕