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本文深入探讨spring boot admin与prometheus的集成监控方案，包括指标收集、数据导出、可视化展示等关键技术点。通过详细的技术解析和实践示例，帮助开发者构建完整的微服务监控体系。
1. 引言
prometheus作为开源的系统监控和报警工具包，已经成为云原生监控的标准。spring boot admin结合prometheus可以提供更强大的监控能力。本文将详细介绍如何实现两者的集成。
2. prometheus基础
2.1 prometheus架构
prometheus生态系统包含以下组件：
- prometheus server：收集和存储指标数据
- client libraries：用于应用代码中暴露指标
- pushgateway：支持批处理作业的指标推送
- alertmanager：处理报警
- 可视化工具：如grafana
2.2 数据模型
prometheus使用时间序列数据模型，每个时间序列由指标名称和键值对标签标识。
3. 集成配置
3.1 依赖配置
<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 应用配置
# 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集成监控平台'
brand: '<img src="assets/img/icon-spring-boot-admin.svg"><span>prometheus集成监控平台</span>'
info:
app:
name: ${spring.application.name}
version: ${project.version}
description: spring boot admin与prometheus集成示例
4. 指标收集与暴露
4.1 自定义指标收集器
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) {
// 请求计数器
requestcounter = counter.builder("http_requests_total")
.description("total number of http requests")
.register(registry);
// 错误计数器
errorcounter = counter.builder("http_errors_total")
.description("total number of http errors")
.register(registry);
// 系统指标
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() {
// 获取系统cpu使用率
return math.random() * 100; // 模拟数据
}
private double getsystemmemoryusage() {
// 获取系统内存使用率
long totalmemory = runtime.getruntime().totalmemory();
long freememory = runtime.getruntime().freememory();
return (double) (totalmemory - freememory) / totalmemory * 100;
}
}
4.2 业务指标收集
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;
// 业务操作计时器
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 告警规则配置
# 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. 数据导出与格式化
6.1 自定义指标格式化
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) {
// 自定义指标格式化
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) {
// 添加自定义标签
if (id.getname().startswith("http.")) {
return id.withtags(io.micrometer.core.instrument.tag.of("application", "admin-server"));
}
return id;
}
});
}
}
6.2 指标数据处理
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. 监控面板集成
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 监控数据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();
// 获取各种指标的摘要信息
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. 高级功能
8.1 指标过滤与转换
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 指标聚合
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 # 创建应用目录 run addgroup -s spring && adduser -s spring -g spring user spring:spring workdir /app # 复制应用文件 copy --chown=spring:spring target/admin-server-prometheus.jar app.jar # 暴露端口 expose 8022 # 启动命令 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. 性能优化
10.1 指标收集优化
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. 总结
本文详细介绍了spring boot admin与prometheus的集成监控方案，包括：
- prometheus基础概念和架构
- 集成配置和依赖管理
- 指标收集与暴露
- prometheus配置和告警规则
- 数据导出与格式化
- 监控面板集成
- 高级功能实现
- 部署配置方案
- 性能优化策略
通过合理的集成配置，可以构建一个功能完善的微服务监控体系，为系统运维提供有力支持。
12. 扩展阅读
13. 参考资料
- 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
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