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創(chuàng)新互聯(lián)服務項目包括金堂縣網(wǎng)站建設、金堂縣網(wǎng)站制作、金堂縣網(wǎng)頁制作以及金堂縣網(wǎng)絡營銷策劃等。多年來，我們專注于互聯(lián)網(wǎng)行業(yè)，利用自身積累的技術優(yōu)勢、行業(yè)經(jīng)驗、深度合作伙伴關系等，向廣大中小型企業(yè)、政府機構等提供互聯(lián)網(wǎng)行業(yè)的解決方案，金堂縣網(wǎng)站推廣取得了明顯的社會效益與經(jīng)濟效益。目前，我們服務的客戶以成都為中心已經(jīng)輻射到金堂縣省份的部分城市，未來相信會繼續(xù)擴大服務區(qū)域并繼續(xù)獲得客戶的支持與信任！
關于Actuator：
對Spring Boot監(jiān)控能力有過了解的小伙伴都應該知道Spring Boot Actuator這個子項目，它為應用提供了強大的監(jiān)控能力。從Spring Boot 2.x開始，Actuator將底層改為Micrometer，提供了更強、更靈活的監(jiān)控能力。Micrometer是一個監(jiān)控門面，可以類比成監(jiān)控界的 Slf4j 。借助Micrometer，應用能夠對接各種監(jiān)控系統(tǒng)，例如本文所要介紹的：Prometheus
關于Prometheus ：
Prometheus是一個由SoundCloud開發(fā)的開源系統(tǒng)監(jiān)控+告警+時序列數(shù)據(jù)庫(TSDB)，Prometheus大部分組件使用Go語言編寫，是Google BorgMon監(jiān)控系統(tǒng)的開源版本。目前在CNCF基金會托管，并已成功孵化。在開源社區(qū)Prometheus目前也是相當活躍，在性能上Prometheus也足夠支撐上萬臺規(guī)模的集群。
Prometheus的功能：
- 用度量名和鍵值對識別時間序列數(shù)據(jù)的多維數(shù)據(jù)模型
- 擁有靈活的查詢語言：PromQL
- 不依賴分布式存儲，單個服務器節(jié)點是自治的
- 通過基于HTTP的pull方式采集時序數(shù)據(jù)
- 可以通過中間網(wǎng)關進行時序列數(shù)據(jù)的推送
- 支持通過服務發(fā)現(xiàn)或者靜態(tài)配置來發(fā)現(xiàn)目標服務對象
- 支持多種多樣的圖表和界面展示，比如Grafana等
更多內容參考：官方文檔，GitHub倉庫
關于Grafana：
Grafana 是一款采用 GO 語言編寫的開源應用，支持跨平臺度量分析和可視化 + 告警?？梢酝ㄟ^將采集的數(shù)據(jù)查詢然后可視化地展示，并及時通知。Grafana 支持多種數(shù)據(jù)源和展示方式，總而言之是一款強大酷炫的監(jiān)控指標可視化工具。
更多內容參考：官方文檔，GitHub倉庫
本文的主要目的是實現(xiàn)微服務的監(jiān)控，簡單了解了上述工具的概念后，我們就來動手實踐一下。首先創(chuàng)建一個簡單的Spring Boot項目，其主要依賴如下：
org.springframework.boot
spring-boot-starter-web
org.springframework.boot
spring-boot-starter-actuator
io.micrometer
micrometer-registry-prometheus
Influx ，則將依賴改為 micrometer-registry-influx 即可。編輯項目配置：
server:
port: 9562
spring:
application:
# 指定應用名
name: prometheus-demo
management:
endpoints:
web:
exposure:
# 將 Actuator 的 /actuator/prometheus 端點暴露出來
include: 'prometheus'
metrics:
tags:
# 為指標設置一個Tag，這里設置為應用名，Tag是Prometheus提供的一種能力，從而實現(xiàn)更加靈活的篩選
application: ${spring.application.name}完成以上步驟后，進行一個簡單的測試，看看端點是否能正常返回監(jiān)控數(shù)據(jù)。啟動項目，訪問/actuator/prometheus端點。正常情況下會返回如下內容：
# HELP process_start_time_seconds Start time of the process since unix epoch.
# TYPE process_start_time_seconds gauge
process_start_time_seconds{application="prometheus-demo",} 1.577697308142E9
# HELP jvm_buffer_memory_used_bytes An estimate of the memory that the Java virtual machine is using for this buffer pool
# TYPE jvm_buffer_memory_used_bytes gauge
jvm_buffer_memory_used_bytes{application="prometheus-demo",id="mapped",} 0.0
jvm_buffer_memory_used_bytes{application="prometheus-demo",id="direct",} 16384.0
# HELP tomcat_sessions_expired_sessions_total
# TYPE tomcat_sessions_expired_sessions_total counter
tomcat_sessions_expired_sessions_total{application="prometheus-demo",} 0.0
# HELP jvm_gc_pause_seconds Time spent in GC pause
# TYPE jvm_gc_pause_seconds summary
jvm_gc_pause_seconds_count{action="end of minor GC",application="prometheus-demo",cause="Metadata GC Threshold",} 1.0
jvm_gc_pause_seconds_sum{action="end of minor GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.006
jvm_gc_pause_seconds_count{action="end of major GC",application="prometheus-demo",cause="Metadata GC Threshold",} 1.0
jvm_gc_pause_seconds_sum{action="end of major GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.032
jvm_gc_pause_seconds_count{action="end of minor GC",application="prometheus-demo",cause="Allocation Failure",} 1.0
jvm_gc_pause_seconds_sum{action="end of minor GC",application="prometheus-demo",cause="Allocation Failure",} 0.008
# HELP jvm_gc_pause_seconds_max Time spent in GC pause
# TYPE jvm_gc_pause_seconds_max gauge
jvm_gc_pause_seconds_max{action="end of minor GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.006
jvm_gc_pause_seconds_max{action="end of major GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.032
jvm_gc_pause_seconds_max{action="end of minor GC",application="prometheus-demo",cause="Allocation Failure",} 0.008
# HELP jvm_memory_used_bytes The amount of used memory
# TYPE jvm_memory_used_bytes gauge
jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 0.0
jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Old Gen",} 1.3801776E7
jvm_memory_used_bytes{application="prometheus-demo",area="nonheap",id="Metaspace",} 3.522832E7
jvm_memory_used_bytes{application="prometheus-demo",area="nonheap",id="Code Cache",} 6860800.0
jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Eden Space",} 1.9782928E7
jvm_memory_used_bytes{application="prometheus-demo",area="nonheap",id="Compressed Class Space",} 4825568.0
# HELP logback_events_total Number of error level events that made it to the logs
# TYPE logback_events_total counter
logback_events_total{application="prometheus-demo",level="info",} 7.0
logback_events_total{application="prometheus-demo",level="trace",} 0.0
logback_events_total{application="prometheus-demo",level="warn",} 0.0
logback_events_total{application="prometheus-demo",level="debug",} 0.0
logback_events_total{application="prometheus-demo",level="error",} 0.0
# HELP process_uptime_seconds The uptime of the Java virtual machine
# TYPE process_uptime_seconds gauge
process_uptime_seconds{application="prometheus-demo",} 30.499
# HELP jvm_buffer_count_buffers An estimate of the number of buffers in the pool
# TYPE jvm_buffer_count_buffers gauge
jvm_buffer_count_buffers{application="prometheus-demo",id="mapped",} 0.0
jvm_buffer_count_buffers{application="prometheus-demo",id="direct",} 2.0
# HELP system_cpu_count The number of processors available to the Java virtual machine
# TYPE system_cpu_count gauge
system_cpu_count{application="prometheus-demo",} 6.0
# HELP jvm_threads_peak_threads The peak live thread count since the Java virtual machine started or peak was reset
# TYPE jvm_threads_peak_threads gauge
jvm_threads_peak_threads{application="prometheus-demo",} 22.0
# HELP tomcat_sessions_alive_max_seconds
# TYPE tomcat_sessions_alive_max_seconds gauge
tomcat_sessions_alive_max_seconds{application="prometheus-demo",} 0.0
# HELP jvm_memory_committed_bytes The amount of memory in bytes that is committed for the Java virtual machine to use
# TYPE jvm_memory_committed_bytes gauge
jvm_memory_committed_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 1.5204352E7
jvm_memory_committed_bytes{application="prometheus-demo",area="heap",id="PS Old Gen",} 1.31596288E8
jvm_memory_committed_bytes{application="prometheus-demo",area="nonheap",id="Metaspace",} 3.7879808E7
jvm_memory_committed_bytes{application="prometheus-demo",area="nonheap",id="Code Cache",} 6881280.0
jvm_memory_committed_bytes{application="prometheus-demo",area="heap",id="PS Eden Space",} 1.76685056E8
jvm_memory_committed_bytes{application="prometheus-demo",area="nonheap",id="Compressed Class Space",} 5373952.0
# HELP jvm_buffer_total_capacity_bytes An estimate of the total capacity of the buffers in this pool
# TYPE jvm_buffer_total_capacity_bytes gauge
jvm_buffer_total_capacity_bytes{application="prometheus-demo",id="mapped",} 0.0
jvm_buffer_total_capacity_bytes{application="prometheus-demo",id="direct",} 16384.0
# HELP jvm_gc_live_data_size_bytes Size of old generation memory pool after a full GC
# TYPE jvm_gc_live_data_size_bytes gauge
jvm_gc_live_data_size_bytes{application="prometheus-demo",} 1.3801776E7
# HELP jvm_memory_max_bytes The maximum amount of memory in bytes that can be used for memory management
# TYPE jvm_memory_max_bytes gauge
jvm_memory_max_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 1.5204352E7
jvm_memory_max_bytes{application="prometheus-demo",area="heap",id="PS Old Gen",} 2.841116672E9
jvm_memory_max_bytes{application="prometheus-demo",area="nonheap",id="Metaspace",} -1.0
jvm_memory_max_bytes{application="prometheus-demo",area="nonheap",id="Code Cache",} 2.5165824E8
jvm_memory_max_bytes{application="prometheus-demo",area="heap",id="PS Eden Space",} 1.390411776E9
jvm_memory_max_bytes{application="prometheus-demo",area="nonheap",id="Compressed Class Space",} 1.073741824E9
# HELP jvm_threads_daemon_threads The current number of live daemon threads
# TYPE jvm_threads_daemon_threads gauge
jvm_threads_daemon_threads{application="prometheus-demo",} 18.0
# HELP jvm_threads_states_threads The current number of threads having NEW state
# TYPE jvm_threads_states_threads gauge
jvm_threads_states_threads{application="prometheus-demo",state="runnable",} 8.0
jvm_threads_states_threads{application="prometheus-demo",state="new",} 0.0
jvm_threads_states_threads{application="prometheus-demo",state="timed-waiting",} 2.0
jvm_threads_states_threads{application="prometheus-demo",state="blocked",} 0.0
jvm_threads_states_threads{application="prometheus-demo",state="waiting",} 12.0
jvm_threads_states_threads{application="prometheus-demo",state="terminated",} 0.0
# HELP jvm_gc_memory_promoted_bytes_total Count of positive increases in the size of the old generation memory pool before GC to after GC
# TYPE jvm_gc_memory_promoted_bytes_total counter
jvm_gc_memory_promoted_bytes_total{application="prometheus-demo",} 8296848.0
# HELP tomcat_sessions_active_max_sessions
# TYPE tomcat_sessions_active_max_sessions gauge
tomcat_sessions_active_max_sessions{application="prometheus-demo",} 0.0
# HELP tomcat_sessions_created_sessions_total
# TYPE tomcat_sessions_created_sessions_total counter
tomcat_sessions_created_sessions_total{application="prometheus-demo",} 0.0
# HELP jvm_gc_memory_allocated_bytes_total Incremented for an increase in the size of the young generation memory pool after one GC to before the next
# TYPE jvm_gc_memory_allocated_bytes_total counter
jvm_gc_memory_allocated_bytes_total{application="prometheus-demo",} 1.36924824E8
# HELP process_cpu_usage The "recent cpu usage" for the Java Virtual Machine process
# TYPE process_cpu_usage gauge
process_cpu_usage{application="prometheus-demo",} 0.10024585094452443
# HELP system_cpu_usage The "recent cpu usage" for the whole system
# TYPE system_cpu_usage gauge
system_cpu_usage{application="prometheus-demo",} 0.38661791030714154
# HELP tomcat_sessions_active_current_sessions
# TYPE tomcat_sessions_active_current_sessions gauge
tomcat_sessions_active_current_sessions{application="prometheus-demo",} 0.0
# HELP jvm_classes_loaded_classes The number of classes that are currently loaded in the Java virtual machine
# TYPE jvm_classes_loaded_classes gauge
jvm_classes_loaded_classes{application="prometheus-demo",} 7195.0
# HELP http_server_requests_seconds
# TYPE http_server_requests_seconds summary
http_server_requests_seconds_count{application="prometheus-demo",exception="None",method="GET",outcome="CLIENT_ERROR",status="404",uri="/**",} 1.0
http_server_requests_seconds_sum{application="prometheus-demo",exception="None",method="GET",outcome="CLIENT_ERROR",status="404",uri="/**",} 0.012429856
# HELP http_server_requests_seconds_max
# TYPE http_server_requests_seconds_max gauge
http_server_requests_seconds_max{application="prometheus-demo",exception="None",method="GET",outcome="CLIENT_ERROR",status="404",uri="/**",} 0.012429856
# HELP jvm_gc_max_data_size_bytes Max size of old generation memory pool
# TYPE jvm_gc_max_data_size_bytes gauge
jvm_gc_max_data_size_bytes{application="prometheus-demo",} 2.841116672E9
# HELP jvm_threads_live_threads The current number of live threads including both daemon and non-daemon threads
# TYPE jvm_threads_live_threads gauge
jvm_threads_live_threads{application="prometheus-demo",} 22.0
# HELP jvm_classes_unloaded_classes_total The total number of classes unloaded since the Java virtual machine has started execution
# TYPE jvm_classes_unloaded_classes_total counter
jvm_classes_unloaded_classes_total{application="prometheus-demo",} 1.0
# HELP tomcat_sessions_rejected_sessions_total
# TYPE tomcat_sessions_rejected_sessions_total counter
tomcat_sessions_rejected_sessions_total{application="prometheus-demo",} 0.0該端點返回的數(shù)據(jù)是Prometheus需要使用的。每一項都有相應的注釋解釋其含義，相信不難看懂。例如：
# HELP jvm_memory_used_bytes The amount of used memory
# TYPE jvm_memory_used_bytes gauge
jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 0.0表示：prometheus-demo 應用堆內存中的 PS Survivor Space 區(qū)域占用的空間是 0.0 個字節(jié)。
接下來就是需要在服務器上安裝Prometheus服務，用于從微服務暴露的監(jiān)控端點中采集監(jiān)控數(shù)據(jù)。為了簡單起見，我這里采用docker的安裝方式，其他安裝方式可以參考 官方安裝文檔。
首先為Prometheus準備一個配置文件：
[root@localhost ~]# mkdir /etc/prometheus
[root@localhost ~]# vim /etc/prometheus/prometheus.yml
scrape_configs:
# 任意寫，建議英文，不要包含特殊字符
- job_name: 'spring'
# 多久采集一次數(shù)據(jù)
scrape_interval: 15s
# 采集時的超時時間
scrape_timeout: 10s
# 采集的端點
metrics_path: '/actuator/prometheus'
# 被采集的服務地址，即微服務的ip及端口
static_configs:
- targets: ['192.168.1.252:9562']該配置文件的目的是讓Prometheus服務自動每隔15秒請求 http://192.168.1.252:9562/actuator/prometheus 。更多配置項參考：Prometheus Configuration官方文檔
最后通過docker啟動Prometheus服務，命令如下：
[root@localhost ~]# docker run -d -p 9090:9090 -v /etc/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus --config.file=/etc/prometheus/prometheus.yml啟動成功后，正常情況下訪問http://{ip}:9090，就可以看到Prometheus的首頁：
點擊 Insert metric at cursor ，即可選擇監(jiān)控指標；點擊 Graph ，即可讓指標以圖表方式展示；點擊Execute 按鈕，即可看到類似下圖的結果：.jpg)
功能說明：
Insert metric at cursor：選擇展示的指標Graph：讓指標以圖形展示Execute：繪制指標圖表信息Add Graph：繪制更多指標圖表上一小節(jié)我們已經(jīng)成功搭建了Prometheus服務，并簡單介紹了Prometheus自帶的監(jiān)控數(shù)據(jù)可視化界面，然而使用體驗并不好，功能也比較少。下面我們來集成Grafana實現(xiàn)更友好、更貼近生產(chǎn)的監(jiān)控數(shù)據(jù)可視化平臺。
同樣需要在服務器上安裝Grafana服務，為了簡單起見，我這里依舊采用docker的安裝方式。其他安裝方式可以參考 官方安裝文檔。
使用docker只需要一行命令就可以啟動Grafana，如下：
[root@localhost ~]# docker run -d -p 3000:3000 grafana/grafanaGrafana啟動成功后，訪問http://{ip}:3000/login進行登錄，默認賬戶密碼均為admin：
登錄成功后，首頁如下：
首先需要添加監(jiān)控數(shù)據(jù)的來源，點擊首頁中的Add data source ，即可看到類似如下的界面：
這里點擊Prometheus，即可看到類似如下界面，在這里配置Prometheus服務相關的信息：
保存成功后會有如下提示：
點擊導航欄上的 + 按鈕，并點擊Dashboard，將會看到類似如下的界面：.jpg)
點擊 Add Query ，即可看到類似如下的界面：.jpg)
在紅框標記的位置添加指標查詢，指標的取值詳見Spring Boot應用的 /actuator/prometheus 端點，例如jvm_memory_used_bytes 、jvm_threads_states_threads 、jvm_threads_live_threads 等。
Grafana會給你較好的提示，并且支持較為復雜的計算，例如聚合、求和、平均等。如果想要繪制多個線條，可點擊Add Query 按鈕。如上圖所示，筆者為圖表繪制了兩條線，分別代表daemon以及peak線程。
點擊下圖的按鈕，并填入Title，即可設置圖表標題：.jpg)
若需要為Dashboard添加新的圖表則點擊上圖中的左上角按鈕：
并按下圖步驟操作即可：.jpg)
如果需要保存該Dashboard，則點擊右上角的保存按鈕即可：
至此，我們已經(jīng)成功將Grafana與Prometheus集成，實現(xiàn)了較為豐富的圖表展示——將關心的監(jiān)控指標放置到Dashboard上，并且非常靈活！然而，這個配置的操作雖然不難，但還是挺費時間的。
那么是否有配置好的又強大、又通用、拿來即用的Dashboard呢？答案是肯定的！前往 Grafana Lab - Dashboards ，輸入關鍵詞即可搜索指定Dashboard：
如上圖所示，可以找到若干款以 Prometheus 作為數(shù)據(jù)源，支持Micrometer的Dashboard。下面，簡單演示一下如何使用 JVM(Micrometer) 這個Dashboard。點擊 JVM(Micrometer) 進入Dashboard詳情介紹頁，如下圖所示：
如圖已詳細描述了該Dashboard的特性、配置。其中的management.metrics.tags.application ，前面安裝Prometheus服務時已經(jīng)配置過了。該頁的右上角用紅框標注的 4701 是一個非常重要的數(shù)字，因為這是該Dashboard的id。
回到Grafana的首頁，我們來導入這個Dashboard，按下圖步驟操作：
輸入后即可看到類似如下的界面，選擇數(shù)據(jù)源，并點擊Import：
此時，即可看到類似如下的界面，我們常關心的指標該Dashboard均已支持：
在上方的選項欄中可以選擇查看不同的服務/應用：
此外，還有一些比較好用的Dashboard，可以自行了解一下這里就不贅述了：
