Metrics插件

插件是网关用来监控自身运行状态（JVM相关），请求的响应迟延，QPS、TPS等相关metrics。

异步或者同步的方式，在 Apache ShenYu 网关里面进行 metrics 埋点。
prometheus 服务端通过 http 请求来拉取 metrics，再使用 Grafana 展示。

在网关的 pom.xml 文件中添加 metrics 的依赖。

在网关的配置yaml文件中编辑如下内容：

shenyu:
  metrics:
    enabled: false  #设置为 true 表示开启
    name : prometheus 
    host: 127.0.0.1 #暴露的ip
    jmxConfig: #jmx配置
    props:
      jvm_enabled: true #开启jvm的监控指标

所有的JVM，线程，内存，等相关信息都会埋点，可以在 Grafana 面板中，新增一个 JVM 模块，则会完全展示具体请看：https://github.com/prometheus/jmx_exporter
另外还有如下自定义的 metrics

name	type	help
jmx_config_reload_success_total	counter	Number of times configuration have successfully been reloaded.
jmx_config_reload_failure_total	counter	Number of times configuration have failed to be reloaded.
jmx_scrape_duration_seconds	gauge	Time this JMX scrape took, in seconds.
jmx_scrape_error	gauge	Non-zero if this scrape failed.
jmx_scrape_cached_beans	gauge	Number of beans with their matching rule cached
jmx_scrape_duration_seconds	gauge	Time this JMX scrape took, in seconds.
jmx_scrape_error	gauge	Non-zero if this scrape failed.
jmx_scrape_cached_beans	gauge	Number of beans with their matching rule cached

jvm 指标

StandardExports

name	type	help
process_cpu_seconds_total	counter	Total user and system CPU time spent in seconds.
process_start_time_seconds	gauge	Start time of the process since unix epoch in seconds.
process_open_fds	gauge	Number of open file descriptors.
process_max_fds	gauge	Maximum number of open file descriptors.
process_virtual_memory_bytes	gauge	Virtual memory size in bytes.
process_resident_memory_bytes	gauge	Resident memory size in bytes.

MemoryPoolsExports

MemoryAllocationExports

name	type	labels	help
jvm_memory_pool_allocated_bytes_total	counter	{pool}	Total bytes allocated in a given JVM memory pool. Only updated after GC, not continuously.

BufferPoolsExports

name	type	labels	help
jvm_buffer_pool_used_bytes	gauge	{pool}	Used bytes of a given JVM buffer pool.
jvm_buffer_pool_capacity_bytes	gauge	{pool}	Bytes capacity of a given JVM buffer pool.
jvm_buffer_pool_used_buffers	gauge	{pool}	Used buffers of a given JVM buffer pool.

GarbageCollectorExports

ThreadExports

name	type	labels	help
jvm_threads_current	gauge		Current thread count of a JVM
jvm_threads_daemon	gauge		Daemon thread count of a JVM
jvm_threads_peak	gauge		Peak thread count of a JVM
jvm_threads_started_total	counter		Started thread count of a JVM
jvm_threads_deadlocked	gauge		Cycles of JVM-threads that are in deadlock waiting to acquire object monitors or ownable synchronizers
jvm_threads_deadlocked_monitor	gauge		Cycles of JVM-threads that are in deadlock waiting to acquire object monitors
jvm_threads_state	gauge	{state}	Current count of threads by state

ClassLoadingExports

name	type	help
jvm_classes_loaded	gauge	The number of classes that are currently loaded in the JVM
jvm_classes_loaded_total	counter	The total number of classes that have been loaded since the JVM has started execution
jvm_classes_unloaded_total	counter	The total number of classes that have been unloaded since the JVM has started execution

VersionInfoExports

用户需部署Prometheus 服务来采集

选择对应环境的安装
修改配置文件：prometheus.yml

配置完成之后，在 windows 下可以直接双击 prometheus.exe 启动即可，默认启动端口为 9090 ，访问 http://localhost:9090/ ，点击status->Targets，验证是否成功。

macos 环境下安装Prometheus

使用brew 安装 prometheus，安装完成后在homebrew下的 Cellar 文件夹中。

brew install prometheus

在prometheus.yml文件所在位置执行如下命令即可启动prometheus。

访问 http://localhost:9090/ 验证是否正常启动。

下面介绍如何安装 Grafana

安装 Grafana

解压进入 bin 目录然后双击 grafana-server.exe 运行访问 http://localhost:3000/?orgId=1 admin/admin 验证是否成功

macos环境下安装Grafana

使用brew 安装 grafana 。

brew install grafana

以服务方式启动grafana

访问 http://localhost:3000/ 验证是否正常启动。

配置数据源，选择prometheus，注意数据源名字为prometheus。

点击 Create - Import 输入dashboards 的面板json配置

最终自定义 Http 请求监控面板效果如下：