分布式环境系统监控

January 5, 2017
apm
microservice

分布式环境系统监控Zipkin&Pinpoint

Dapper

Zipkin

zipkin为分布式链路调用监控系统，聚合各业务系统调用延迟数据，达到链路调用监控跟踪。

architecture

slow service 如图，在复杂的调用链路中假设存在一条调用链路响应缓慢，如何定位其中延迟高的服务呢？

日志：通过分析调用链路上的每个服务日志得到结果
zipkin：使用zipkin的web UI可以一眼看出延迟高的服务

zipkin

如图所示，各业务系统在彼此调用时，将特定的跟踪消息传递至zipkin,zipkin在收集到跟踪信息后将其聚合处理、存储、展示等，用户可通过web UI方便获得网络延迟、调用链路、系统依赖等等。

zipkin

zipkin主要涉及四个组件 collector storage search web UI

Collector接收各service传输的数据
Cassandra作为Storage的一种，也可以是mysql等，默认存储在内存中，配置cassandra可以参考这里
Query负责查询Storage中存储的数据,提供简单的JSON API获取数据，主要提供给web UI使用
Web 提供简单的web界面

install

执行如下命令下载jar包

wget -O zipkin.jar 'https://search.maven.org/remote_content?g=io.zipkin.java&a=zipkin-server&v=LATEST&c=exec'

其为一个spring boot功能，直接运行jar

nohup java -jar zipkin.jar &

访问 http://ip:9411 web-ui

terminology

使用zipkin涉及几个概念

Span:基本工作单元，一次链路调用(可以是RPC，DB等没有特定的限制)创建一个span，通过一个64位ID标识它， span通过还有其他的数据，例如描述信息，时间戳，key-value对的(Annotation)tag信息，parent-id等,其中parent-id 可以表示span调用链路来源，通俗的理解span就是一次请求信息
Trace:类似于树结构的Span集合，表示一条调用链路，存在唯一标识
Annotation: 注解,用来记录请求特定事件相关信息(例如时间)，通常包含四个注解信息

cs - Client Start,表示客户端发起请求

sr - Server Receive,表示服务端收到请求

ss - Server Send,表示服务端完成处理，并将结果发送给客户端

cr - Client Received,表示客户端获取到服务端返回信息
BinaryAnnotation:提供一些额外信息，一般已key-value对出现

概念说完，来看下完整的调用链路 request chain

上图表示一请求链路，一条链路通过Trace Id唯一标识，Span标识发起的请求信息，各span通过parent id 关联起来，如图 tree-like

整个链路的依赖关系如下: dependency

完成链路调用的记录后，如何来计算调用的延迟呢，这就需要利用Annotation信息

annotation

sr-cs 得到请求发出延迟

ss-sr 得到服务端处理延迟

cr-cs 得到真个链路完成延迟

brave Usage

作为各调用链路，只需要负责将指定格式的数据发送给zipkin即可，利用brave可快捷完成操作。

首先导入jar包pom.xml

<parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>1.3.6.RELEASE</version>
    </parent>



    <!-- https://mvnrepository.com/artifact/io.zipkin.brave/brave-core -->
    <dependencies>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-aop</artifactId>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-actuator</artifactId>
        </dependency>

        <dependency>
            <groupId>io.zipkin.brave</groupId>
            <artifactId>brave-core</artifactId>
            <version>3.9.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/io.zipkin.brave/brave-http -->
        <dependency>
            <groupId>io.zipkin.brave</groupId>
            <artifactId>brave-http</artifactId>
            <version>3.9.0</version>
        </dependency>
        <dependency>
            <groupId>io.zipkin.brave</groupId>
            <artifactId>brave-spancollector-http</artifactId>
            <version>3.9.0</version>
        </dependency>
        <dependency>
            <groupId>io.zipkin.brave</groupId>
            <artifactId>brave-web-servlet-filter</artifactId>
            <version>3.9.0</version>
        </dependency>

        <dependency>
            <groupId>io.zipkin.brave</groupId>
            <artifactId>brave-okhttp</artifactId>
            <version>3.9.0</version>
        </dependency>

        <!-- https://mvnrepository.com/artifact/org.slf4j/slf4j-api -->
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.13</version>
        </dependency>
        <dependency>
            <groupId>org.apache.httpcomponents</groupId>
            <artifactId>httpclient</artifactId>
            <version>4.5.1</version>
        </dependency>

    </dependencies>

利用spring boot创建工程

Application.java

package com.lkl.zipkin;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

/**
 *
 * Created by liaokailin on 16/7/27.
 */
@SpringBootApplication
public class Application {


    public static void main(String[] args) {
        SpringApplication app = new SpringApplication(Application.class);
        app.run(args);


    }
}

建立controller对外提供服务

HomeController.java

RestController
@RequestMapping("/")
public class HomeController {

    @Autowired
    private OkHttpClient client;

    private  Random random = new Random();

    @RequestMapping("start")
    public String start() throws InterruptedException, IOException {
        int sleep= random.nextInt(100);
        TimeUnit.MILLISECONDS.sleep(sleep);
        Request request = new Request.Builder().url("http://localhost:9090/foo").get().build();
        Response response = client.newCall(request).execute();
        return " [service1 sleep " + sleep+" ms]" + response.body().toString();
    }

HomeController中利用OkHttpClient调用发起http请求。在每次发起请求时则需要通过brave记录Span信息，并异步传递给zipkin 作为被调用方(服务端)也同样需要完成以上操作.

ZipkinConfig.java


package com.lkl.zipkin.config;

import com.github.kristofa.brave.Brave;
import com.github.kristofa.brave.EmptySpanCollectorMetricsHandler;
import com.github.kristofa.brave.SpanCollector;
import com.github.kristofa.brave.http.DefaultSpanNameProvider;
import com.github.kristofa.brave.http.HttpSpanCollector;
import com.github.kristofa.brave.okhttp.BraveOkHttpRequestResponseInterceptor;
import com.github.kristofa.brave.servlet.BraveServletFilter;
import okhttp3.OkHttpClient;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

/**
 * Created by liaokailin on 16/7/27.
 */
@Configuration
public class ZipkinConfig {

    @Autowired
    private ZipkinProperties properties;


    @Bean
    public SpanCollector spanCollector() {
        HttpSpanCollector.Config config = HttpSpanCollector.Config.builder().connectTimeout(properties.getConnectTimeout()).readTimeout(properties.getReadTimeout())
                .compressionEnabled(properties.isCompressionEnabled()).flushInterval(properties.getFlushInterval()).build();
        return HttpSpanCollector.create(properties.getUrl(), config, new EmptySpanCollectorMetricsHandler());
    }


    @Bean
    public Brave brave(SpanCollector spanCollector){
        Brave.Builder builder = new Brave.Builder(properties.getServiceName());  //指定state
        builder.spanCollector(spanCollector);
        builder.traceSampler(Sampler.ALWAYS_SAMPLE);
        Brave brave = builder.build();
        return brave;
    }

    @Bean
    public BraveServletFilter braveServletFilter(Brave brave){
        BraveServletFilter filter = new BraveServletFilter(brave.serverRequestInterceptor(),brave.serverResponseInterceptor(),new DefaultSpanNameProvider());
        return filter;
    }

    @Bean
    public OkHttpClient okHttpClient(Brave brave){
        OkHttpClient client = new OkHttpClient.Builder()
                .addInterceptor(new BraveOkHttpRequestResponseInterceptor(brave.clientRequestInterceptor(), brave.clientResponseInterceptor(), new DefaultSpanNameProvider()))
                .build();
        return client;
    }
}

SpanCollector 配置收集器
Brave 各工具类的封装,其中builder.traceSampler(Sampler.ALWAYS_SAMPLE)设置采样比率，0-1之间的百分比
BraveServletFilter 作为拦截器，需要serverRequestInterceptor,serverResponseInterceptor 分别完成sr和ss操作
OkHttpClient 添加拦截器，需要clientRequestInterceptor,clientResponseInterceptor 分别完成cs和cr操作,该功能由 brave中的brave-okhttp模块提供，同样的道理如果需要记录数据库的延迟只要在数据库操作前后完成cs和cr即可，当然brave提供其封装。

以上还缺少一个配置信息ZipkinProperties.java

package com.lkl.zipkin.config;

import org.springframework.boot.context.properties.ConfigurationProperties;
import org.springframework.context.annotation.Configuration;

/**
 * Created by liaokailin on 16/7/28.
 */
@Configuration
@ConfigurationProperties(prefix = "com.zipkin")
public class ZipkinProperties {

    private String serviceName;

    private String url;

    private int connectTimeout;

    private int readTimeout;

    private int flushInterval;

    private boolean compressionEnabled;

    public String getUrl() {
        return url;
    }

    public void setUrl(String url) {
        this.url = url;
    }

    public int getConnectTimeout() {
        return connectTimeout;
    }

    public void setConnectTimeout(int connectTimeout) {
        this.connectTimeout = connectTimeout;
    }

    public int getReadTimeout() {
        return readTimeout;
    }

    public void setReadTimeout(int readTimeout) {
        this.readTimeout = readTimeout;
    }

    public int getFlushInterval() {
        return flushInterval;
    }

    public void setFlushInterval(int flushInterval) {
        this.flushInterval = flushInterval;
    }

    public boolean isCompressionEnabled() {
        return compressionEnabled;
    }

    public void setCompressionEnabled(boolean compressionEnabled) {
        this.compressionEnabled = compressionEnabled;
    }

    public String getServiceName() {
        return serviceName;
    }

    public void setServiceName(String serviceName) {
        this.serviceName = serviceName;
    }
}

则可以在配置文件application.properties中配置相关信息

com.zipkin.serviceName=service1
com.zipkin.url=http://110.173.14.57:9411
com.zipkin.connectTimeout=6000
com.zipkin.readTimeout=6000
com.zipkin.flushInterval=1
com.zipkin.compressionEnabled=true
server.port=8080

那么其中的service1即完成，同样的道理，修改配置文件(调整com.zipkin.serviceName,以及server.port)以及controller对应的方法构造若干服务

service1 中访问http://localhost:8080/start需要访问http://localhost:9090/foo,则构造server2提供该方法

server2配置

com.zipkin.serviceName=service2
com.zipkin.url=http://110.173.14.57:9411
com.zipkin.connectTimeout=6000
com.zipkin.readTimeout=6000
com.zipkin.flushInterval=1
com.zipkin.compressionEnabled=true


server.port=9090

controller方法

    @RequestMapping("foo")
    public String foo() throws InterruptedException, IOException {
        Random random = new Random();
        int sleep= random.nextInt(100);
        TimeUnit.MILLISECONDS.sleep(sleep);
        Request request = new Request.Builder().url("http://localhost:9091/bar").get().build();  //service3
        Response response = client.newCall(request).execute();
        String result = response.body().string();
        request = new Request.Builder().url("http://localhost:9092/tar").get().build();  //service4
        response = client.newCall(request).execute();
       result += response.body().string();
        return " [service2 sleep " + sleep+" ms]" + result;
    }

在server2中调用server3和server4中的方法

方法分别为

 @RequestMapping("bar")
    public String bar() throws InterruptedException, IOException {  //service3 method
        Random random = new Random();
        int sleep= random.nextInt(100);
        TimeUnit.MILLISECONDS.sleep(sleep);
        return " [service3 sleep " + sleep+" ms]";
    }

    @RequestMapping("tar")
    public String tar() throws InterruptedException, IOException { //service4 method
        Random random = new Random();
        int sleep= random.nextInt(1000);
        TimeUnit.MILLISECONDS.sleep(sleep);
        return " [service4 sleep " + sleep+" ms]";
    }

将工程修改后编译成jar形式

执行


nohup java -jar server4.jar &
nohup java -jar server3.jar &
nohup java -jar server2.jar &
nohup java -jar server1.jar &

访问http://localhost:8080/start后查看zipkin的web UI

chain

点击条目可以查看具体的延迟信息

times

服务之间的依赖为 dependency

brave In depth

以上完成了基本的操作，下面将从源码角度来看下brave的实现

brave如何装配应用，首先从SpanCollector来入手


 @Bean
    public SpanCollector spanCollector() {
        HttpSpanCollector.Config config = HttpSpanCollector.Config.builder().connectTimeout(properties.getConnectTimeout()).readTimeout(properties.getReadTimeout())
                .compressionEnabled(properties.isCompressionEnabled()).flushInterval(properties.getFlushInterval()).build();
        return HttpSpanCollector.create(properties.getUrl(), config, new EmptySpanCollectorMetricsHandler());
    }

从名称上看HttpSpanCollector是基于http的span收集器,因此超时配置是必须的，默认给出的超时时间较长，flushInterval表示span的传递间隔，实际为定时任务执行的间隔时间.

Brave Initialization

 @Bean
    public Brave brave(SpanCollector spanCollector){
        Brave.Builder builder = new Brave.Builder(properties.getServiceName());  //指定state
        builder.spanCollector(spanCollector);
        builder.traceSampler(Sampler.ALWAYS_SAMPLE);
        Brave brave = builder.build();
        return brave;
    }

包装了各种工具类

public Brave build() {
            return new Brave(this);
        }

创建一个Brave


private Brave(Builder builder) {
        serverTracer = ServerTracer.builder()
                .randomGenerator(builder.random)
                .spanCollector(builder.spanCollector)
                .state(builder.state)
                .traceSampler(builder.sampler).build();

        clientTracer = ClientTracer.builder()
                .randomGenerator(builder.random)
                .spanCollector(builder.spanCollector)
                .state(builder.state)
                .traceSampler(builder.sampler).build();

        localTracer = LocalTracer.builder()
                .randomGenerator(builder.random)
                .spanCollector(builder.spanCollector)
                .spanAndEndpoint(SpanAndEndpoint.LocalSpanAndEndpoint.create(builder.state))
                .traceSampler(builder.sampler).build();
        
        serverRequestInterceptor = new ServerRequestInterceptor(serverTracer);
        serverResponseInterceptor = new ServerResponseInterceptor(serverTracer);
        clientRequestInterceptor = new ClientRequestInterceptor(clientTracer);
        clientResponseInterceptor = new ClientResponseInterceptor(clientTracer);
        serverSpanAnnotationSubmitter = AnnotationSubmitter.create(SpanAndEndpoint.ServerSpanAndEndpoint.create(builder.state));
        serverSpanThreadBinder = new ServerSpanThreadBinder(builder.state);
        clientSpanThreadBinder = new ClientSpanThreadBinder(builder.state);
    }

封装了*Tracer,*Interceptor,*Binder等

其中 serverTracer当服务作为服务端时处理span信息，clientTracer当服务作为客户端时处理span信息

Servlet Filter

BraveServletFilter是http模块提供的拦截器功能，传递serverRequestInterceptor,serverResponseInterceptor,spanNameProvider等参数其中spanNameProvider表示如何处理span的名称，默认使用method名称,spring boot中申明的filter bean默认拦截所有请求

@Override
    public void doFilter(ServletRequest request, ServletResponse response, FilterChain filterChain) throws IOException, ServletException {

        String alreadyFilteredAttributeName = getAlreadyFilteredAttributeName();
        boolean hasAlreadyFilteredAttribute = request.getAttribute(alreadyFilteredAttributeName) != null;

        if (hasAlreadyFilteredAttribute) {
            // Proceed without invoking this filter...
            filterChain.doFilter(request, response);
        } else {

            final StatusExposingServletResponse statusExposingServletResponse = new StatusExposingServletResponse((HttpServletResponse) response);
            requestInterceptor.handle(new HttpServerRequestAdapter(new ServletHttpServerRequest((HttpServletRequest) request), spanNameProvider));

            try {
                filterChain.doFilter(request, statusExposingServletResponse);
            } finally {
                responseInterceptor.handle(new HttpServerResponseAdapter(new HttpResponse() {
                    @Override
                    public int getHttpStatusCode() {
                        return statusExposingServletResponse.getStatus();
                    }
                }));
            }
        }
    }

首先来看requestInterceptor.handle方法，


 public void handle(ServerRequestAdapter adapter) {
        serverTracer.clearCurrentSpan();
        final TraceData traceData = adapter.getTraceData();

        Boolean sample = traceData.getSample();
        if (sample != null && Boolean.FALSE.equals(sample)) {
            serverTracer.setStateNoTracing();
            LOGGER.fine("Received indication that we should NOT trace.");
        } else {
            if (traceData.getSpanId() != null) {
                LOGGER.fine("Received span information as part of request.");
                SpanId spanId = traceData.getSpanId();
                serverTracer.setStateCurrentTrace(spanId.traceId, spanId.spanId,
                        spanId.nullableParentId(), adapter.getSpanName());
            } else {
                LOGGER.fine("Received no span state.");
                serverTracer.setStateUnknown(adapter.getSpanName());
            }
            serverTracer.setServerReceived();
            for(KeyValueAnnotation annotation : adapter.requestAnnotations())
            {
                serverTracer.submitBinaryAnnotation(annotation.getKey(), annotation.getValue());
            }
        }
    }

其中serverTracer.clearCurrentSpan()清除当前线程上的span信息，调用ThreadLocalServerClientAndLocalSpanState中的


  @Override
    public void setCurrentServerSpan(final ServerSpan span) {
        if (span == null) {
            currentServerSpan.remove();
        } else {
            currentServerSpan.set(span);
        }
    }

currentServerSpan为ThreadLocal对象

private final static ThreadLocal<ServerSpan> currentServerSpan = new ThreadLocal<ServerSpan>() {

回到ServerRequestInterceptor#handle()方法中final TraceData traceData = adapter.getTraceData()

 @Override
    public TraceData getTraceData() {
        final String sampled = serverRequest.getHttpHeaderValue(BraveHttpHeaders.Sampled.getName());
        if (sampled != null) {
            if (sampled.equals("0") || sampled.toLowerCase().equals("false")) {
                return TraceData.builder().sample(false).build();
            } else {
                final String parentSpanId = serverRequest.getHttpHeaderValue(BraveHttpHeaders.ParentSpanId.getName());
                final String traceId = serverRequest.getHttpHeaderValue(BraveHttpHeaders.TraceId.getName());
                final String spanId = serverRequest.getHttpHeaderValue(BraveHttpHeaders.SpanId.getName());

                if (traceId != null && spanId != null) {
                    SpanId span = getSpanId(traceId, spanId, parentSpanId);
                    return TraceData.builder().sample(true).spanId(span).build();
                }
            }
        }
        return TraceData.builder().build();
    }

其中SpanId span = getSpanId(traceId, spanId, parentSpanId) 将构造一个SpanId对象

 private SpanId getSpanId(String traceId, String spanId, String parentSpanId) {
        return SpanId.builder()
            .traceId(convertToLong(traceId))
            .spanId(convertToLong(spanId))
            .parentId(parentSpanId == null ? null : convertToLong(parentSpanId)).build();
   }

将traceId,spanId,parentId关联起来，其中设置parentId方法为


public Builder parentId(@Nullable Long parentId) {
      if (parentId == null) {
        this.flags |= FLAG_IS_ROOT;
      } else {
        this.flags &= ~FLAG_IS_ROOT;
      }
      this.parentId = parentId;
      return this;
    }

如果parentId为空为根节点，则执行this.flags |= FLAG_IS_ROOT ,因此后续在判断节点是否为根节点时，只需要执行(flags & FLAG_IS_ROOT) == FLAG_IS_ROOT即可.

构造完SpanId后看

    serverTracer.setStateCurrentTrace(spanId.traceId, spanId.spanId,
                        spanId.nullableParentId(), adapter.getSpanName());

设置当前Span

 public void setStateCurrentTrace(long traceId, long spanId, @Nullable Long parentSpanId, @Nullable String name) {
        checkNotBlank(name, "Null or blank span name");
        spanAndEndpoint().state().setCurrentServerSpan(
            ServerSpan.create(traceId, spanId, parentSpanId, name));
    }

ServerSpan.create创建Span信息


 static ServerSpan create(long traceId, long spanId, @Nullable Long parentSpanId, String name) {
        Span span = new Span();
        span.setTrace_id(traceId);
        span.setId(spanId);
        if (parentSpanId != null) {
            span.setParent_id(parentSpanId);
        }
        span.setName(name);
        return create(span, true);
    }

构造了一个包含Span信息的AutoValue_ServerSpan对象

通过setCurrentServerSpan设置到当前线程上

继续看serverTracer.setServerReceived()方法

public void setServerReceived() {
        submitStartAnnotation(zipkinCoreConstants.SERVER_RECV);
    }

为当前请求设置了server received event(sr)


void submitStartAnnotation(String annotationName) {
        Span span = spanAndEndpoint().span();
        if (span != null) {
            Annotation annotation = Annotation.create(
                currentTimeMicroseconds(),
                annotationName,
                spanAndEndpoint().endpoint()
            );
            synchronized (span) {
                span.setTimestamp(annotation.timestamp);
                span.addToAnnotations(annotation);
            }
        }
    }

在这里为Span信息设置了Annotation信息,后续的

 for(KeyValueAnnotation annotation : adapter.requestAnnotations())
            {
                serverTracer.submitBinaryAnnotation(annotation.getKey(), annotation.getValue());
            }

设置了BinaryAnnotation信息，adapter.requestAnnotations()在构造HttpServerRequestAdapter时已完成

 @Override
    public Collection<KeyValueAnnotation> requestAnnotations() {
        KeyValueAnnotation uriAnnotation = KeyValueAnnotation.create(
                TraceKeys.HTTP_URL, serverRequest.getUri().toString());
        return Collections.singleton(uriAnnotation);
    }

以上将Span信息(包括sr)存储在当前线程中，处理完请求后接下来继续看BraveServletFilter#doFilter方法的finally部分，如何对响应处理


 responseInterceptor.handle(new HttpServerResponseAdapter(new HttpResponse() {
                    @Override  //获取http状态码
                    public int getHttpStatusCode() {
                        return statusExposingServletResponse.getStatus();
                    }
                }));

responseInterceptor.handle方法

 public void handle(ServerResponseAdapter adapter) {
        // We can submit this in any case. When server state is not set or
        // we should not trace this request nothing will happen.
        LOGGER.fine("Sending server send.");
        try {
            for(KeyValueAnnotation annotation : adapter.responseAnnotations())
            {
                serverTracer.submitBinaryAnnotation(annotation.getKey(), annotation.getValue());
            }
            serverTracer.setServerSend();
        } finally {
            serverTracer.clearCurrentSpan();
        }
    }

首先配置BinaryAnnotation信息，然后执行serverTracer.setServerSend,在finally中清除当前线程中的Span信息(不管前面是否清楚成功,最终都将执行该不走)，ThreadLocal中的数据要做到有始有终

看serverTracer.setServerSend()

public void setServerSend() {
        if (submitEndAnnotation(zipkinCoreConstants.SERVER_SEND, spanCollector())) {
            spanAndEndpoint().state().setCurrentServerSpan(null);
        }
    }

终于看到spanCollector收集器了，说明下面将看是收集Span信息,这里为ss注解


boolean submitEndAnnotation(String annotationName, SpanCollector spanCollector) {
        Span span = spanAndEndpoint().span();
        if (span == null) {
          return false;
        }
        Annotation annotation = Annotation.create(
            currentTimeMicroseconds(),
            annotationName,
            spanAndEndpoint().endpoint()
        );
        span.addToAnnotations(annotation);
        if (span.getTimestamp() != null) {
            span.setDuration(annotation.timestamp - span.getTimestamp());
        }
        spanCollector.collect(span);
        return true;
    }

首先获取当前线程中的Span信息，然后处理注解信息，通过annotation.timestamp - span.getTimestamp()计算延迟, 调用spanCollector.collect(span)进行收集Span信息，那么Span信息是同步收集的吗？肯定不是的，接着看

zipkin-span-collect-inherit

调用spanCollector.collect(span)则执行FlushingSpanCollector中的collect方法


@Override
  public void collect(Span span) {
    metrics.incrementAcceptedSpans(1);
    if (!pending.offer(span)) {
      metrics.incrementDroppedSpans(1);
    }
  }

首先进行的是metrics统计信息，可以自定义该SpanCollectorMetricsHandler信息收集各指标信息,利用如grafana等展示信息

pending.offer(span)将span信息存储在BlockingQueue中，然后通过定时任务去取出阻塞队列中的值，偷偷摸摸的上传span信息

定时任务利用了Flusher类来执行，在构造FlushingSpanCollector时构造了Flusher类


 static final class Flusher implements Runnable {
    final Flushable flushable;
    final ScheduledExecutorService scheduler = Executors.newScheduledThreadPool(1);

    Flusher(Flushable flushable, int flushInterval) {
      this.flushable = flushable;
      this.scheduler.scheduleWithFixedDelay(this, 0, flushInterval, SECONDS);
    }

    @Override
    public void run() {
      try {
        flushable.flush();
      } catch (IOException ignored) {
      }
    }
  }

创建了一个核心线程数为1的线程池，每间隔flushInterval秒执行一次Span信息上传，执行flush方法

@Override
  public void flush() {
    if (pending.isEmpty()) return;
    List<Span> drained = new ArrayList<Span>(pending.size());
    pending.drainTo(drained);
    if (drained.isEmpty()) return;
    int spanCount = drained.size();
    try {
      reportSpans(drained);
    } catch (IOException e) {
      metrics.incrementDroppedSpans(spanCount);
    } catch (RuntimeException e) {
      metrics.incrementDroppedSpans(spanCount);
    }
  }

首先将阻塞队列中的值全部取出存如集合中，最后调用reportSpans(List<Span> drained)抽象方法，该方法在AbstractSpanCollector得到覆写

@Override
  protected void reportSpans(List<Span> drained) throws IOException {
    byte[] encoded = codec.writeSpans(drained);
    sendSpans(encoded);
  }

转换成字节流后调用sendSpans抽象方法发送Span信息.

Pinpoint

翻译自 Pinpoint 的 github 首页内容

介绍

Pinpoint是一个开源的 APM (Application Performance Management/应用性能管理)工具，用于基于java的大规模分布式系统。

仿照 Google Dapper , Pinpoint 通过跟踪分布式应用之间的调用来提供解决方案，以帮助分析系统的总体结构和内部模块之间如何相互联系.

注：对于各个模块之间的通讯英文原文中用的是transaction一词，但是我觉得如果翻译为”事务”容易引起误解，所以替换为”交互”或者”调用”这种比较直白的字眼。

在使用上力图简单高效：

安装agent，不需要修改哪怕一行代码
最小化性能损失

概述

如今的服务通常由很多不同模块组成，他们之间相互调用并通过API调用外部服务。每个交互是如何被执行的通常是一个黑盒。Pinpoint跟踪这些模块之间的调用流并提供清晰的视图来定位问题区域和潜在瓶颈。

服务器地图(ServerMap)

通过可视化分布式系统的模块和他们之间的相互联系来理解系统拓扑。点击某个节点会展示这个模块的详情，比如它当前的状态和请求数量。
实时活动线程图表(Realtime Active Thread Chart)

实时监控应用内部的活动线程。
请求/应答分布图表(Request/Response Scatter Chart)

长期可视化请求数量和应答模式来定位潜在问题。通过在图表上拉拽可以选择请求查看更多的详细信息。
调用栈(CallStack)

在分布式环境中为每个调用生成代码级别的可视图，在单个视图中定位瓶颈和失败点。
巡查(Inspector)

查看应用上的其他详细信息，比如CPU使用率，内存/垃圾回收，TPS，和JVM参数。

架构

支持模块

JDK 6+
Tomcat 6/7/8, Jetty ⁸⁄₉
Spring, Spring Boot
Apache HTTP Client 3.x/4.x, JDK HttpConnector, GoogleHttpClient, OkHttpClient, NingAsyncHttpClient
Thrift Client, Thrift Service
MySQL, Oracle, MSSQL, CUBRID, DBCP, POSTGRESQL
Arcus, Memcached, Redis
iBATIS, MyBatis
gson, Jackson, Json Lib
log4j, Logback