当我们的服务器成千上万，当我们的模块上万成千，当我们的调用链路复杂如蜘蛛网时，我们突然发现一个小小的性能问题却不能快速定位到点！千万不要以为自己是神，当年那个觉得ELK日志分析系统多余的程序员已经被老板祭天！
废话有点多，今天我们要做的一件事非常简单，如何在一个多层调用的接口里快速查看它们的网络拓扑图并得到监控数据!
2、我们要注意什么 但凡一个合格的辅助，都不能抢主力的经济，不然会影响主力DPS输出----性能轻损耗
但凡一个合格的辅助，都应该跟随主力的脚步，而不能对主力指手画脚----业务非嵌入
但凡一个合格的辅助，都应该尽可能的实现简单轻负载----架构轻量级
3、zipkin实现原理 流程图：
流程图包含三个重要信息：
Trace
表示一条调用链路，是整个调用链路串联的唯一标识，将所有Span汇聚起来
Span
通俗的理解就是一次请求信息；它是链路跟踪的基本工作单元，一次链路调用(可以是RPC，DB等没有特定的限制)创建一个span
Annotation
用于定位一个request的开始和结束，cs/sr/ss/cr含有额外的信息，比如说时间点，当这个annotation被记录了，这个RPC也被认为完成了
cs：Client Start,表示客户端发起请求 ；一个span的开始；cf：Client Finish,表示客户端获取到服务端返回信息；一个span的结束ss：Server Start,表示服务端收到请求sf：Server Finish,表示服务端完成处理，并将结果发送给客户端ss-cs：网络延迟sf-ss：逻辑处理时间cf-cs：整个流程时间
Collector
接受或者收集各个应用传输的数据，跟踪一个Http请求的工作流程：
把当前调用链的Trace信息添加到HTTP Header里面记录当前调用的时间戳发送HTTP请求，把trace相关的header信息携带上调用结束之后，记录当前调用话费的时间然后把上面流程产生的 信息汇集成一个span，把这个span信息上传到zipkin的Collector模块下一个Http请求继续从第一步开始 4、落地实现 4.1 搭建zipkin server 持久化方式创建zipkin持久化数据库，当然，也可以不持久化，放内存中，不过我相信您如果不想被老板祭天也不会这么干！
SET NAMES utf8mb4;SET FOREIGN_KEY_CHECKS = 0;-- ------------------------------ Table structure for zipkin_annotations-- ----------------------------DROP TABLE IF EXISTS `zipkin_annotations`;CREATE TABLE `zipkin_annotations` ( `trace_id_high` bigint(20) NOT NULL DEFAULT 0 COMMENT 'If non zero, this means therntrace uses 128 bit traceIds instead of 64 bit', `trace_id` bigint(20) NOT NULL COMMENT 'coincides with zipkin_spans.trace_id', `span_id` bigint(20) NOT NULL COMMENT 'coincides with zipkin_spans.id', `a_key` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT 'BinaryAnnotation.key orrnAnnotation.value if type == -1', `a_value` blob NULL COMMENT 'BinaryAnnotation.value(), which must be smaller thanrn64KB', `a_type` int(11) NOT NULL COMMENT 'BinaryAnnotation.type() or -1 if Annotation', `a_timestamp` bigint(20) NULL DEFAULT NULL COMMENT 'Used to implement TTL; Annotation.timestamp orrnzipkin_spans.timestamp', `endpoint_ipv4` int(11) NULL DEFAULT NULL COMMENT 'Null when Binary/Annotation.endpoint is null', `endpoint_ipv6` binary(16) NULL DEFAULT NULL COMMENT 'Null when Binary/Annotation.endpoint isrnnull, or no IPv6 address', `endpoint_port` smallint(6) NULL DEFAULT NULL COMMENT 'Null when Binary/Annotation.endpoint isrnnull', `endpoint_service_name` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL COMMENT 'Null whenrnBinary/Annotation.endpoint is null', UNIQUE INDEX `trace_id_high`(`trace_id_high`, `trace_id`, `span_id`, `a_key`, `a_timestamp`) USING BTREE COMMENT 'Ignore insert on duplicate', INDEX `trace_id_high_2`(`trace_id_high`, `trace_id`, `span_id`) USING BTREE COMMENT 'for joining with zipkin_spans', INDEX `trace_id_high_3`(`trace_id_high`, `trace_id`) USING BTREE COMMENT 'for getTraces/ByIds', INDEX `endpoint_service_name`(`endpoint_service_name`) USING BTREE COMMENT 'forrngetTraces and getServiceNames', INDEX `a_type`(`a_type`) USING BTREE COMMENT 'for getTraces andrnautocomplete values', INDEX `a_key`(`a_key`) USING BTREE COMMENT 'for getTraces andrnautocomplete values', INDEX `trace_id`(`trace_id`, `span_id`, `a_key`) USING BTREE COMMENT 'for dependencies job') ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = COMPRESSED;-- ------------------------------ Table structure for zipkin_spans-- ----------------------------DROP TABLE IF EXISTS `zipkin_spans`;CREATE TABLE `zipkin_spans` ( `trace_id_high` bigint(20) NOT NULL DEFAULT 0 COMMENT 'If non zero, this means therntrace uses 128 bit traceIds instead of 64 bit', `trace_id` bigint(20) NOT NULL, `id` bigint(20) NOT NULL, `name` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL, `remote_service_name` varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL DEFAULT NULL, `parent_id` bigint(20) NULL DEFAULT NULL, `debug` bit(1) NULL DEFAULT NULL, `start_ts` bigint(20) NULL DEFAULT NULL COMMENT 'Span.timestamp(): epoch micros used for endTs queryrnand to implement TTL', `duration` bigint(20) NULL DEFAULT NULL COMMENT 'Span.duration(): micros used for minDuration andrnmaxDuration query', PRIMARY KEY (`trace_id_high`, `trace_id`, `id`) USING BTREE, INDEX `trace_id_high`(`trace_id_high`, `trace_id`) USING BTREE COMMENT 'forrngetTracesByIds', INDEX `name`(`name`) USING BTREE COMMENT 'for getTraces andrngetSpanNames', INDEX `remote_service_name`(`remote_service_name`) USING BTREE COMMENT 'for getTracesrnand getRemoteServiceNames', INDEX `start_ts`(`start_ts`) USING BTREE COMMENT 'for getTraces orderingrnand range') ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = COMPRESSED;-- ------------------------------ Records of zipkin_annotations-- ----------------------------set global innodb_large_prefix=1;set global innodb_file_format=BARRACUDA;-- ------------------------------ Table structure for zipkin_dependencies-- ----------------------------DROP TABLE IF EXISTS `zipkin_dependencies`;CREATE TABLE `zipkin_dependencies` ( `day` date NOT NULL, `parent` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL, `child` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL, `call_count` bigint(20) NULL DEFAULT NULL, `error_count` bigint(20) NULL DEFAULT NULL, PRIMARY KEY (`day`, `parent`, `child`) USING BTREE) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = COMPRESSED;SET FOREIGN_KEY_CHECKS = 1;
部署zipkin server使用Docker Compose部署zipkin server
zipkin: image: openzipkin/zipkin container_name: zipkin environment: - STORAGE_TYPE=mysql # Point the zipkin at the storage backend - MYSQL_DB=zipkin - MYSQL_USER=root - MYSQL_PASS=root - MYSQL_HOST=192.168.137.129 - MYSQL_TCP_PORT=3306 network_mode: host ports: # Port used for the Zipkin UI and HTTP Api - 9411:9411
配置好数据库，启动docker容器
通过web浏览器访问如下，表示搭建成功
非常简单，四个应用服务，调用深度为三层！
引入依赖每个zipkin客户端服务都引入如下依赖：
service1
package com.paratera.console.linktracking.controller;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.http.ResponseEntity;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController;import org.springframework.web.client.RestTemplate;@RestController@RequestMapping("/service1")public class ZipkinBraveController { @Autowired private RestTemplate restTemplate; @RequestMapping("/test") public String service1() throws Exception { //休眠100ms，模拟业务处理耗时 Thread.sleep(100); //调用service2服务 ResponseEntity
service2
package com.paratera.console.linktracking.controller;import org.springframework.beans.factory.annotation.Autowired;import org.springframework.http.ResponseEntity;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController;import org.springframework.web.client.RestTemplate;@RestController@RequestMapping("/service2")public class ZipkinBraveController { @Autowired private RestTemplate restTemplate; @RequestMapping("/test") public String service1() throws Exception { //休眠200ms，模拟业务处理 Thread.sleep(200); //调用service3服务 ResponseEntity
service3
package com.paratera.console.linktracking.controller;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController;@RestController@RequestMapping("/service3")public class ZipkinBraveController { @RequestMapping("/test") public String service1() throws Exception { //休眠3s，模拟性能耗点 Thread.sleep(3000); return "service3"; }}
service4
package com.paratera.console.linktracking.controller;import org.springframework.web.bind.annotation.RequestMapping;import org.springframework.web.bind.annotation.RestController;@RestController@RequestMapping("/service4")public class ZipkinBraveController { @RequestMapping("/test") public String service1() throws Exception { //休眠100ms，模拟业务耗时 Thread.sleep(100); return "service4"; }}
application.yml配置spring: application: name: service1 zipkin: base-url: http://192.168.137.129:9411 #zipkin server 的地址 sender: type: web #如果ClassPath里没有kafka, active MQ, 默认是web的方式 sleuth: sampler: probability: 1.0 #100%取样，生产环境应该低一点,用不着全部取出来server: port: 8081
四个服务工程除了端口不一样，其他都一样，zipkin监控serviceName不做配置，默认会使用Spring Application Name
附RestTemplate实例化代码@Beanpublic RestTemplate restTemplate(ClientHttpRequestFactory factory) { return new RestTemplate(factory);}@Beanpublic ClientHttpRequestFactory clientHttpRequestFactory() { SimpleClientHttpRequestFactory factory = new SimpleClientHttpRequestFactory(); factory.setConnectTimeout(5000); factory.setReadTimeout(5000); return factory;}
4.3 测试结果当我们访问http://localhost:8081/service1/test时，会生成一个完整的调用链路json数据，通过4.1搭建的zipkin server UI可以查看详情：
点击show查看各server请求详情：
进入service3详情：
可以自己通过CS,SS,CF,SF计算是网络延迟引起的问题还是逻辑处理引起的性能问题！