在开发环境中对业务问题的排查可以debugger计算时差等问题进行处理,如果架构复杂微服务嗲用众多,这样的方式就显得鸡肋。
如何快速发现问题?
如何判断故障影响范围?
如何梳理服务依赖以及依赖的合理性?
如何分析链路性能问题以及实现容量规划?
分布式链路追踪:
就是将一次分布式请求还原成调用链路,进行日志记录、性能监控并将一次分布式请求的调用情况集中展示。
比如各个服务节点上的耗时、请求具体到达那台机器上、每个服务节点的请求状态等等
Sleuth:
引入依赖,将依赖放入到父工程中
<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-sleuth</artifactId></dependency>
重启项目:通过网关访问创建订单,控制台输出一下内容,就完成了sleuth的集成
# 服务名称 traceId(链路id) spanId是否将链路的追踪结果输出到第三方
wdz-gateway,4eeae5ea48aa4abc,4eeae5ea48aa4abc,false
wdz-order, 4eeae5ea48aa4abc,7620d991a5dfc5bb,false
ZipKin集成
zipkin是twitter的开源项目,基于Google Dapper实现,它致力于收集服务的定时数据,以解决微服务架构中的延迟问题,包括数据的收集、存储、查找和展现
安装服务端:
可通过GITHUB 下载源码,进行打包使用
# get the latest sourcegit clone /openzipkin/zipkincd zipkin# Build the server and also make its dependencies./mvnw -DskipTests --also-make -pl zipkin-server clean install# Run the serverjava -jar ./zipkin-server/target/zipkin-server-*exec.jar
或者直接下载jar包运行
/maven2/io/zipkin/java/zipkin-server/2.12.9/zipkin-server-2.12.9-exec.jar
访问路径:
localhost:9411
集成客户端引入依赖:
<dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-zipkin</artifactId></dependency>
配置文件:
spring:zipkin:base-url: http://l27.0.0.1:9411/ # zipkin server 的请求地址discovery-client-enabled: false # 让nacos把它当成一个URL,而不要当做服务名sleuth:sampler:probability: 1.0 #采样百分比
重启服务通过网关访问product/order
能够很清楚的看到请求耗时链路等信息
持久化:
zipkin默认是将信息存入缓存中的,重启之后数据将会消失
mysql方式
CREATE TABLE IF NOT EXISTS zipkin_spans (`trace_id_high` BIGINT NOT NULL DEFAULT 0 COMMENT 'If non zero, this means the trace uses 128 bit traceIds instead of 64 bit',`trace_id` BIGINT NOT NULL,`id` BIGINT NOT NULL,`name` VARCHAR(255) NOT NULL,`parent_id` BIGINT,`debug` BIT(1),`start_ts` BIGINT COMMENT 'Span.timestamp(): epoch micros used for endTs query and to implement TTL',`duration` BIGINT COMMENT 'Span.duration(): micros used for minDuration and maxDuration query') ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;ALTER TABLE zipkin_spans ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `id`) COMMENT 'ignore insert on duplicate';ALTER TABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`, `id`) COMMENT 'for joining with zipkin_annotations';ALTER TABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`) COMMENT 'for getTracesByIds';ALTER TABLE zipkin_spans ADD INDEX(`name`) COMMENT 'for getTraces and getSpanNames';ALTER TABLE zipkin_spans ADD INDEX(`start_ts`) COMMENT 'for getTraces ordering and range';CREATE TABLE IF NOT EXISTS zipkin_annotations (`trace_id_high` BIGINT NOT NULL DEFAULT 0 COMMENT 'If non zero, this means the trace uses 128 bit traceIds instead of 64 bit',`trace_id` BIGINT NOT NULL COMMENT 'coincides with zipkin_spans.trace_id',`span_id` BIGINT NOT NULL COMMENT 'coincides with zipkin_spans.id',`a_key` VARCHAR(255) NOT NULL COMMENT 'BinaryAnnotation.key or Annotation.value if type == -1',`a_value` BLOB COMMENT 'BinaryAnnotation.value(), which must be smaller than 64KB',`a_type` INT NOT NULL COMMENT 'BinaryAnnotation.type() or -1 if Annotation',`a_timestamp` BIGINT COMMENT 'Used to implement TTL; Annotation.timestamp or zipkin_spans.timestamp',`endpoint_ipv4` INT COMMENT 'Null when Binary/Annotation.endpoint is null',`endpoint_ipv6` BINARY(16) COMMENT 'Null when Binary/Annotation.endpoint is null, or no IPv6 address',`endpoint_port` SMALLINT COMMENT 'Null when Binary/Annotation.endpoint is null',`endpoint_service_name` VARCHAR(255) COMMENT 'Null when Binary/Annotation.endpoint is null') ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;ALTER TABLE zipkin_annotations ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `span_id`, `a_key`, `a_timestamp`) COMMENT 'Ignore insert on duplicate';ALTER TABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`, `span_id`) COMMENT 'for joining with zipkin_spans';ALTER TABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`) COMMENT 'for getTraces/ByIds';ALTER TABLE zipkin_annotations ADD INDEX(`endpoint_service_name`) COMMENT 'for getTraces and getServiceNames';ALTER TABLE zipkin_annotations ADD INDEX(`a_type`) COMMENT 'for getTraces';ALTER TABLE zipkin_annotations ADD INDEX(`a_key`) COMMENT 'for getTraces';CREATE TABLE IF NOT EXISTS zipkin_dependencies (`day` DATE NOT NULL,`parent` VARCHAR(255) NOT NULL,`child` VARCHAR(255) NOT NULL,`call_count` BIGINT) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;ALTER TABLE zipkin_dependencies ADD UNIQUE KEY(`day`, `parent`, `child`);
启动命令:
java -jar zipkin.jar --STORAGE_TYPE=mysql --MYSQL_HOST=127.0.0.1 --MYSQL_TCP_PORT=3306 --MYSQL_DB=zipkin --MYSQL_USER=root --MYSQL_PASS=root
eleasticsearch方式
启动方式:
java -jar zipkin.jar --STORAGE_TYPE=elasticsearch --ES-HOST=localhost:9200
如果觉得《Sleuth + Zipkin 微服务分布式链路追踪》对你有帮助,请点赞、收藏,并留下你的观点哦!