Zipkin是一個分散式追蹤系統。它有助於收集解決微服務架構中延遲問題所需的時序資料。它管理這些資料的收集和查詢。Zipkin的設計基於Google Dapper論文。

應用程式用於向Zipkin報告時間資料。Zipkin使用者介面還提供了一個依賴關係圖，顯示每個應用程式有多少跟蹤請求。如果您正在解決延遲問題或錯誤問題，則可以根據應用程式，跟蹤長度，註釋或時間戳過濾或排序所有跟蹤。一旦選擇了一個跟蹤，您可以看到每個跨度所花費的總跟蹤時間的百分比，從而可以確定問題應用程式。

為什麼使用Zipkin

隨著業務越來越複雜，系統也隨之進行各種拆分，特別是隨著微服務架構和容器技術的興起，看似簡單的一個應用，後臺可能有幾十個甚至幾百個服務在支撐；一個前端的請求可能需要多次的服務呼叫最後才能完成；當請求變慢或者不可用時，我們無法得知是哪個後臺服務引起的，這時就需要解決如何快速定位服務故障點，Zipkin分散式跟蹤系統就能很好的解決這樣的問題。

三種啟動方式

docker 啟動

docker run -d -p 9411:9411 openzipkin/zipkin

java  啟動

curl -sSL https://zipkin.io/quickstart.sh | bash -s
java -jar zipkin.jar

springboot  啟動

依賴

<dependency>
   <groupId>io.zipkin.java</groupId>
   <artifactId>zipkin-server</artifactId>
</dependency>
<dependency>
 
   <groupId>io.zipkin.java</groupId>
   <artifactId>zipkin-autoconfigure-ui</artifactId>
</dependency>

預設記憶體儲存

新增mysql 儲存

<dependency>
   <groupId>io.zipkin.java</groupId>
   <artifactId>zipkin-autoconfigure-storage-mysql</artifactId>
</dependency>
 
<dependency>
   <groupId>mysql</groupId>
   <artifactId>mysql-connector-java</artifactId>
</dependency>
<dependency>
   <groupId>org.springframework.boot</groupId>
   <artifactId>spring-boot-starter-jdbc</artifactId>
</dependency>
<dependency>
   <groupId>com.zaxxer</groupId>
   <artifactId>HikariCP</artifactId>
</dependency>

#資料庫指令碼建立地址，當有多個是可使用[x]表示集合第幾個元素
spring.datasource.schema[0]=classpath:/sql/zipkin.sql
spring.datasource.name=zipkin
spring.datasource.driver-class-name=com.mysql.jdbc.Driver
spring.datasource.url=jdbc:mysql://local-pc-node1:3306/snjx?characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=false
spring.datasource.username=snjx
spring.datasource.password=kRqKjGw1s;RH
spring.datasource.type=com.zaxxer.hikari.HikariDataSource
spring.datasource.hikari.minimum-idle=5
spring.datasource.hikari.maximum-pool-size=15
spring.datasource.hikari.auto-commit=true
spring.datasource.hikari.idle-timeout=30000
spring.datasource.hikari.pool-name=DatebookHikariCP
spring.datasource.hikari.max-lifetime=1800000
spring.datasource.hikari.connection-timeout=30000
spring.datasource.hikari.connection-test-query=SELECT 1

zipkin.sql  檔案

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';
ALTER TABLE zipkin_annotations ADD INDEX(`trace_id`, `span_id`, `a_key`) COMMENT 'for dependencies job';
CREATE TABLE IF NOT EXISTS zipkin_dependencies (
  `day` DATE NOT NULL,
`parent` VARCHAR(255) NOT NULL,
`child` VARCHAR(255) NOT NULL,
`call_count` BIGINT,
`error_count` BIGINT
) ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;
ALTER TABLE zipkin_dependencies ADD UNIQUE KEY(`day`, `parent`, `child`);

client 端的配置

<dependency>
   <groupId>org.springframework.cloud</groupId>
   <artifactId>spring-cloud-starter-sleuth</artifactId>
</dependency>
<dependency>
   <groupId>org.springframework.cloud</groupId>
   <artifactId>spring-cloud-sleuth-zipkin</artifactId>
</dependency>

#zipkin取樣率，預設為0.1，改為1後全取樣，但是會降低介面呼叫效率
spring.sleuth.sampler.percentage=1.0
#服務鏈路追蹤
spring.zipkin.base-url=http://localhost:8867

spring.zipkin.base-url=http://localhost:8867  這個主意不需要新增/zipkin 字尾

啟動執行的結果圖

服務之間依賴呼叫關係圖

ps :  zikpin 還提供其他方式的存貯 如 Cassandra，Elasticsearch