Zipkin简介

Posted 2023-04-12

参考技术A Zipkin是一个分布式跟踪系统。它有助于收集解决服务架构中延迟问题所需的计时数据。特性包括此数据的收集和查找。

如果日志文件中有跟踪ID，则可以直接跳转到它。也可以根据服务、操作名称、标签、持续时间等属性进行查询。将为您总结一些有趣的数据，例如花费在服务上的时间百分比，以及操作是否失败。

Zipkin UI还提供了一个依赖关系图，显示通过每个应用程序的跟踪请求的数量。这有助于识别聚合行为，包括错误路径或对弃用服务的调用。

应用程序需要被“检测”，以向Zipkin报告跟踪数据。这通常意味着跟踪程序或检测库的配置。最流行的向Zipkin报告数据的方式是通过HTTP或Kafka，尽管还有很多其他的选择，如Apache ActiveMQ, gRPC和RabbitMQ。提供给UI的数据存储在内存中，或者通过Apache Cassandra或Elasticsearch等后端持久存储。

微服务之分布式跟踪系统（springboot+zipkin+mysql）

  通过上一节《微服务之分布式跟踪系统（springboot+zipkin）》我们简单熟悉了zipkin的使用，但是收集的数据都保存在内存中重启后数据丢失，不过zipkin的Storage除了内存，还有Cassandra、MYSQL、ElasticSearch。

二、zipkin的各种Storage配置简介

          zipkin存在一些公用的配置，同时存在一些私有的配置（详细信息地址为：https://github.com/openzipkin/zipkin/tree/master/zipkin-server#configuration-for-the-ui），此处不做配置说明的翻译（因为都比较简单易懂），其公用的配置如下所示：

 

1.  
   *`QUERY_PORT`: Listen port for the http api and web ui; Defaults to 9411
2.  
   *`QUERY_LOG_LEVEL`: Log level written to the console; Defaults to INFO
3.  
   *`QUERY_LOOKBACK`: How many milliseconds queries can look back from endTs;Defaults to 7 days
4.  
   *`STORAGE_TYPE`: SpanStore implementation: one of `mem`, `mysql`, `cassandra`,`elasticsearch`
5.  
   *`COLLECTOR_PORT`: Listen port for the scribe thrift api; Defaults to 9410
6.  
   *`COLLECTOR_SAMPLE_RATE`: Percentage of traces to retain, defaults to alwayssample (1.0).

 

（1）Cassandra Storage配置

 

1.  
   * `CASSANDRA_KEYSPACE`: The keyspace to use. Defaults to "zipkin".
2.  
   * `CASSANDRA_CONTACT_POINTS`: Comma separated list of hosts / ip addresses part of Cassandra cluster. Defaults to localhost
3.  
   * `CASSANDRA_LOCAL_DC`: Name of the datacenter that will be considered "local" for latency load balancing. When unset, load-balancing is round-robin.
4.  
   * `CASSANDRA_ENSURE_SCHEMA`: Ensuring cassandra has the latest schema. If enabled tries to execute scripts in the classpath prefixed with `cassandra-schema-cql3`. Defaults to true
5.  
   * `CASSANDRA_USERNAME` and `CASSANDRA_PASSWORD`: Cassandra authentication. Will throw an exception on startup if authentication fails. No default
6.  
   * `CASSANDRA_USE_SSL`: Requires `javax.net.ssl.trustStore` and `javax.net.ssl.trustStorePassword`, defaults to false.

（2）MySQL Storage配置

 

1.  
   * `MYSQL_DB`: The database to use. Defaults to "zipkin".
2.  
   * `MYSQL_USER` and `MYSQL_PASS`: MySQL authentication, which defaults to empty string.
3.  
   * `MYSQL_HOST`: Defaults to localhost
4.  
   * `MYSQL_TCP_PORT`: Defaults to 3306
5.  
   * `MYSQL_MAX_CONNECTIONS`: Maximum concurrent connections, defaults to 10
6.  
   * `MYSQL_USE_SSL`: Requires `javax.net.ssl.trustStore` and `javax.net.ssl.trustStorePassword`, defaults to false.

（3）Elasticsearch Storage配置

 

1.  
   * `ES_CLUSTER`: The name of the elasticsearch cluster to connect to. Defaults to "elasticsearch".
2.  
   * `ES_HOSTS`: A comma separated list of elasticsearch hostnodes to connect to. When in host:port
3.  
   format, they should use the transport port, not the http port. To use http, specify
4.  
   base urls, ex. http://host:9200. Defaults to "localhost:9300". When not using http,
5.  
   Only one of the hosts needs to be available to fetch the remaining nodes in the
6.  
   cluster. It is recommended to set this to all the master nodes of the cluster.
7.  
    
8.  
   If the http URL is an AWS-hosted elasticsearch installation (e.g.
9.  
   https://search-domain-xyzzy.us-west-2.es.amazonaws.com) then Zipkin will attempt to
10.  
    use the default AWS credential provider (env variables, system properties, config
11.  
    files, or ec2 profiles) to sign outbound requests to the cluster.
12.  
    * `ES_PIPELINE`: Only valid when the destination is Elasticsearch 5.x. Indicates the ingest
13.  
    pipeline used before spans are indexed. No default.
14.  
    * `ES_MAX_REQUESTS`: Only valid when the transport is http. Sets maximum in-flight requests from
15.  
    this process to any Elasticsearch host. Defaults to 64.
16.  
    * `ES_AWS_DOMAIN`: The name of the AWS-hosted elasticsearch domain to use. Supercedes any set
17.  
    `ES_HOSTS`. Triggers the same request signing behavior as with `ES_HOSTS`, but
18.  
    requires the additional IAM permission to describe the given domain.
19.  
    * `ES_AWS_REGION`: An optional override to the default region lookup to search for the domain
20.  
    given in `ES_AWS_DOMAIN`. Ignored if only `ES_HOSTS` is present.
21.  
    * `ES_INDEX`: The index prefix to use when generating daily index names. Defaults to zipkin.
22.  
    * `ES_DATE_SEPARATOR`: The date separator to use when generating daily index names. Defaults to ‘-‘.
23.  
    * `ES_INDEX_SHARDS`: The number of shards to split the index into. Each shard and its replicas
24.  
    are assigned to a machine in the cluster. Increasing the number of shards
25.  
    and machines in the cluster will improve read and write performance. Number
26.  
    of shards cannot be changed for existing indices, but new daily indices
27.  
    will pick up changes to the setting. Defaults to 5.

三、zipkin环境准备与启动

       在本节中，以MySQL为例进行说明，由于目前只是Mysql5.6和5.7进行测试过，所以本次我选择Mysql5.7版本。

（1）    初始化数据库

       安装好Mysql5.7后新建zipkin的数据库，然后执行下面的SQL语句新建表：

 

1.  
   CREATETABLE IF NOT EXISTS zipkin_spans (
2.  
   `trace_id_high` BIGINT NOT NULL DEFAULT 0COMMENT ‘If non zero, this means the trace uses 128 bit traceIds instead of 64bit‘,
3.  
   `trace_id` BIGINT NOT NULL,
4.  
   `id` BIGINT NOT NULL,
5.  
   `name` VARCHAR(255) NOT NULL,
6.  
   `parent_id` BIGINT,
7.  
   `debug` BIT(1),
8.  
   `start_ts` BIGINT COMMENT ‘Span.timestamp():epoch micros used for endTs query and to implement TTL‘,
9.  
   `duration` BIGINT COMMENT ‘Span.duration():micros used for minDuration and maxDuration query‘
10.  
    )ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;
11.  
     
12.  
    ALTERTABLE zipkin_spans ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `id`) COMMENT‘ignore insert on duplicate‘;
13.  
    ALTERTABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`, `id`) COMMENT ‘forjoining with zipkin_annotations‘;
14.  
    ALTERTABLE zipkin_spans ADD INDEX(`trace_id_high`, `trace_id`) COMMENT ‘forgetTracesByIds‘;
15.  
    ALTERTABLE zipkin_spans ADD INDEX(`name`) COMMENT ‘for getTraces and getSpanNames‘;
16.  
    ALTERTABLE zipkin_spans ADD INDEX(`start_ts`) COMMENT ‘for getTraces ordering andrange‘;
17.  
     
18.  
    CREATETABLE IF NOT EXISTS zipkin_annotations (
19.  
    `trace_id_high` BIGINT NOT NULL DEFAULT 0COMMENT ‘If non zero, this means the trace uses 128 bit traceIds instead of 64bit‘,
20.  
    `trace_id` BIGINT NOT NULL COMMENT ‘coincideswith zipkin_spans.trace_id‘,
21.  
    `span_id` BIGINT NOT NULL COMMENT ‘coincideswith zipkin_spans.id‘,
22.  
    `a_key` VARCHAR(255) NOT NULL COMMENT‘BinaryAnnotation.key or Annotation.value if type == -1‘,
23.  
    `a_value` BLOB COMMENT‘BinaryAnnotation.value(), which must be smaller than 64KB‘,
24.  
    `a_type` INT NOT NULL COMMENT‘BinaryAnnotation.type() or -1 if Annotation‘,
25.  
    `a_timestamp` BIGINT COMMENT ‘Used toimplement TTL; Annotation.timestamp or zipkin_spans.timestamp‘,
26.  
    `endpoint_ipv4` INT COMMENT ‘Null whenBinary/Annotation.endpoint is null‘,
27.  
    `endpoint_ipv6` BINARY(16) COMMENT ‘Null whenBinary/Annotation.endpoint is null, or no IPv6 address‘,
28.  
    `endpoint_port` SMALLINT COMMENT ‘Null whenBinary/Annotation.endpoint is null‘,
29.  
    `endpoint_service_name` VARCHAR(255) COMMENT‘Null when Binary/Annotation.endpoint is null‘
30.  
    )ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;
31.  
     
32.  
    ALTERTABLE zipkin_annotations ADD UNIQUE KEY(`trace_id_high`, `trace_id`, `span_id`,`a_key`, `a_timestamp`) COMMENT ‘Ignore insert on duplicate‘;
33.  
    ALTERTABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`, `span_id`)COMMENT ‘for joining with zipkin_spans‘;
34.  
    ALTERTABLE zipkin_annotations ADD INDEX(`trace_id_high`, `trace_id`) COMMENT ‘forgetTraces/ByIds‘;
35.  
    ALTERTABLE zipkin_annotations ADD INDEX(`endpoint_service_name`) COMMENT ‘forgetTraces and getServiceNames‘;
36.  
    ALTERTABLE zipkin_annotations ADD INDEX(`a_type`) COMMENT ‘for getTraces‘;
37.  
    ALTERTABLE zipkin_annotations ADD INDEX(`a_key`) COMMENT ‘for getTraces‘;
38.  
    ALTERTABLE zipkin_annotations ADD INDEX(`trace_id`, `span_id`, `a_key`) COMMENT ‘fordependencies job‘;
39.  
     
40.  
    CREATETABLE IF NOT EXISTS zipkin_dependencies (
41.  
    `day` DATE NOT NULL,
42.  
    `parent` VARCHAR(255) NOT NULL,
43.  
    `child` VARCHAR(255) NOT NULL,
44.  
    `call_count` BIGINT
45.  
    )ENGINE=InnoDB ROW_FORMAT=COMPRESSED CHARACTER SET=utf8 COLLATE utf8_general_ci;
46.  
     
47.  
    ALTERTABLE zipkin_dependencies ADD UNIQUE KEY(`day`, `parent`, `child`);

（2）    启动实例

       执行命令：java -jar zipkin-server-1.17.1-exec.jar --STORAGE_TYPE=mysql--MYSQL_DB=zipkin --MYSQL_USER=root --MYSQL_PASS=root --MYSQL_HOST=localhost--MYSQL_TCP_PORT=3306，启动成功如下图所示：

 

（3）    查看运行效果

       通过上图，我们发现zipkin使用springboot，并且启动的端口为9411，然后我们通过浏览器访问，效果如下：

 

四、分布式跟踪系统实践（springboot+zipkin+mysql）

 4.1场景设置与分析

      现在有一个服务A调用服务B，服务B又分别调用服务C和D，整个链路过程的关系图如下所示：

 

4.2 代码编写

      具体代码和上一节代码相同，源代码下载地址：https://github.com/dreamerkr/mircoservice.git文件夹springboot+zipkin下面。

 

4.3运行效果

 （1）分别启动每个服务，然后访问服务1，浏览器访问（http://localhost:8081/service1/test）

（2）输入zipkin地址，每次trace的列表

 

点击其中的trace，可以看trace的树形结构，包括每个服务所消耗的时间：

 

点击每个span可以获取延迟信息：

 

同时可以查看服务之间的依赖关系：

 

同时查看zipkin数据库表已经存在数据：