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使用 Kafka、MongoDB 和 Maxwell's Daemon 构建 SQL 数据库审计系统 #8103

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joyking7
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译文翻译完成,resolve #8010

@PassionPenguin
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@itcodes @lsvih ... https://www.infoq.cn/article/KuhboGV2zpeI00k1Rxwu

这玩意有中文站....

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2月5号发布的(摊手

Screen Shot 2021-02-28 at 10 46 26 AM

…MongoDB and Maxwell's Daemon.md to Building-an-SQL-Database-Audit-System-Using-Kafka,-MongoDB-and-Maxwell's-Daemon.md
…-system-using-kafka-mongodb-and-maxwells-daemon
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lsvih commented Feb 28, 2021

@joyking7 我直接在您的文件上改了哈

@lsvih lsvih merged commit 33a90fc into xitu:master Feb 28, 2021
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lsvih commented Feb 28, 2021

@joyking7 已经 merge 啦~ 快快麻溜发布到掘金然后给我发下链接,方便及时添加积分哟。

掘金翻译计划有自己的知乎专栏,你也可以投稿哈,推荐使用一个好用的插件
专栏地址:https://zhuanlan.zhihu.com/juejinfanyi

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ψ(`∇´)ψ @joyking7 @lsvih

* There are many open source tools, e.g [Maxwell’s Daemons](https://maxwells-daemon.io/), [Debezium](https://debezium.io/), to support these needs and with minimum infrastructure and time requirements. 
* Maxwell’s daemons can read SQL bin logs and send the events to various producers such as [Kafka](https://kafka.apache.org/), [Amazon Kinesis](https://aws.amazon.com/kinesis/), [SQS](https://aws.amazon.com/sqs/), [Rabbit MQ](https://www.rabbitmq.com/).
* The bin log generated from SQL dbs must be in ROW based format for the whole setup to work
* 审计日志系统的用处远不止存储数据用于审计目的。除了合规性和安全性目的之外,它还能被市场营销团队使用,便于锁定目标用户,也可以用来生成关键的告警。
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* 审计日志系统的用处远不止存储数据用于审计目的。除了合规性和安全性目的之外,它还能被市场营销团队使用,便于锁定目标用户,也可以用来生成关键的告警。
* 审计日志系统的用处远不止存储数据用于审计目的。除了合规性和安全性目的之外,它还能被市场营销团队使用,便于锁定目标用户,也可以用来生成关键的告警。

* Maxwell’s daemons can read SQL bin logs and send the events to various producers such as [Kafka](https://kafka.apache.org/), [Amazon Kinesis](https://aws.amazon.com/kinesis/), [SQS](https://aws.amazon.com/sqs/), [Rabbit MQ](https://www.rabbitmq.com/).
* The bin log generated from SQL dbs must be in ROW based format for the whole setup to work
* 审计日志系统的用处远不止存储数据用于审计目的。除了合规性和安全性目的之外,它还能被市场营销团队使用,便于锁定目标用户,也可以用来生成关键的告警。
* 数据库内置的审计日志功能可能并不够用,要处理所有用户场景,它肯定不是最佳选择。
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* 数据库内置的审计日志功能可能并不够用,要处理所有用户场景,它肯定不是最佳选择。
* 数据库内置的审计日志功能可能并不够用,并且对于需要处理所有用户场景的情况下,它肯定不是最佳选择。

* The bin log generated from SQL dbs must be in ROW based format for the whole setup to work
* 审计日志系统的用处远不止存储数据用于审计目的。除了合规性和安全性目的之外,它还能被市场营销团队使用,便于锁定目标用户,也可以用来生成关键的告警。
* 数据库内置的审计日志功能可能并不够用,要处理所有用户场景,它肯定不是最佳选择。
* 当前有许多开源工具,比如 [Maxwell's Daemons](https://maxwells-daemon.io/) 和 [Debezium](https://debezium.io/),它们能够以最少的基础设施和时间来支持这些需求。
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* 当前有许多开源工具,比如 [Maxwell's Daemons](https://maxwells-daemon.io/)[Debezium](https://debezium.io/)它们能够以最少的基础设施和时间来支持这些需求
* 当前有许多开源工具实现审计日志功能,比如说 [Maxwell's Daemons](https://maxwells-daemon.io/)[Debezium](https://debezium.io/)它们就能够以最少的代码和最短的时间来支持这些需求

这里的 infrastructure 怎么翻译好呢?

* 数据库内置的审计日志功能可能并不够用,要处理所有用户场景,它肯定不是最佳选择。
* 当前有许多开源工具,比如 [Maxwell's Daemons](https://maxwells-daemon.io/)[Debezium](https://debezium.io/),它们能够以最少的基础设施和时间来支持这些需求。
* Maxwell's Daemon 能够读取 SQL binlog 并将 binlog event 发送给各种生产者,比如 [Kafka](https://kafka.apache.org/)[Amazon Kinesis](https://aws.amazon.com/kinesis/)[SQS](https://aws.amazon.com/sqs/)[Rabbit MQ](https://www.rabbitmq.com/)
* SQL 数据库生成的 binlog 文件必须是 ROW 格式,这样整个配置才能正常工作。
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* SQL 数据库生成的 binlog 文件必须是 ROW 格式,这样整个配置才能正常工作。
* SQL 数据库生成的 binlog 文件必须是 ROW 格式,这样整个配置才能正常工作。

* 审计日志系统的用处远不止存储数据用于审计目的。除了合规性和安全性目的之外,它还能被市场营销团队使用,便于锁定目标用户,也可以用来生成关键的告警。
* 数据库内置的审计日志功能可能并不够用,要处理所有用户场景,它肯定不是最佳选择。
* 当前有许多开源工具,比如 [Maxwell's Daemons](https://maxwells-daemon.io/) 和 [Debezium](https://debezium.io/),它们能够以最少的基础设施和时间来支持这些需求。
* Maxwell's Daemon 能够读取 SQL binlog 并将 binlog event 发送给各种生产者,比如 [Kafka](https://kafka.apache.org/)、[Amazon Kinesis](https://aws.amazon.com/kinesis/)、[SQS](https://aws.amazon.com/sqs/)、[Rabbit MQ](https://www.rabbitmq.com/) 。
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* Maxwell's Daemon 能够读取 SQL binlog 并将 binlog event 发送给各种生产者,比如 [Kafka](https://kafka.apache.org/)[Amazon Kinesis](https://aws.amazon.com/kinesis/)[SQS](https://aws.amazon.com/sqs/)[Rabbit MQ](https://www.rabbitmq.com/)
* Maxwell's Daemon 能够读取 SQL binlog 并将 binlog event 发送给各种服务提供者,比如 [Kafka](https://kafka.apache.org/)[Amazon Kinesis](https://aws.amazon.com/kinesis/)[SQS](https://aws.amazon.com/sqs/)[Rabbit MQ](https://www.rabbitmq.com/)

producer => streaming data analyzer


Ok! So, you use a relational database to maintain your transactional data and you need to store the audit trail of certain data present in a few tables. If you are like most of the developers you would end up doing one of the following:
好的!假设你正在使用关系型数据库来维护你的事务型数据,并且你需要存储的某些数据的审计跟踪信息只出现在很少的表中。如果你像大多数开发人员那样做,那么最终所使用的方案可能如下所示:
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好的!假设你正在使用关系型数据库来维护你的事务型数据,并且你需要存储的某些数据的审计跟踪信息只出现在很少的表中。如果你像大多数开发人员那样做,那么最终所使用的方案可能如下所示:
那么现在!就让我们来假设你正在使用关系型数据库来维护你的事务型数据,并且你需要存储的某些数据的审计跟踪信息只出现在很少的表中。如果你像大多数开发人员那样做,那么最终所使用的方案可能如下所示:


_Important Note: This system will work only when you are using a MySQL DB with [binlog logging format](https://dev.mysql.com/doc/refman/5.7/en/binary-log-formats.html) that is ROW based._
> 重要提示:本系统只适用于使用 MySQL 数据库的情况,并且是使用基于 ROW 格式的 [binlog 日志模式](https://dev.mysql.com/doc/refman/5.7/en/binary-log-formats.html)
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> 重要提示:本系统只适用于使用 MySQL 数据库的情况,并且是使用基于 ROW 格式的 [binlog 日志模式](https://dev.mysql.com/doc/refman/5.7/en/binary-log-formats.html)
> 重要提示:本系统只适用于使用 MySQL 数据库的情况,并且使用的是基于 ROW 格式的 [binlog 日志模式](https://dev.mysql.com/doc/refman/5.7/en/binary-log-formats.html)


About the Author
----------------
**Vishal Sinha** 是一位充满激情的技术专业,对分布式计算和大型可扩展系统有着专业的知识和浓厚的兴趣,他目前在一家领先的印度独角兽公司担任技术总监。在 16 年多的软件行业生涯中,他曾在多家跨国公司和初创公司工作,开发过各种大型可扩展系统,并带领过一个由许多软件工程师组成的团队,他十分享受解决复杂问题及尝试各种新技术。
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成分残缺了


The system described in this article works well in the live deployment and provides us an additional data source for user data but of course, there are some trade-offs that you must be aware of before adopting this architecture.
1. 基础设施成本。这样的设置需要额外的基础设施,数据会经过多次跳转,从数据库到 Kafka 再到另一个数据库,还可能存到备份中,这些都会增加基础设施的成本。
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基础设施这样翻译嘛(

```

### Kafka Consumer
### Kafka 消费者
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### Kafka 消费者
### Kafka 使用者

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阿这...

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lsvih commented Feb 28, 2021

@PassionPenguin 提前发个校对认领呀...好几次了= =

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producer & consumer,按照karfa的说法,应该是数据提供者和使用者

* Audit logs are written in a log file and the data isn’t easily searchable. For data analysis and auditing purposes, you want your audit data to be in a searchable format.
* Large audit archives consume critical database storage as it is stored on the same server as your DB.
* 成熟完善的审计日志插件一般只有企业版才提供,社区版可能会缺少这些插件。以 MySQL 为例,[审计日志插件](https://dev.mysql.com/doc/refman/5.7/en/audit-log.html) 只有企业版才能使用。值得一提的是,MySQL 社区版的用户仍然可以安装其他来自 MariaDB 或者 Percona 的审计日志插件绕过这个限制。
* 正如[慢查询日志对性能影响](http://blog.symedia.pl/2016/10/performance-impact-general-slow-query-log.html) 和[ mysql 日志性能影响](https://www.percona.com/blog/2009/02/10/impact-of-logging-on-mysql%E2%80%99s-performance)两篇文章讨论的一样,数据库级别的审计日志会给数据库服务器带来 10-20% 的额外开销。通常来讲,对于高负载的系统,我们可能想只对于慢查询启用审计日志,而不是对于所有查询开启。
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* 正如[慢查询日志对性能影响](http://blog.symedia.pl/2016/10/performance-impact-general-slow-query-log.html)[ mysql 日志性能影响](https://www.percona.com/blog/2009/02/10/impact-of-logging-on-mysql%E2%80%99s-performance)两篇文章讨论的一样,数据库级别的审计日志会给数据库服务器带来 10-20% 的额外开销。通常来讲,对于高负载的系统,我们可能想只对于慢查询启用审计日志,而不是对于所有查询开启。
* 正如[慢查询日志对性能影响](http://blog.symedia.pl/2016/10/performance-impact-general-slow-query-log.html)[MySQL 日志性能影响](https://www.percona.com/blog/2009/02/10/impact-of-logging-on-mysql%E2%80%99s-performance)两篇文章讨论的一样,数据库级别的审计日志会给数据库服务器带来 10-20% 的额外开销。通常来讲,对于高负载的系统,我们可能只想对于慢查询部分启用审计日志,而不是对于所有查询开启。

* Audit logging at the DB level causes 10-20% overhead on the database server as discussed [here](http://blog.symedia.pl/2016/10/performance-impact-general-slow-query-log.html) and [here](https://www.percona.com/blog/2009/02/10/impact-of-logging-on-mysql%E2%80%99s-performance). Generally, you may want to enable audit logging only for slow queries and not all the queries for a highly loaded system.
* Audit logs are written in a log file and the data isn’t easily searchable. For data analysis and auditing purposes, you want your audit data to be in a searchable format.
* Large audit archives consume critical database storage as it is stored on the same server as your DB.
* 成熟完善的审计日志插件一般只有企业版才提供,社区版可能会缺少这些插件。以 MySQL 为例,[审计日志插件](https://dev.mysql.com/doc/refman/5.7/en/audit-log.html) 只有企业版才能使用。值得一提的是,MySQL 社区版的用户仍然可以安装其他来自 MariaDB 或者 Percona 的审计日志插件绕过这个限制。
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* 成熟完善的审计日志插件一般只有企业版才提供,社区版可能会缺少这些插件。以 MySQL 为例,[审计日志插件](https://dev.mysql.com/doc/refman/5.7/en/audit-log.html) 只有企业版才能使用。值得一提的是,MySQL 社区版的用户仍然可以安装其他来自 MariaDB 或者 Percona 的审计日志插件绕过这个限制。
* 成熟完善的审计日志插件一般只有企业版才提供,社区版可能会缺少这些插件。以 MySQL 为例,[审计日志插件](https://dev.mysql.com/doc/refman/5.7/en/audit-log.html)只有企业版才能使用。当然值得一提的是,MySQL 社区版的用户仍然可以安装其他来自 MariaDB 或者 Percona 的审计日志插件绕过这个限制。

* Large audit archives consume critical database storage as it is stored on the same server as your DB.
* 成熟完善的审计日志插件一般只有企业版才提供,社区版可能会缺少这些插件。以 MySQL 为例,[审计日志插件](https://dev.mysql.com/doc/refman/5.7/en/audit-log.html) 只有企业版才能使用。值得一提的是,MySQL 社区版的用户仍然可以安装其他来自 MariaDB 或者 Percona 的审计日志插件绕过这个限制。
* 正如[慢查询日志对性能影响](http://blog.symedia.pl/2016/10/performance-impact-general-slow-query-log.html) 和[ mysql 日志性能影响](https://www.percona.com/blog/2009/02/10/impact-of-logging-on-mysql%E2%80%99s-performance)两篇文章讨论的一样,数据库级别的审计日志会给数据库服务器带来 10-20% 的额外开销。通常来讲,对于高负载的系统,我们可能想只对于慢查询启用审计日志,而不是对于所有查询开启。
* 审计日志会被写入到日志文件中,数据不易于搜索。为了数据分析和审计,我们想要让审计数据存储成可搜索的格式。
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* 审计日志会被写入到日志文件中,数据不易于搜索。为了数据分析和审计,我们想要让审计数据存储成可搜索的格式
* 审计日志会被写入到日志文件中,让这些数据不易于搜索。为了数据分析和审计,我们会更想要让审计数据存储成可搜索的格式


### Maxwell’s Daemon

[Maxwells Daemon](https://maxwells-daemon.io/) (MD) is an open-source project from [Zendesk](https://www.zendesk.com/) that reads MySQL binlogs and writes ROW updates as JSON to Kafka, Kinesis, or other streaming platforms. Maxwell has low operational overhead, requiring nothing but MySQL and a place to write as explained [here](https://maxwells-daemon.io/). In short, MD is a tool for Change-Data-Capture (CDC).
[Maxwell's Daemon](https://maxwells-daemon.io/)(MD)是一个来自 [Zendesk](https://www.zendesk.com/) 的开源项目,它会读取 MySQL binlog 并且将 ROW 的更新以 JSON 格式写入到 KafkaKinesis 或其他流平台。Maxwell 的运维成本很低,除了 MySQL 和一些在 [Maxwell's Daemon 文档](https://maxwells-daemon.io/)提到的需要写入数据的地方之外,就没有别的需求了。简而言之,MD 是一个数据变更捕获(Change-Data-Capture, CDC)的工具。
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[Maxwell's Daemon](https://maxwells-daemon.io/)(MD)是一个来自 [Zendesk](https://www.zendesk.com/) 的开源项目,它会读取 MySQL binlog 并且将 ROW 的更新以 JSON 格式写入到 Kafka、Kinesis 或其他流平台。Maxwell 的运维成本很低,除了 MySQL 和一些在 [Maxwell's Daemon 文档](https://maxwells-daemon.io/)提到的需要写入数据的地方之外,就没有别的需求了。简而言之,MD 是一个数据变更捕获(Change-Data-Capture, CDC)的工具。
[Maxwell's Daemon](https://maxwells-daemon.io/)(MD)是一个由 [Zendesk](https://www.zendesk.com/) 开发的开源项目,它会读取 MySQL binlog 并且将 ROW 的更新以 JSON 格式写入到 Kafka、Kinesis 或其他流平台。Maxwell 的运维成本很低,除了 MySQL 和一些在 [Maxwell's Daemon 文档](https://maxwells-daemon.io/)提到的需要写入数据的地方之外,就没有别的需求了。简而言之,MD 是一个数据变更捕获(Change-Data-Capture, CDC)的工具。

* Debezium can write data only in Kafka - at least that is the primary producer it supports. On the other hand, MD supports a variety of producers including Kafka. The list of producers MD supports is Kafka, [Kinesis](https://aws.amazon.com/kinesis/), [Google Cloud Pub/Sub](https://cloud.google.com/pubsub/docs/overview), [SQS](https://aws.amazon.com/sqs/), [Rabbit MQ](https://www.rabbitmq.com/), and Redis.
* MD provides options to write your own producer and configure with it. Details can be found [here](https://maxwells-daemon.io/producers/).
* The advantage of Debezium is that it can read Change Data from multiple sources such as [MySQL](https://www.mysql.com/), [MongoDB](https://www.mongodb.com/), [PostgreSQL](https://www.postgresql.org/), [SQL Server](https://www.microsoft.com/en-in/sql-server/), [Cassandra](http://cassandra.apache.org/), [DB2](https://www.ibm.com/in-en/products/db2-database), and [Oracle](https://www.oracle.com/index.html). They are quite active in adding new data sources. On the other hand, MD supports only the MySQL data source as of now.
* Debezium 只能写入数据到 Kafka,至少这是它所主要支持的 Producer。而 MD 支持包括 Kafka 在内的各类 Producer,它所支持的 Producer 包括 Kafka、[Kinesis](https://aws.amazon.com/kinesis/)、 [Google Cloud Pub/Sub](https://cloud.google.com/pubsub/docs/overview)、 [SQS](https://aws.amazon.com/sqs/)、[Rabbit MQ](https://www.rabbitmq.com/)和 Redis。
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* Debezium 只能写入数据到 Kafka,至少这是它所主要支持的 Producer。而 MD 支持包括 Kafka 在内的各类 Producer,它所支持的 Producer 包括 Kafka、[Kinesis](https://aws.amazon.com/kinesis/)[Google Cloud Pub/Sub](https://cloud.google.com/pubsub/docs/overview)[SQS](https://aws.amazon.com/sqs/)[Rabbit MQ](https://www.rabbitmq.com/)和 Redis。
* Debezium 只能写入数据到 Kafka,至少这是它所主要支持的平台。而 MD 支持包括 Kafka 在内的各类平台 —— 它所支持的平台包括 Kafka、[Kinesis](https://aws.amazon.com/kinesis/)[Google Cloud Pub/Sub](https://cloud.google.com/pubsub/docs/overview)[SQS](https://aws.amazon.com/sqs/)[Rabbit MQ](https://www.rabbitmq.com/)和 Redis。

* MD provides options to write your own producer and configure with it. Details can be found [here](https://maxwells-daemon.io/producers/).
* The advantage of Debezium is that it can read Change Data from multiple sources such as [MySQL](https://www.mysql.com/), [MongoDB](https://www.mongodb.com/), [PostgreSQL](https://www.postgresql.org/), [SQL Server](https://www.microsoft.com/en-in/sql-server/), [Cassandra](http://cassandra.apache.org/), [DB2](https://www.ibm.com/in-en/products/db2-database), and [Oracle](https://www.oracle.com/index.html). They are quite active in adding new data sources. On the other hand, MD supports only the MySQL data source as of now.
* Debezium 只能写入数据到 Kafka,至少这是它所主要支持的 Producer。而 MD 支持包括 Kafka 在内的各类 Producer,它所支持的 Producer 包括 Kafka、[Kinesis](https://aws.amazon.com/kinesis/)、 [Google Cloud Pub/Sub](https://cloud.google.com/pubsub/docs/overview)、 [SQS](https://aws.amazon.com/sqs/)、[Rabbit MQ](https://www.rabbitmq.com/)和 Redis。
* MD 允许用户编写自己的 Producer 并支持对其进行配置,详情参考 [Maxwell's Daemon Producers](https://maxwells-daemon.io/producers/) 文档。
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Suggested change
* MD 允许用户编写自己的 Producer 并支持对其进行配置,详情参考 [Maxwell's Daemon Producers](https://maxwells-daemon.io/producers/) 文档。
* MD 允许让我们构造自己的平台并对其进行配置,详情参考 [Maxwell's Daemon 平台](https://maxwells-daemon.io/producers/)文档。

* The advantage of Debezium is that it can read Change Data from multiple sources such as [MySQL](https://www.mysql.com/), [MongoDB](https://www.mongodb.com/), [PostgreSQL](https://www.postgresql.org/), [SQL Server](https://www.microsoft.com/en-in/sql-server/), [Cassandra](http://cassandra.apache.org/), [DB2](https://www.ibm.com/in-en/products/db2-database), and [Oracle](https://www.oracle.com/index.html). They are quite active in adding new data sources. On the other hand, MD supports only the MySQL data source as of now.
* Debezium 只能写入数据到 Kafka,至少这是它所主要支持的 Producer。而 MD 支持包括 Kafka 在内的各类 Producer,它所支持的 Producer 包括 Kafka[Kinesis](https://aws.amazon.com/kinesis/) [Google Cloud Pub/Sub](https://cloud.google.com/pubsub/docs/overview) [SQS](https://aws.amazon.com/sqs/)[Rabbit MQ](https://www.rabbitmq.com/)Redis
* MD 允许用户编写自己的 Producer 并支持对其进行配置,详情参考 [Maxwell's Daemon Producers](https://maxwells-daemon.io/producers/) 文档。
* Debezium 的优势在于它可以从多种数据源读取变化数据,比如 [MySQL](https://www.mysql.com/)[MongoDB](https://www.mongodb.com/)[PostgreSQL](https://www.postgresql.org/)[SQL Server](https://www.microsoft.com/en-in/sql-server/)[Cassandra](http://cassandra.apache.org/)[DB2](https://www.ibm.com/in-en/products/db2-database)[Oracle](https://www.oracle.com/index.html)。在新增数据源上,Debezium 十分灵活,而 MD 目前只支持 MySQL 数据源。
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* Debezium 的优势在于它可以从多种数据源读取变化数据,比如 [MySQL](https://www.mysql.com/)[MongoDB](https://www.mongodb.com/)[PostgreSQL](https://www.postgresql.org/)[SQL Server](https://www.microsoft.com/en-in/sql-server/)[Cassandra](http://cassandra.apache.org/)[DB2](https://www.ibm.com/in-en/products/db2-database)[Oracle](https://www.oracle.com/index.html)。在新增数据源上,Debezium 十分灵活,而 MD 目前只支持 MySQL 数据源。
* Debezium 的优势在于它可以从多种数据源读取变化数据,比如 [MySQL](https://www.mysql.com/)[MongoDB](https://www.mongodb.com/)[PostgreSQL](https://www.postgresql.org/)[SQL Server](https://www.microsoft.com/en-in/sql-server/)[Cassandra](http://cassandra.apache.org/)[DB2](https://www.ibm.com/in-en/products/db2-database)[Oracle](https://www.oracle.com/index.html)。在新增数据源上,Debezium 十分灵活,而 MD 目前只支持 MySQL 数据源。

@PassionPenguin
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@PassionPenguin 提前发个校对认领呀...好几次了= =

我看着一直没人校对,就感觉....

@lsvih
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lsvih commented Feb 28, 2021

@joyking7 得麻烦您参考校对者的意见再开个 PR 了 🤦

@PassionPenguin
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@joyking7 得麻烦您参考校对者的意见再开个 PR 了 🤦

@joyking7 抱歉.....

@itcodes
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itcodes commented Mar 2, 2021

@itcodes @lsvih ... https://www.infoq.cn/article/KuhboGV2zpeI00k1Rxwu

这玩意有中文站....

他们中英文站其实没啥关系。就是一个牌子。。

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使用 Kafka、MongoDB 和 Maxwell's Daemon 构建 SQL 数据库审计系统
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