[总结]全链路分布式追踪系统经验
微服务中台技术解析之全链路分布式追踪系统实践 用了3年CAT,这次我想选择SkyWalking,老板反手就是一个赞! 全链路监控神器Skywalking,就是这么秀!
Just One Pure ITer
微服务中台技术解析之全链路分布式追踪系统实践 用了3年CAT,这次我想选择SkyWalking,老板反手就是一个赞! 全链路监控神器Skywalking,就是这么秀!
40张图看懂SkyWalking分布式追踪系统原理及实践 不论是 CPU,内存,还是响应时间,使用 SkyWalking 带来的性能损耗几乎可以忽略不计。 接下来我们再来看 SkyWalking 与另一款业界比较知名的分布式追踪工具 Zipkin, Pinpoint 的对比(在采样率为 1 秒 1 个,线程数 500,请求总数为 5000 的情况下做的对比),可以看到在关键的响应时间上, Zipkin(117ms),PinPoint(201ms)远逊色于 SkyWalking(22ms)
现代微服务架构由于业务系统模型日趋复杂,分布式系统中需要一套链路追踪系统来帮助我们理解系统行为,明确服务间调用。最近作者请到了 Zipkin 项目的主要开发维护人员 Adrian Cole 来介绍有关 Zipkin 项目的细节内容,可以让大家了解到如何在分布式追踪系统中用好 Zipkin。Adrian 一直在从事云计算相关开源项目的开发,是开源项目 Apache jclouds 和 OpenFeign 的创始人。最近几年,他专注于分布式跟踪领域,是 OpenZipkin 项目的主要开发维护人员。Adrian 目前在 Pivotal Spring Cloud OSS 团队工作。在加入 Pivotal 之前,他还在 Twitter,Square,Netflix 工作过。
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