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金克木
2022-03-12
$滴滴(DIDI)$
难道中国私营企业就这么无足轻重?尤其是互联网公司,怎么就成作恶的了。这是怎么了,这么整是不是有点过分了。
金克木
2023-12-27
$DiDi Global Inc.(DIDIY)$
如果突破 30 日均线,第五浪形成,将会有超过第四浪顶点价格的 30% 以上的涨幅
金克木
2022-12-03
$DiDi Global Inc.(DIDIY)$
上架前的铺垫吧?要上架会才会逐步回归。下架一年多,总单量还能保持在70%,除去自己想调降的原因,还是有点儿厉害的。
金克木
05-10
$能链智电(NAAS)$
看来投资市场还是有客观性的。这么一家没有底线、没有道德的公司,数据造假、账务造假、编造业绩是一定存在的,内部混乱不堪、创始人素质低到水平线以下,离职率全中国找不出几个的公司。股价跌成这样,还是比较客观的。但其实还远不如此
金克木
2023-11-22
$DiDi Global Inc.(DIDIY)$
反常,感觉要出利好,莫名其妙的涨。
金克木
2022-12-07
$DiDi Global Inc.(DIDIY)$
这是什么情况?涨的这么稳
金克木
07-10
$DiDi Global Inc.(DIDIY)$
狗屎,一次下架,把滴滴吓丢了魂,连灵魂都没了。烂泥
金克木
2023-11-29
$美团-W(03690)$
最近自己开了个店,才深切的感受到美团有多么牛,整个中国的商户几乎被他绑架了,没有他几乎没有流量,而且支付、管账、等等都要用他的,流水也要提成。美团可真不是个送外卖的,原来全国的商户都在为美团打工。今天坚定的买入了美团。。。
金克木
2023-03-16
$DiDi Global Inc.(DIDIY)$
为什么呀???看不懂,滴滴自己现在账面上的现金都超过200亿美金,居然市值都不如自己的现金多[捂脸]
金克木
07-10
$DiDi Global Inc.(DIDIY)$
滴滴不是也有无人车吗?怎么人家涨,你怎么都是个跌呢?
金克木
2022-12-13
$DiDi Global Inc.(DIDIY)$
这就对了,还没上架呢,别TMD老涨,要不又要被搞。
金克木
2023-12-09
$能链智电(NAAS)$
这个公司确实烂的很,管理层没有底线,员工离职率奇高,基本没有业务沉淀,全靠喷。负福利。数据造假的可能性高。
金克木
2023-11-02
$DiDi Global Inc.(DIDIY)$
这么多大单,但不涨,为啥
金克木
2023-09-01
$DiDi Global Inc.(DIDIY)$
半死不活到什么时候
金克木
2023-04-11
$DiDi Global Inc.(DIDIY)$
像大多数股票一样,半死不活[捂脸] 这个词儿贴切不
金克木
2022-11-08
$DiDi Global Inc.(DIDIY)$
感觉有机构在建仓了
金克木
2021-07-21
风波会过去,进入好时机
抱歉,原内容已删除
金克木
2022-04-15
滴滴到底是得罪谁了
滴滴下架9个月,又一出行平台杀出
金克木
2021-07-16
其实这是好事儿,离上架不远了
七大国家部门入驻调查滴滴,这次股价还要跌多少?
去老虎APP查看更多动态
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日均线,第五浪形成,将会有超过第四浪顶点价格的 30% 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团队是我见过最烂的,没有之一","listText":"说的对,起码滴滴的 PR 团队是我见过最烂的,没有之一","text":"说的对,起码滴滴的 PR 团队是我见过最烂的,没有之一","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/251332396228832","repostId":"2390801832","repostType":2,"repost":{"id":"2390801832","kind":"highlight","pubTimestamp":1702256401,"share":"https://www.laohu8.com/m/news/2390801832?lang=&edition=full","pubTime":"2023-12-11 09:00","market":"hk","language":"zh","title":"互联网故障背后的草台班子们","url":"https://stock-news.laohu8.com/highlight/detail?id=2390801832","media":"瑞典马工©","summary":"老老实实补课,不要再吹牛X了","content":"<html><body><p label=\"大标题\">滴滴不专业的故障沟通</p><p>11月27日,滴滴出行出了故障,后续没有发布一个官方的时间线,没人知道故障是什么时候开始的和什么时候彻底恢复的。当时最为详细的故障时间线,是一家财经媒体发布的《滴滴崩溃原因找到了!并非网络攻击,而是底层系统软件故障》<sup>[1][2][3]</sup>。尽管和滴滴没有任何利益关系,我都感觉到一种从业者的行业羞耻感:“我这个行业怎么这么业余?还需要记者来帮我们整理时间线?”</p><p>滴滴第一次沟通和第二次沟通间隔八个小时,这段时间内,一个猜测是“滴滴被网络攻击了”成了最有说服力的解释,以至于第二天滴滴要专门澄清:“没有被攻击”。如果滴滴第一时间就坦诚地和客户沟通是技术原因,并且指出数据不受影响,可以减少很多混乱和恐慌。关于这一点,我建议滴滴团队学习一下Atlassian的故障沟通最佳实践<sup>[4]</sup>的如下部分:</p><blockquote><p>Regular updates during the incident </p></blockquote><p>在故障恢复后,滴滴用很含糊的词语把故障原因解释为:“底层系统软件发生故障”。利益相关方既不清楚这个故障软件是第三方的还是滴滴自研的,也不知道滴滴是否启动了对这个软件的替换/修复。只得到了一个空洞的无法验证的承诺:“深入开展技术风险隐患排查和升级工作”。</p><p label=\"大标题\">为了表演火中取栗,滴滴先把栗子扔进去</p><p>由于滴滴不披露,大家只能自行挖掘。滴滴10月17日发布的一篇技术分享文章《滴滴弹性云基于K8S的调度实践》被挖出来,大家特别摘抄出三个点:</p><blockquote><p>k8s 版本的升级:介绍到从 k8s 1.12 到 1.20 跨版本升级的方案。</p></blockquote><p>Kubernetes 1.12是2018年7月发布的,在2019年7月8日就终止支持了。<strong>也就是说,在2023年10月的时候,滴滴在生产环境使用一个社区已经废弃4年多的老版本</strong>。不论是看可靠性,还是看安全性,这都是非常草台班子的做法。</p><p>在五年没有升级版本的历史债务下,滴滴团队决定孤注一掷,直接从1.12升级到1.20。但是 Kubernetes Deprecation Policy<sup>[5]</sup>很清楚地说了Beta API有可能在三个小版本之后就被删除。一次性升8个版本,风险完全不可控,也完全没有必要。</p><blockquote><p>从方案落地以及成本角度最终选取了原地升级。</p><p>修改原生的kubelet实现,按hash值是否变化来决定是否重建容器的策略。</p></blockquote><p>在冒险跨版本升级的前提下,还进一步选择原地升级,断绝Plan B的可能性,是一个更加费解的策略。实际上Kubernetes集群的蓝绿升级非常成熟,出问题的时候也更容易挽救。原地升级除了可以节约几个机器资源之外,没有其他好处。而升级Node不重建容器的做法,极容易引入兼容性问题,给自己的安全/调试/性能都带来极大的困难。</p><blockquote><p>集群体量大,最大集群规模已经远远超出了社区推荐的5千个node上限,有问题的爆炸半径大。</p></blockquote><p>Kubernetes的多集群管理工具已经非常成熟了,而且滴滴其实有多集群,所以维护超大集群没有任何意义。作者自己也清楚“爆炸半径大”,那么合理的做法就是把集群拆成合理大小的,比如把两个一万节点的集群拆成十个两千节点的集群,管理成本没有增加,而运行风险和爆炸半径得到极大的降低。</p><p>这三个策略都有一致的特征:<strong>本来没有问题,但是滴滴硬是要跟社区的建议反着来,制造一些高风险的问题,然后用自己的各种杂耍技巧去踩钢丝。所谓的“有困难克服困难都要上,没困难创造困难也要上”。</strong></p><p>这不像是一个正规的工程团队的行为模式,更像是新加入公司的实习生想要一炮打响采取的策略。由于这种杂耍技巧很难改正,我们可以合理地质疑,这个定时炸弹目前是不是还在滴滴机房滴答作响?</p><p label=\"大标题\">阿里云摧毁客户信心</p><p>11月12日,阿里云出现了一次影响所有区域的全局大故障。作为云厂商的一哥,阿里云发布了详细的故障时间线<sup>[6]</sup>,但是发布的故障报告语焉不详,我建议大家参考冯若航的非官方复盘文章《我们能从阿里云史诗级故障中学到什么》,目前为止这篇文章是对这次故障最为权威的分析。</p><p>这个故障离谱的是,尽管阿里云一再宣称自己有多区域,但是显然他们的RAM没有做到区域的隔离。</p><p>这个故障还是对我个人的一巴掌。我和我的朋友王明松一直鼓吹大家使用IAM, 在《云原生王四条》<sup>[7]</sup>中,我们特意详述了使用IAM的Role特性。我在故障发生之前恰好发了几篇文章,试图帮助云厂商提高服务质量。</p><p>但是正如冯若航所说,“深度使用云厂商提供的AK/SK/IAM不仅会让自己陷入供应商锁定中,更是将自己暴露在云基础设施单点的问题里”,我不得不承认,在你无法确认云厂商能力之前,暂停使用RAM 是一个明智的工程决策。</p><p label=\"大标题\">草台班主的哀叹</p><p>HelloJava的主理人据说曾经是阿里最优秀的架构师之一。他撰文《稳定性,难的不是技术,而是》向大家讲解了一些可靠性的经验。但是,非常抱歉,我认为这篇文章恰好反映了阿里技术团队的非常业余的一面。</p><p>我对专家的期望是,他能推荐一个有效的可靠性模型,然后给出可以落地的工具推荐。实际上,作者只是零零碎碎分享一些私人经验,像个散文家一样想到哪里说到哪里,别说没有模型,连个结构都没有。</p><p>有些地方甚至有明显的错误。比如作者主张:</p><blockquote><p>不管什么情况,以保障代码能正常运转是最重要的。</p></blockquote><p>这是一个非常非常非常糟糕的建议。对于绝大多数业务来说,服务的可用性<span label=\"备注\">(Availability)</span>的优先级应该低于数据的完整性<span label=\"备注\">(Integrity)</span>。如果维持服务在线会导致数据泄露或者数据损毁,那么应该毫不犹豫地牺牲可靠性。这个很好理解,对大多数用户来说,一天不能上钉钉和丢失钉钉联系人之间,显然后者损失更大。</p><p>他下面这个建议本身是非常正确的,但是工程师可以用一个词语精炼地概括他的建议:追求故障平均修复时间<span label=\"备注\">(Mean Time To Recovery<sup>[8]</sup>)</span>。MTTR是一个有精确定义的概念,与之相关的概念还有MTBF以及SLO。</p><blockquote><p>在故障出现时尽快恢复,而不是解决故障,在保留一定的现场的基础上,尽快的恢复问题比查问题重要得多,例如大家很多时候看到最有效处理故障的方法可能是重启,有同城双活、异地多活的通常最有效的处理方法是切流量等。</p></blockquote><p>另外,作者使用稳定性这个词,是非常外行的。在工程学中,可靠性<span label=\"备注\">(Reliability)</span>是一个专业术语,国家标准GB3187-1982《可靠性基本名词术语及定义》把这一套术语都涵盖了。而稳定性<span label=\"备注\">(Stability)</span>则是计量系统的一个词汇,指一个衡器多次衡量同一个样品,应该输出一个稳定的值。淘宝用户或者特大号小编把这两个词汇搞混淆是可以原谅的,但是技术专家应该要知道这两者完全不是一回事。</p><p>作者在文章中号称可靠性其实“技术上真的没有那么难”,只不过:</p><blockquote><p>这意味着的是大量的投入,能不能在稳定性这件事上保持持续的一定的投入,甚至当成做业务功能实现必须的投入,这才是真正做好稳定性最难的。</p></blockquote><p>然后作者把可靠性的锅抛给了管理者,指责:</p><blockquote><p>很多做过稳定性这事的人都知道,做这个事情最麻烦的是很难被认可,做得好,不出问题,不懂的人不知道你做了什么,出了问题的时候觉得你到底做了什么</p></blockquote><p><strong>不客气地说,这是一种非常典型的大妈发牢骚。</strong>工程师都应该知道,一个工程项目的资源总是有限的,工程师的任务永远都是在给定时间和成本的多重限制下,满足既定的质量要求。如果一个目标需要“大量的投入”,那么决策者在衡量投入产出比之后,降低该目标,是非常正常的项目管理动作,没有任何值得抱怨的。</p><p>值得抱怨的是这两种情况:项目本来要求A级可靠性,但是最终依照C级可靠性施工。或者,项目只需要C级可靠性,却花费大量的资源用于追求A级可靠性。你把银行存款业务跑在一台树莓派上,属于前者。你把公司内部论坛在亚洲欧洲北美三个region部署,属于后者。两者都是不可取的。</p><p>那么依据项目的资源和需求,制定一个可行的<span label=\"备注\">(Feasible)</span>可靠性目标,是谁的责任呢?在其他行业,答案很简单,这属于可行性研究<span label=\"备注\">(Feasibility Study)</span>的一部分,也是一个非功能需求的技术问题,是工程团队的责任。机械工程师们和土木工程师们非常熟悉这个任务了。如果你在可靠性目标制定上有这么多牢骚,很可能问题不在于管理者,要么你制定的目标确实不合理,要么你能力有限,无法向利益相关人有力地证明目标的合理性。</p><p>一篇文章读下来,我的印象就是:这位阿里技术一哥可能是个聪明人,也有一些不错的经验,但是整体上来说,没有接受过正规工程培训,严重欠缺工程理论常识,以前走野路子可能做了一些项目,但是个人经验几乎不具备可复制性。这样薄弱的底子,写文章参与可靠性讨论的结果,正如评论区一位读者说的:</p><blockquote><p>好像什么都说了,又好像什么都没说。</p></blockquote><p label=\"大标题\">天生不良的教育欠缺</p><p>软件工程是一门工程学科,从业者首先是个工程师,其次才是个软件工程师/硬件工程师/Java工程师。但是很可惜,由于教育的缺失,很多顶着很高头衔的从业者,其实不能算现代工业的工程师,更像一群家庭作坊的手工业者。</p><p>可靠性工程作为一个非常成熟的工程学科,是机械工程/土木工程的必修课。中南大学土木工程学院本科生就被要求必修《工程结构可靠度》<sup>[9]</sup>:</p><blockquote><p>Reliability of Engineering Structures 课程简介:荷载是工程结构设计的一个重要方面,也是着手一项工程设计要解决的一个重要问题,而概率可靠度方法已成为各类工程结构<span label=\"备注\">(房屋、桥梁、地下建筑、道路等)</span>设计的理论基础。本课程全面、系统地介绍工程结构各类荷载的基本概念及其确定方法,以及结构可靠度分析与设计理论。</p></blockquote><p>作为成熟的工程学科,他们有专门的可靠性教材:</p><figure><p><img src=\"https://static.tigerbbs.com/7741b918fa224f56b006e5356120b6b5\"/></p></figure><p>作为对比,全国的软件工程系/计算机系还没看到给本科生开这门课程的,更不用说作为必修课。我翻了几本《软件工程》课本,没有一本覆盖了可靠性。</p><p><strong>当然,即使软件工程课程覆盖了可靠性理论,也不一定能触及学生。</strong>在上海交大计算机科学与技术系的课程表<sup>[10]</sup>中,《软件工程》竟然是选修课程。也就是说,一个优秀大学热门计算机专业的优秀毕业生,有可能会《移动互联网》或者《大数据处理》这些热门技能,但是很可能没有接受过最基本的工程教育。</p><p label=\"大标题\">后天不足的持续学习</p><p>尽管高等教育落后,但是工程界并没有自暴自弃,做了很多努力去提升从业者的可靠性能力。就以很多家庭主妇为了糊口落户而去参考的软件为例,可靠性是考试大纲中的一部分。</p><ul><li><p>系统的可靠性分析与设计</p></li><li><p>系统的故障模型和可靠性模型</p></li><li><p>系统的可靠性分析和可靠度计算</p></li><li><p>提高系统可靠性的措施</p></li><li><p>系统的故障对策和系统的备份与恢复</p></li></ul><p>国标GB/T29832 《系统与软件可靠性》有三个部分,虽然内容不一定及时更新,但是至少规定了一些基本术语和基本方法:</p><ul><li><p>第1部分:指标体系;</p></li><li><p>第2部分:度量方法;</p></li><li><p>第3部分:测试方法。</p></li></ul><p>如果偏好看书,教材也有很多,中英文的都有。如果你嫌弃软件可靠性开山鼻祖John D. Musa的Software Reliability Engineering: More Reliable Software Faster and Cheaper 2nd Edition是英文的,也可以读徐仁佐的《软件可靠性工程》<sup>[11]</sup>。</p><p>如果有从业者学习能力实在差,不能考试,也不愿意读标准,甚至读书都会头痛,行业也提供了很多视频,比如波兰nobl9公司的学习园地<sup>[12]</sup>就有大量的关于可靠性的音频视频材料。该公司还主办SLOConf会议<sup>[13]</sup>,免费提供很多可靠性演讲。</p><p>如果有人连音频视频都懒得看,我甚至可以找出可靠性的动画片来。但问题是,提供再多的材料,从业者会去学习吗?用我的朋友王明松的话说:“有些从业者的软件工程理论水平,连软考拿落户的家庭主妇都不如。”这一点我毫无异议,因为家庭主妇至少不会搞混稳定性和可靠性。</p><p label=\"大标题\">空洞承诺</p><p>如果一个行业的从业者既没有得到正规的工程教育,也没有得到妥善的在职教育,而是凭着朴素的常识处理工程问题,就像农民工凭着朴素的常识去工地搬砖一样,虽然也能在包工头的带领下修起高楼大厦,但是可靠性恐怕要大打折扣。</p><p>当故障过后,滴滴给出的空洞承诺:</p><blockquote><p>后续我们将深入开展技术风险隐患排查和升级工作,全面保障服务稳定性,尽最大努力避免类似事故再发生。</p></blockquote><p>这个承诺基于一个错误的假设:只要把现有的技术风险排查一遍,就可以全面保障服务稳定性了。但是用任何一个可靠性模型都会指出:<strong>预防故障只是可靠性的一部分工作,而技术风险也只是故障来源的一部分</strong>。</p><p>至少从本次故障来看,滴滴的故障中处理流程非常不规范不严谨。如果我们上面的猜想成立—鉴于滴滴没有公开复盘材料,上述猜想是目前最有解释力的—那么滴滴平时的基础设施技术选型的决策流程也有严重问题。单单只是排查技术风险隐患,恐怕不能提升滴滴的服务水平。</p><p>而阿里云给出的改进措施就更勉强了,几乎就是头痛医头,脚痛医脚:</p><blockquote><p>增加AK服务白名单生成结果的校验及告警拦截能力。</p><p>增加AK服务白名单更新的灰度验证逻辑,提前发现异常。</p><p>增加AK服务白名单的快速恢复能力。</p><p>加强云产品侧的联动恢复能力。</p></blockquote><p label=\"大标题\">建议</p><p>软件从业者在基本工程能力的欠缺,过去被高速增长的业务数据所掩盖,不被当成一个问题。但是潮水一旦落下,我们就看到一个又一个裸泳的屁股。对此,我们没有其他建议,只有一个:<strong>老老实实补课,不要再吹牛X了。</strong></p><p><span>参考资料:</span></p><p><span label=\"备注\">[1]http://www.leidacj.com/yuanchuang/show-36978.html</span></p><p><span label=\"备注\">[2]滴滴崩溃原因找到了!并非网络攻击 而是底层系统软件故障: http://www.leidacj.com/yuanchuang/show-36978.html</span></p><p><span label=\"备注\">[3]: http://www.leidacj.com/yuanchuang/show-36978.html</span></p><p><span label=\"备注\">[4]Atlassian的故障沟通最佳实践: https://www.atlassian.com/incident-management/incident-communication#:~:text=Part%202%3A%20Regular%20updates%20during%20the%20incident</span></p><p><span label=\"备注\">[5]Kubernetes Deprecation Policy: https://kubernetes.io/docs/reference/using-api/deprecation-policy/</span></p><p><span label=\"备注\">[6]阿里云发布了详细的故障时间线: https://status.aliyun.com/#/historyEvent</span></p><p><span label=\"备注\">[7]《云原生王四条》: https://github.com/lipingtababa/cloud-native-best-practices/blob/main/%E4%BA%91%E5%8E%9F%E7%94%9F%E7%8E%8B%E5%9B%9B%E6%9D%A1.md</span></p><p><span label=\"备注\">[8]Mean Time To Recovery: https://en.wikipedia.org/wiki/Mean_time_to_recovery</span></p><p><span label=\"备注\">[9]《工程结构可靠度》:https://civil.csu.edu.cn/bksjy/kcjs/kcjs.htm#:~:text=%E5%B7%A5%E7%A8%8B%E7%BB%93%E6%9E%84%E5%8F%AF%E9%9D%A0-,%E5%BA%A6,-%E8%8B%B1%E6%96%87%E5%90%8D%E7%A7%B0%EF%BC%9AReliability</span></p><p><span label=\"备注\">[10]上海交大计算机科学与技术系的课程表: https://bjwb.seiee.sjtu.edu.cn/bkjwb/info/13371.htm</span></p><p><span label=\"备注\">[11]《软件可靠性工程》: http://www.tup.com.cn/upload/books/yz/016476-01.pdf</span></p><p><span label=\"备注\">[12]波兰 nobl9 公司的学习园地: https://www.nobl9.com/explore/learning-center</span></p><p><span label=\"备注\">[13]SLOConf 会议: https://www.sloconf.com/speakers</span></p><p><span label=\"备注\">本文来自微信公众号:</span><span>瑞典马工(ID:cloudshotgun)</span><span>,作者:马工在瑞典</span></p></body></html>","source":"highlight_huxiu","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>互联网故障背后的草台班子们</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ 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margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 11px; color: #7E829C; margin: 0;line-height: 11px;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\n互联网故障背后的草台班子们\n</h2>\n\n<h4 class=\"meta\">\n\n\n2023-12-11 09:00 北京时间 <a href=https://www.huxiu.com/article/2389271.html><strong>瑞典马工©</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>滴滴不专业的故障沟通11月27日,滴滴出行出了故障,后续没有发布一个官方的时间线,没人知道故障是什么时候开始的和什么时候彻底恢复的。当时最为详细的故障时间线,是一家财经媒体发布的《滴滴崩溃原因找到了!并非网络攻击,而是底层系统软件故障》[1][2][3]。尽管和滴滴没有任何利益关系,我都感觉到一种从业者的行业羞耻感:“我这个行业怎么这么业余?还需要记者来帮我们整理时间线?”滴滴第一次沟通和第二次...</p>\n\n<a href=\"https://www.huxiu.com/article/2389271.html\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://img.huxiucdn.com/article/cover/202312/06/105146344234.jpg?imageView2/1/w/720/h/405/|imageMogr2/strip/interlace/1/quality/85/format/jpg","relate_stocks":{"DIDIY":"DiDi Global Inc.","BK4022":"陆运","BK4230":"旅客陆运"},"source_url":"https://www.huxiu.com/article/2389271.html","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"2390801832","content_text":"滴滴不专业的故障沟通11月27日,滴滴出行出了故障,后续没有发布一个官方的时间线,没人知道故障是什么时候开始的和什么时候彻底恢复的。当时最为详细的故障时间线,是一家财经媒体发布的《滴滴崩溃原因找到了!并非网络攻击,而是底层系统软件故障》[1][2][3]。尽管和滴滴没有任何利益关系,我都感觉到一种从业者的行业羞耻感:“我这个行业怎么这么业余?还需要记者来帮我们整理时间线?”滴滴第一次沟通和第二次沟通间隔八个小时,这段时间内,一个猜测是“滴滴被网络攻击了”成了最有说服力的解释,以至于第二天滴滴要专门澄清:“没有被攻击”。如果滴滴第一时间就坦诚地和客户沟通是技术原因,并且指出数据不受影响,可以减少很多混乱和恐慌。关于这一点,我建议滴滴团队学习一下Atlassian的故障沟通最佳实践[4]的如下部分:Regular updates during the incident 在故障恢复后,滴滴用很含糊的词语把故障原因解释为:“底层系统软件发生故障”。利益相关方既不清楚这个故障软件是第三方的还是滴滴自研的,也不知道滴滴是否启动了对这个软件的替换/修复。只得到了一个空洞的无法验证的承诺:“深入开展技术风险隐患排查和升级工作”。为了表演火中取栗,滴滴先把栗子扔进去由于滴滴不披露,大家只能自行挖掘。滴滴10月17日发布的一篇技术分享文章《滴滴弹性云基于K8S的调度实践》被挖出来,大家特别摘抄出三个点:k8s 版本的升级:介绍到从 k8s 1.12 到 1.20 跨版本升级的方案。Kubernetes 1.12是2018年7月发布的,在2019年7月8日就终止支持了。也就是说,在2023年10月的时候,滴滴在生产环境使用一个社区已经废弃4年多的老版本。不论是看可靠性,还是看安全性,这都是非常草台班子的做法。在五年没有升级版本的历史债务下,滴滴团队决定孤注一掷,直接从1.12升级到1.20。但是 Kubernetes Deprecation Policy[5]很清楚地说了Beta API有可能在三个小版本之后就被删除。一次性升8个版本,风险完全不可控,也完全没有必要。从方案落地以及成本角度最终选取了原地升级。修改原生的kubelet实现,按hash值是否变化来决定是否重建容器的策略。在冒险跨版本升级的前提下,还进一步选择原地升级,断绝Plan B的可能性,是一个更加费解的策略。实际上Kubernetes集群的蓝绿升级非常成熟,出问题的时候也更容易挽救。原地升级除了可以节约几个机器资源之外,没有其他好处。而升级Node不重建容器的做法,极容易引入兼容性问题,给自己的安全/调试/性能都带来极大的困难。集群体量大,最大集群规模已经远远超出了社区推荐的5千个node上限,有问题的爆炸半径大。Kubernetes的多集群管理工具已经非常成熟了,而且滴滴其实有多集群,所以维护超大集群没有任何意义。作者自己也清楚“爆炸半径大”,那么合理的做法就是把集群拆成合理大小的,比如把两个一万节点的集群拆成十个两千节点的集群,管理成本没有增加,而运行风险和爆炸半径得到极大的降低。这三个策略都有一致的特征:本来没有问题,但是滴滴硬是要跟社区的建议反着来,制造一些高风险的问题,然后用自己的各种杂耍技巧去踩钢丝。所谓的“有困难克服困难都要上,没困难创造困难也要上”。这不像是一个正规的工程团队的行为模式,更像是新加入公司的实习生想要一炮打响采取的策略。由于这种杂耍技巧很难改正,我们可以合理地质疑,这个定时炸弹目前是不是还在滴滴机房滴答作响?阿里云摧毁客户信心11月12日,阿里云出现了一次影响所有区域的全局大故障。作为云厂商的一哥,阿里云发布了详细的故障时间线[6],但是发布的故障报告语焉不详,我建议大家参考冯若航的非官方复盘文章《我们能从阿里云史诗级故障中学到什么》,目前为止这篇文章是对这次故障最为权威的分析。这个故障离谱的是,尽管阿里云一再宣称自己有多区域,但是显然他们的RAM没有做到区域的隔离。这个故障还是对我个人的一巴掌。我和我的朋友王明松一直鼓吹大家使用IAM, 在《云原生王四条》[7]中,我们特意详述了使用IAM的Role特性。我在故障发生之前恰好发了几篇文章,试图帮助云厂商提高服务质量。但是正如冯若航所说,“深度使用云厂商提供的AK/SK/IAM不仅会让自己陷入供应商锁定中,更是将自己暴露在云基础设施单点的问题里”,我不得不承认,在你无法确认云厂商能力之前,暂停使用RAM 是一个明智的工程决策。草台班主的哀叹HelloJava的主理人据说曾经是阿里最优秀的架构师之一。他撰文《稳定性,难的不是技术,而是》向大家讲解了一些可靠性的经验。但是,非常抱歉,我认为这篇文章恰好反映了阿里技术团队的非常业余的一面。我对专家的期望是,他能推荐一个有效的可靠性模型,然后给出可以落地的工具推荐。实际上,作者只是零零碎碎分享一些私人经验,像个散文家一样想到哪里说到哪里,别说没有模型,连个结构都没有。有些地方甚至有明显的错误。比如作者主张:不管什么情况,以保障代码能正常运转是最重要的。这是一个非常非常非常糟糕的建议。对于绝大多数业务来说,服务的可用性(Availability)的优先级应该低于数据的完整性(Integrity)。如果维持服务在线会导致数据泄露或者数据损毁,那么应该毫不犹豫地牺牲可靠性。这个很好理解,对大多数用户来说,一天不能上钉钉和丢失钉钉联系人之间,显然后者损失更大。他下面这个建议本身是非常正确的,但是工程师可以用一个词语精炼地概括他的建议:追求故障平均修复时间(Mean Time To Recovery[8])。MTTR是一个有精确定义的概念,与之相关的概念还有MTBF以及SLO。在故障出现时尽快恢复,而不是解决故障,在保留一定的现场的基础上,尽快的恢复问题比查问题重要得多,例如大家很多时候看到最有效处理故障的方法可能是重启,有同城双活、异地多活的通常最有效的处理方法是切流量等。另外,作者使用稳定性这个词,是非常外行的。在工程学中,可靠性(Reliability)是一个专业术语,国家标准GB3187-1982《可靠性基本名词术语及定义》把这一套术语都涵盖了。而稳定性(Stability)则是计量系统的一个词汇,指一个衡器多次衡量同一个样品,应该输出一个稳定的值。淘宝用户或者特大号小编把这两个词汇搞混淆是可以原谅的,但是技术专家应该要知道这两者完全不是一回事。作者在文章中号称可靠性其实“技术上真的没有那么难”,只不过:这意味着的是大量的投入,能不能在稳定性这件事上保持持续的一定的投入,甚至当成做业务功能实现必须的投入,这才是真正做好稳定性最难的。然后作者把可靠性的锅抛给了管理者,指责:很多做过稳定性这事的人都知道,做这个事情最麻烦的是很难被认可,做得好,不出问题,不懂的人不知道你做了什么,出了问题的时候觉得你到底做了什么不客气地说,这是一种非常典型的大妈发牢骚。工程师都应该知道,一个工程项目的资源总是有限的,工程师的任务永远都是在给定时间和成本的多重限制下,满足既定的质量要求。如果一个目标需要“大量的投入”,那么决策者在衡量投入产出比之后,降低该目标,是非常正常的项目管理动作,没有任何值得抱怨的。值得抱怨的是这两种情况:项目本来要求A级可靠性,但是最终依照C级可靠性施工。或者,项目只需要C级可靠性,却花费大量的资源用于追求A级可靠性。你把银行存款业务跑在一台树莓派上,属于前者。你把公司内部论坛在亚洲欧洲北美三个region部署,属于后者。两者都是不可取的。那么依据项目的资源和需求,制定一个可行的(Feasible)可靠性目标,是谁的责任呢?在其他行业,答案很简单,这属于可行性研究(Feasibility Study)的一部分,也是一个非功能需求的技术问题,是工程团队的责任。机械工程师们和土木工程师们非常熟悉这个任务了。如果你在可靠性目标制定上有这么多牢骚,很可能问题不在于管理者,要么你制定的目标确实不合理,要么你能力有限,无法向利益相关人有力地证明目标的合理性。一篇文章读下来,我的印象就是:这位阿里技术一哥可能是个聪明人,也有一些不错的经验,但是整体上来说,没有接受过正规工程培训,严重欠缺工程理论常识,以前走野路子可能做了一些项目,但是个人经验几乎不具备可复制性。这样薄弱的底子,写文章参与可靠性讨论的结果,正如评论区一位读者说的:好像什么都说了,又好像什么都没说。天生不良的教育欠缺软件工程是一门工程学科,从业者首先是个工程师,其次才是个软件工程师/硬件工程师/Java工程师。但是很可惜,由于教育的缺失,很多顶着很高头衔的从业者,其实不能算现代工业的工程师,更像一群家庭作坊的手工业者。可靠性工程作为一个非常成熟的工程学科,是机械工程/土木工程的必修课。中南大学土木工程学院本科生就被要求必修《工程结构可靠度》[9]:Reliability of Engineering Structures 课程简介:荷载是工程结构设计的一个重要方面,也是着手一项工程设计要解决的一个重要问题,而概率可靠度方法已成为各类工程结构(房屋、桥梁、地下建筑、道路等)设计的理论基础。本课程全面、系统地介绍工程结构各类荷载的基本概念及其确定方法,以及结构可靠度分析与设计理论。作为成熟的工程学科,他们有专门的可靠性教材:作为对比,全国的软件工程系/计算机系还没看到给本科生开这门课程的,更不用说作为必修课。我翻了几本《软件工程》课本,没有一本覆盖了可靠性。当然,即使软件工程课程覆盖了可靠性理论,也不一定能触及学生。在上海交大计算机科学与技术系的课程表[10]中,《软件工程》竟然是选修课程。也就是说,一个优秀大学热门计算机专业的优秀毕业生,有可能会《移动互联网》或者《大数据处理》这些热门技能,但是很可能没有接受过最基本的工程教育。后天不足的持续学习尽管高等教育落后,但是工程界并没有自暴自弃,做了很多努力去提升从业者的可靠性能力。就以很多家庭主妇为了糊口落户而去参考的软件为例,可靠性是考试大纲中的一部分。系统的可靠性分析与设计系统的故障模型和可靠性模型系统的可靠性分析和可靠度计算提高系统可靠性的措施系统的故障对策和系统的备份与恢复国标GB/T29832 《系统与软件可靠性》有三个部分,虽然内容不一定及时更新,但是至少规定了一些基本术语和基本方法:第1部分:指标体系;第2部分:度量方法;第3部分:测试方法。如果偏好看书,教材也有很多,中英文的都有。如果你嫌弃软件可靠性开山鼻祖John D. Musa的Software Reliability Engineering: More Reliable Software Faster and Cheaper 2nd Edition是英文的,也可以读徐仁佐的《软件可靠性工程》[11]。如果有从业者学习能力实在差,不能考试,也不愿意读标准,甚至读书都会头痛,行业也提供了很多视频,比如波兰nobl9公司的学习园地[12]就有大量的关于可靠性的音频视频材料。该公司还主办SLOConf会议[13],免费提供很多可靠性演讲。如果有人连音频视频都懒得看,我甚至可以找出可靠性的动画片来。但问题是,提供再多的材料,从业者会去学习吗?用我的朋友王明松的话说:“有些从业者的软件工程理论水平,连软考拿落户的家庭主妇都不如。”这一点我毫无异议,因为家庭主妇至少不会搞混稳定性和可靠性。空洞承诺如果一个行业的从业者既没有得到正规的工程教育,也没有得到妥善的在职教育,而是凭着朴素的常识处理工程问题,就像农民工凭着朴素的常识去工地搬砖一样,虽然也能在包工头的带领下修起高楼大厦,但是可靠性恐怕要大打折扣。当故障过后,滴滴给出的空洞承诺:后续我们将深入开展技术风险隐患排查和升级工作,全面保障服务稳定性,尽最大努力避免类似事故再发生。这个承诺基于一个错误的假设:只要把现有的技术风险排查一遍,就可以全面保障服务稳定性了。但是用任何一个可靠性模型都会指出:预防故障只是可靠性的一部分工作,而技术风险也只是故障来源的一部分。至少从本次故障来看,滴滴的故障中处理流程非常不规范不严谨。如果我们上面的猜想成立—鉴于滴滴没有公开复盘材料,上述猜想是目前最有解释力的—那么滴滴平时的基础设施技术选型的决策流程也有严重问题。单单只是排查技术风险隐患,恐怕不能提升滴滴的服务水平。而阿里云给出的改进措施就更勉强了,几乎就是头痛医头,脚痛医脚:增加AK服务白名单生成结果的校验及告警拦截能力。增加AK服务白名单更新的灰度验证逻辑,提前发现异常。增加AK服务白名单的快速恢复能力。加强云产品侧的联动恢复能力。建议软件从业者在基本工程能力的欠缺,过去被高速增长的业务数据所掩盖,不被当成一个问题。但是潮水一旦落下,我们就看到一个又一个裸泳的屁股。对此,我们没有其他建议,只有一个:老老实实补课,不要再吹牛X了。参考资料:[1]http://www.leidacj.com/yuanchuang/show-36978.html[2]滴滴崩溃原因找到了!并非网络攻击 而是底层系统软件故障: http://www.leidacj.com/yuanchuang/show-36978.html[3]: http://www.leidacj.com/yuanchuang/show-36978.html[4]Atlassian的故障沟通最佳实践: https://www.atlassian.com/incident-management/incident-communication#:~:text=Part%202%3A%20Regular%20updates%20during%20the%20incident[5]Kubernetes Deprecation Policy: https://kubernetes.io/docs/reference/using-api/deprecation-policy/[6]阿里云发布了详细的故障时间线: https://status.aliyun.com/#/historyEvent[7]《云原生王四条》: https://github.com/lipingtababa/cloud-native-best-practices/blob/main/%E4%BA%91%E5%8E%9F%E7%94%9F%E7%8E%8B%E5%9B%9B%E6%9D%A1.md[8]Mean Time To Recovery: https://en.wikipedia.org/wiki/Mean_time_to_recovery[9]《工程结构可靠度》:https://civil.csu.edu.cn/bksjy/kcjs/kcjs.htm#:~:text=%E5%B7%A5%E7%A8%8B%E7%BB%93%E6%9E%84%E5%8F%AF%E9%9D%A0-,%E5%BA%A6,-%E8%8B%B1%E6%96%87%E5%90%8D%E7%A7%B0%EF%BC%9AReliability[10]上海交大计算机科学与技术系的课程表: https://bjwb.seiee.sjtu.edu.cn/bkjwb/info/13371.htm[11]《软件可靠性工程》: http://www.tup.com.cn/upload/books/yz/016476-01.pdf[12]波兰 nobl9 公司的学习园地: 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href=\"https://laohu8.com/S/DIDIY\">$DiDi Global Inc.(DIDIY)$ </a>像大多数股票一样,半死不活[捂脸] 这个词儿贴切不","listText":"<a href=\"https://laohu8.com/S/DIDIY\">$DiDi Global Inc.(DIDIY)$ </a>像大多数股票一样,半死不活[捂脸] 这个词儿贴切不","text":"$DiDi Global Inc.(DIDIY)$ 像大多数股票一样,半死不活[捂脸] 这个词儿贴切不","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/653447969","isVote":1,"tweetType":1,"viewCount":780,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0},{"id":664884815,"gmtCreate":1667922618238,"gmtModify":1667922621210,"author":{"id":"3541382744912552","authorId":"3541382744912552","name":"金克木","avatar":"https://static.tigerbbs.com/f5050d8a07d0bb340d57369927e80303","crmLevel":4,"crmLevelSwitch":0,"followedFlag":false,"idStr":"3541382744912552","authorIdStr":"3541382744912552"},"themes":[],"htmlText":"<a href=\"https://laohu8.com/S/DIDIY\">$DiDi Global Inc.(DIDIY)$</a>感觉有机构在建仓了","listText":"<a href=\"https://laohu8.com/S/DIDIY\">$DiDi Global Inc.(DIDIY)$</a>感觉有机构在建仓了","text":"$DiDi Global Inc.(DIDIY)$感觉有机构在建仓了","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/664884815","isVote":1,"tweetType":1,"viewCount":1203,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0},{"id":176940664,"gmtCreate":1626856875558,"gmtModify":1626856875558,"author":{"id":"3541382744912552","authorId":"3541382744912552","name":"金克木","avatar":"https://static.tigerbbs.com/f5050d8a07d0bb340d57369927e80303","crmLevel":4,"crmLevelSwitch":0,"followedFlag":false,"idStr":"3541382744912552","authorIdStr":"3541382744912552"},"themes":[],"htmlText":"风波会过去,进入好时机","listText":"风波会过去,进入好时机","text":"风波会过去,进入好时机","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":3,"commentSize":0,"repostSize":0,"link":"https://laohu8.com/post/176940664","repostId":"1199993483","repostType":2,"isVote":1,"tweetType":1,"viewCount":732,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"CN","totalScore":0},{"id":613702026,"gmtCreate":1650030282392,"gmtModify":1650030282392,"author":{"id":"3541382744912552","authorId":"3541382744912552","name":"金克木","avatar":"https://static.tigerbbs.com/f5050d8a07d0bb340d57369927e80303","crmLevel":4,"crmLevelSwitch":0,"followedFlag":false,"idStr":"3541382744912552","authorIdStr":"3541382744912552"},"themes":[],"htmlText":"滴滴到底是得罪谁了","listText":"滴滴到底是得罪谁了","text":"滴滴到底是得罪谁了","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":1,"repostSize":0,"link":"https://laohu8.com/post/613702026","repostId":"2227673292","repostType":2,"repost":{"id":"2227673292","kind":"news","pubTimestamp":1649940771,"share":"https://www.laohu8.com/m/news/2227673292?lang=&edition=full","pubTime":"2022-04-14 20:52","market":"us","language":"zh","title":"滴滴下架9个月,又一出行平台杀出","url":"https://stock-news.laohu8.com/highlight/detail?id=2227673292","media":"21世纪商业评论","summary":"记者/ 杨松 编辑/ 鄢子为行业老大滴滴的App已下架9个月,小弟们全体出动抢市场,T3出行成为最大赢家。月订单量增速最快的,是T3出行。力争老二2021年7月,滴滴下架之后,T3出行动作迅速,给乘客发补贴,广招司机,加快抢占市场。滴滴下架后,T3迅速推动加盟模式,司机自带车辆,也能入驻。2022年,T3出行仍在扩张,截至4月13日,平台进入84座城市。在争夺滴滴份额之际,T3出行再引入外部高管。","content":"<div>\n<p>记者/ 杨松 编辑/ 鄢子为行业老大滴滴的App已下架9个月,小弟们全体出动抢市场,T3出行成为最大赢家。根据交通运输部每月公布的网约车运行数据,《21CBR》记者统计了从2021年7月到2022年3月,10家平台的订单变化情况,包括滴滴、曹操、T3出行、享道、美团、首汽等。由于交通运输部没有公布每个平台的具体订单数据,而是环比月份变化。记者以2021年7月为基准,计算出相应的数据。记者发现,滴滴...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN2022041420543279aff7af&s=b\">Web Link</a>\n\n</div>\n","source":"tencent","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>滴滴下架9个月,又一出行平台杀出</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ 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编辑/ 鄢子为行业老大滴滴的App已下架9个月,小弟们全体出动抢市场,T3出行成为最大赢家。根据交通运输部每月公布的网约车运行数据,《21CBR》记者统计了从2021年7月到2022年3月,10家平台的订单变化情况,包括滴滴、曹操、T3出行、享道、美团、首汽等。由于交通运输部没有公布每个平台的具体订单数据,而是环比月份变化。记者以2021年7月为基准,计算出相应的数据。记者发现,滴滴...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN2022041420543279aff7af&s=b\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"BK4535":"淡马锡持仓","BK4531":"中概回港概念","BK4022":"陆运","BK4561":"索罗斯持仓","DIDI":"滴滴(已退市)","BK4505":"高瓴资本持仓","BK4539":"次新股","BK4526":"热门中概股"},"source_url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN2022041420543279aff7af&s=b","is_english":false,"share_image_url":"https://static.laohu8.com/9a95c1376e76363c1401fee7d3717173","article_id":"2227673292","content_text":"记者/ 杨松 编辑/ 鄢子为行业老大滴滴的App已下架9个月,小弟们全体出动抢市场,T3出行成为最大赢家。根据交通运输部每月公布的网约车运行数据,《21CBR》记者统计了从2021年7月到2022年3月,10家平台的订单变化情况,包括滴滴、曹操、T3出行、享道、美团、首汽等。由于交通运输部没有公布每个平台的具体订单数据,而是环比月份变化。记者以2021年7月为基准,计算出相应的数据。记者发现,滴滴受冲击严重,相比下架前,单量下滑了36.7%。月订单量增速最快的,是T3出行。T3出行2022年3月的单量,相较2021年7月,增长了116.9%。去年底,T3出行高调宣称,订单量突破300万,这是该公司日订单量首次突破300万单。力争老二2021年7月,滴滴下架之后,T3出行动作迅速,给乘客发补贴,广招司机,加快抢占市场。“去年7月,T3出行给用户发大额优惠券。”有消费者收到新用户100元的补贴。杭州T3出行司机王盼称,大额补贴发放后,平台收到大量订单,一天流水高峰期能有500元。T3起家时,以自营模式为主,即平台向司机提供车辆,司机只服务T3一个平台。滴滴下架后,T3迅速推动加盟模式,司机自带车辆,也能入驻。昆山网约车司机刘青,正是在那个时间点加盟T3出行。据他透露,当时平台为了吸引司机,推行免抽佣活动。据内部员工李山透露,截至目前,T3平台在线的司机中,加盟与直营比例为3:1,加盟司机量远大于直营。T3出行内部进入“战斗”状态,开辟新根据地。彼时,有T3出行员工在脉脉透露,产研同学主动实行“007”全月无休,计划月内连开15座城市。在T3全国扩张期,李山从滴滴跳槽到T3出行,运营一个新开辟城市。他所在的小组,5人中有3人来自滴滴,“有经验好使”。招人扩城,补助司乘两端,T3出行的一系列动作,让投资人看到滴滴之外,新平台崛起的希望。2021年10月,T3出行完成77亿A轮融资,此时距离上一次融资已有两年半时间。到了2021年底,T3出行对外表示,日订单量峰值突破300万,进入全国66座城市,累计注册用户数突破7200万。T3出行去年7月仅进入20多个城市。相当于不到半年时间,新进入40座城市,速度远超以往。2022年,T3出行仍在扩张,截至4月13日,平台进入84座城市。据国泰君安证券发布的《2022年1月出行服务平台数据跟踪》报告,T3出行市占率大幅提升,自2021年7月的3.1%,快速提升至2022年1月份的11.6%,排在所有出行平台第二位。增长烦恼T3出行是含着金汤匙出生的。2019年,一汽、东风汽车、长安汽车组团投资,联合腾讯、阿里巴巴,共同打造了T3出行。公司现任CEO崔大勇,曾出任一汽集团高管。如果从2019年7月上线算起,T3出行成为行业第二仅用2年多时间。T3出行想维持高速增长,有三大挑战。首先是,研发部门领导层变动频繁,不利于技术深耕。2020年底,经常与崔大勇一起出席活动的CTO谭天龙,早已离职。内部人士确认,已查询不到谭天龙信息。到了2021年1月,前菜鸟网络CTO谷雪梅(花名:康朵)加入T3出行,担任首席科学家。一年多过去了,除了入职新闻外,没有关于谷雪梅在T3的其他消息。在争夺滴滴份额之际,T3出行再引入外部高管。曾任百度产品总监、智联招聘CTO李京峰,在2021年10月空降T3出行,负责产研业务。有员工对此评论称,“公司成立2年多,产研都换第三个老大了。”“滴滴反应的速度快一点。”李山举例道,晚上11点,在滴滴内部群扔个问题,有人解决,但T3出行没有人回应。去年年底,一名用户投诉,平台系统崩溃,乱派发订单。该用户称,直接派了14辆车,手机被打爆了。其次,T3出行的订单依赖大额补贴,当优惠力度下降,需求降低时,增长难以持续。李山坦承,有时候派单的距离长达三四公里,“单量密度不够,派单距离就远了。”网约车司机刘青吐槽,曾被派过8公里外的订单,“不管多远它都给你派,司机不敢随便取消。”他表示,取消订单要扣服务分。T3大举进入新城市,抢地盘的过程中,还有个挑战是,出行需求骤降。“现在恨不得1个乘客,旁边有5辆车都想接他。”王盼称,到了今年3月,单量就非常低,一天就是300多块钱的流水。据交通运输部数据,今年 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