February 2024
Intermediate to advanced
370 pages
7h
Chinese
Content preview from 数据工程之道：设计和构建健壮的数据系统
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设计好的数据架构
|
81
在云时代，大多数数据系统都是即付即得且易于扩展的。系统可以在查询成本模型、处
理能力成本模型或即付即得模型的另一种变体上运行。这种方法比资本支出方法更有
效。现在可以向上扩展以获得高性能，然后缩小规模以节省资金。然而，即付即得的方
法使支出更具活力。数据领导者面临的新挑战是管理预算、优先级和效率。
云工具需要一组用于管理支出和资源的流程。过去，数据工程师从性能工程的角度考
虑，在一组固定的资源上最大化数据处理的性能，并购买足够的资源以满足未来的需
求。借助
FinOps
，工程师需要学会思考云系统的成本结构。例如，在运行分布式集群
时，
AWS spot
实例的适当组合是什么？就成本效益和性能而言，运行大量日常作业的最
合适方法是什么？公司应在何时从按查询付费模式转换为预留容量模式？
FinOps
改进了运营监控模型，以持续监控支出。
FinOps
不是简单地监控
Web
服务器的
请求和
CPU
利用率，而是监控无服务器功能处理流量的持续成本，以及支出触发警报
的峰值。正如系统被设计为在流量过大时优雅地失败一样，公司可能会考虑对支出采用
硬性限制，并采用优雅的故障模式来应对支出高峰。
运营团队还应该考虑成本攻击。正如分布式拒绝服务（
Distributed Denial-of-Service
，
DDoS
）攻击可以阻止对
Web
服务器的访问一样，许多公司都懊恼地发现，从
S3
存储桶
中过度下载可能会导致支出暴增，并使一家小型初创公司面临破产威胁。在公开共享数
据时，数据团队可以通过设置请求者付费政策来解决这些问题 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.