大规模迁移：在3万英尺高空更换应用引擎
ByteByteGo 以电商平台数据库迁移为例，讲解生产环境大规模迁移的核心挑战与关键策略。
中文处理结果
设想一个假设场景：一个在线购物平台取得了极大成功，它已经超出了原有数据库的承载能力。这导致订单历史加载非常缓慢。维护耗时远超以往。工程师们花费过多时间管理工作负载和系统的各种限制。
该系统背后的工程团队希望更换数据库，把数据迁移到一个承诺性能更好的新数据库。但你不能为了让切换上线而把一家热门网店下线。顾客一直在下单、修改地址、申请退款。商店不能就这么关停。
这个场景揭示了生产环境迁移所固有的主要挑战：在服务仍被人们依赖、持续运行的同时，你如何更换一个正在工作的系统？在大规模场景下，此类迁移中复制现有数据可能需要数天。此外，许多支撑性应用可能依赖于正在被替换的组件。每一个中间步骤都必须在日常业务照常进行的同时正常工作。
在本文中，我们将探讨大规模迁移是如何运作的，以及有助于尽可能提高其效率的关键策略。
究竟替换的是什么？
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原始正文摘录
Migrations at Scale: Changing the Application Engine at 30,000 Feet
Consider a hypothetical scenario in which an online shopping platform has become extremely successful. It has outgrown its original database. This causes order histories to load very slowly. Maintenance takes much longer than it used to. And engineers spend way too much time managing the workload and the system’s limitations.
The engineering team behind this system wants to replace the database and migrate the data to a new database that promises better performance. But you cannot take a popular online store offline to make the switch. Customers are always placing orders, changing addresses, and requesting refunds. The shop can’t be shut down just like that.
This scenario offers a glimpse of the main challenge inherent in production migrations. How do you change a working system while still running the service that people depend on? At scale, copying existing data during such migrations can take days. Also, many supporting applications may depend on the component being replaced. Every intermediate step needs to work while ordinary business continues.
In this article, we will look at how migrations work at scale and the key strategies that can help make it as efficient as possible.
What Exactly is Being Replaced?
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