数据项目：Netflix规模下的数据资产管理

[

Netflix TechBlog

](https://netflixtechblog.com/?source=post_page---publication_nav-2615bd06b42e-7ca25888591e---------------------------------------)

[

Netflix TechBlog

](https://netflixtechblog.com/?source=post_page---post_publication_sidebar-2615bd06b42e-7ca25888591e---------------------------------------)

Learn about Netflix’s world class engineering efforts, company culture, product developments and more.

了解 Netflix 世界一流的工程实践、企业文化、产品开发等更多信息。

The Problem: Managing Assets at Netflix Scale

问题：在 Netflix 规模下管理资产

Netflix’s Data Platform is vast. We have millions of tables in our data warehouse and tens of thousands of scheduled workloads running across our orchestration systems. Behind each of these assets sits an engineer, a team, or an initiative — and behind each of those sits a set of decisions about who can access what, and how those workloads execute day after day.

Netflix 的数据平台非常庞大。我们的数据仓库中有数百万张表，以及数万个定时工作流在我们的编排系统中运行。每个资产背后都有一位工程师、一个团队或一个项目——而在这些背后，是一系列关于谁可以访问什么，以及这些工作流日复一日如何执行的决策。

For years, the tools we used to manage access and identity for these assets operated at the granularity of the individual asset. Every table had its own Access Control List (ACL). Every workflow ran under the identity of the engineer who authored it. In a workforce that is fluid, where people change teams, change roles, and occasionally leave the company, this fine-grained model broke down in two persistent, painful ways.

多年来，我们用于管理这些资产访问和身份的工具都是以单个资产为粒度进行操作的。每个表都有自己的访问控制列表（ACL）。每个工作流都在创建它的工程师的身份下运行。在一个人员流动频繁、经常更换团队、更换角色甚至偶尔离职的员工队伍中，这种细粒度模型在两个持续且痛苦的方面失效了。

Problem 1: Permissions that can’t keep up with organizational changes

问题 1：权限无法跟上组织变更的步伐

Imagine you’re on a team that owns a few hundred tables. Your org restructures, a neighboring team merges into...