提高Pinterest上Goku时间序列数据库的效率（第3部分）
Monil Mukesh Sanghavi; Software Engineer, Real Time Analytics Team | Ming-May Hu; Software Engineer, Real Time Analytics Team | Xiao Li; Software Engineer, Real Time Analytics Team | Zhenxiao Luo; Software Engineer, Real Time Analytics Team | Kapil Bajaj; Manager, Real Time Analytics Team |
Monil Mukesh Sanghavi; 软件工程师，实时分析团队 | Ming-May Hu; 软件工程师，实时分析团队 | Xiao Li; 软件工程师，实时分析团队 | Zhenxiao Luo; 软件工程师，实时分析团队 | Kapil Bajaj; 经理，实时分析团队 |
At Pinterest, one of the pillars of the observability stack provides internal engineering teams (our users) the opportunity to monitor their services using metrics data and set up alerting on it. Goku is our in-house time series database that provides cost efficient and low latency storage for metrics data. Underneath, Goku is not a single cluster but a collection of sub-service components including:
在Pinterest，可观察性堆栈的支柱之一为内部工程团队（我们的用户）提供了使用度量数据监控其服务并设置警报的机会。Goku是我们内部的时间序列数据库，为度量数据提供成本效益和低延迟的存储。在底层，Goku不是一个单一的集群，而是一个包含以下子服务组件的集合：
- Goku Short Term (in-memory storage for the last 24 hours of data and referred to as GokuS)
- Goku短期（存储最近24小时的数据的内存存储，简称GokuS）
- Goku Long Term (ssd and hdd based storage for older data and referred to as GokuL)
- Goku 长期（基于 SSD 和 HDD 的存储用于旧数据，简称 GokuL）
- Goku Compactor (time series data aggregation and conversion engine)
- Goku Compactor（时间序列数据聚合和转换引擎）
- Goku Root (smart query routing)
- Goku根（智能查询路由）
You can read more about these components in the blog posts on GokuS Storage, GokuL (long term) storage, and Cost Savings on Goku, but a lot has changed in Goku since those were written. We have implemented multiple features that increased the efficiency of Goku and improved the user experience. This three part blog post series covers the efficiency improvements (view parts 1 and parts 2), and this final part will cover the reduction of the overall cost of Goku and Pinterest.
您可以在GokuS 存储、GokuL（长期）存储和Goku 成本节约的博客文章中了解更多关于这些组件的信息，但自那些文章以来，Goku 发生了很多变化。我们已经实施了多个功能，提高了 Goku 的效率并改善了用户体验。这个三部分的博客系列涵盖了效率改进（查看第一部分和第二部分），而这最后一部分将涵盖 Goku 和 Pinterest 的整体成本降低。