This technical paper details the architecture and design of Monarch, a planet-scale in-memory time series database developed at Google. Monarch is used to monitor the performance and availability of massive, globally distributed systems like YouTube, Google Maps, and Gmail. The paper discusses the system's novel features, including its regionalized architecture, expressive query language, and support for sophisticated data types, such as distributions and exemplars. It also presents a comprehensive evaluation of Monarch's scalability, highlighting its ability to handle trillions of time series, ingest terabytes of data per second, and serve millions of queries per second. Finally, the paper outlines key lessons learned from the development and operation of Monarch over a decade.

https://www.vldb.org/pvldb/vol13/p3181-adams.pdf

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