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Showing posts from February, 2016

A paper a day keeps the doctor away: Gorilla: A Fast, Scalable, In-Memory Time Series Database

Operating large scale Internet services today is a challenge, and making sure that the services run well with minimal customer disruptions is doubly so. The reason is that both require good visibility into how the individual service components are performing, which necessitates gathering and analyzing a lot of measurements about the performance.    The measurements vary from metrics annotated with labels or dimensions that can be used to filter and group the results at query time, to exception stacks, log lines, and trace events. Collecting and analyzing such a large amount of metrics is the realm of time series databases, and the paper: " Gorilla, a fast, scalable, in-memory time series database " presents such a system which is in use at Facebook to handle monitoring and alerting their vast infrastructure. In the paper the authors start by articulating the design principles for Gorilla: they wanted a system that is always available for writes; they tolerated th