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In this paper, the authors argue that an important piece of the system administration puzzle has largely been left untouched by researchers. This piece involves mechanisms and policies to identify as well as collect missing instrumentation data; the missing data is essential to generate the knowledge required to address certain administrative tasks satisfactorily and efficiently. They introduce the paradigm of experiment-driven management which encapsulates such mechanisms and policies for a given administrative task. They outline the benefits that automated experiment-driven management brings to several long-standing problems in databases as well as other systems, and identify research challenges as well as initial solutions.
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