Lessons from the evolution of the Batfish configuration analysis tool
Matt Brown, Ari Fogel, Daniel Halperin, Victor Heorhiadi, Ratul Mahajan, Todd D. Millstein
摘要
Batfish is a tool to analyze network configurations and forwarding. It has evolved from a research prototype to an industrial-strength product, guided by scalability, fidelity, and usability challenges encountered when analyzing complex, real-world networks. We share key lessons from this evolution, including how Datalog had significant limitations when generating and analyzing forwarding state and how binary decision diagrams (BDDs) proved highly versatile. We also describe our new techniques for addressing real-world challenges, which increase Batfish performance by three orders of magnitude and enable high-fidelity analysis of networks with thousands of nodes within minutes.
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