Modern network infrastructure has evolved into a complex organism to satisfy the performance and availability requirements for the billions of users. Frequent releases such as code upgrades, bug fixes and security updates have become a norm. Millions of globally distributed infrastructure components including servers and load-balancers are restarted frequently from multiple times per-day to per-week. However, every release brings possibilities of disruptions as it can result in reduced cluster capacity, disturb intricate interaction of the components operating at large scales and disrupt the end-users by terminating their connections. The challenge is further complicated by the scale and heterogeneity of supported services and protocols.

Over the last decade, in an attempt to improve the end-user experience, the community has proposed a multitude of changes to the configuration parameters of the networking protocol stack of modern web servers. These changes range from improving security (e.g., TLS 1.2) to improving performance (e.g., HTTP/2). While the performance implications of several of these configuration parameters have been studied in isolation. To date, there is no holistic and general tool to infer, analyze, and under-stand the actual configuration parameters employed by popular web services. Moreover, it is unclear how these parameters are tuned to account for differences in network conditions, devices characteristics, or web page complexity. Although little is known, the configuration of these parameters impact attempts to model and understand performance expectations across the internet. To this end, we present InspectorGadget, a framework for characterizing and fingerprinting the configuration parameters of a server's network stack. InspectorGadget leverages some domain-specific heuristics for reverse engineering configuration parameters and options (protocol versions). To demonstrate the efficacy of InspectorGadget, we implemented a prototype of InspectorGadget and used this prototype to survey the configuration parameters for the top 10K online content providers across different regions and end-user devices.