Data at Cloudflare scale: some insights on measurement for 1,111 interns

Cloudflare aims to hire 1,111 interns by 2026, providing numerous opportunities for developing and implementing code, as well as measuring complex Internet phenomena. Despite the vast data available at Cloudflare, analyzing it to detect Internet tampering by network middleboxes is challenging due to the scale and noise in the data. Former intern Ram Sundara Raman, now an assistant professor, leveraged his experience in active network measurements to develop methods for detecting such interference using Cloudflare's passive data. His internship focused on identifying tampering patterns without active probing, revealing the complexity of interpreting large-scale data. The project underscored that large infrastructure providers, despite extensive data, face difficulties in drawing clear conclusions about Internet tampering. Raman suggests that a combination of passive and active methods could enhance detection capabilities, and he continues to explore this at UC Santa Cruz. This collaboration highlights the potential for academia and industry to contribute to a better Internet, inviting more prospective interns to join such initiatives.

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