PrintQueue: performance diagnosis via queue measurement in the data plane

When diagnosing performance anomalies, it is often useful to reason about why a packet experienced the queuing that it did. To that end, we observe that queuing is both a result of historical effects and the current state of the network. Further, both factors involve short and long timescales by nature. Existing work fails to provide insight that satisfies all of these needs.

This paper presents PrintQueue, a practical data-plane monitoring system for tracking the provenance of packet-level delays at both small and large timescales. We propose a set of metrics for describing 'congestion regimes' and present a set of novel data-plane data structures that accurately track those metrics over arbitrary time spans. We implement PrintQueue on a Tofino switch and evaluate it with multiple network traces. Our evaluation shows that the accuracy of PrintQueue is up to 3× times higher while the overhead is 20× times smaller than existing work.