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Many systems and services rely on timing assumptions for performance andavailability to perform critical aspects of their operation, such as varioustimeouts for failure detectors or optimizations to concurrency controlmechanisms. Many such assumptions rely on the ability of different componentsto communicate on time -- a delay in communication may trigger the failuredetector or cause the system to enter a less-optimized execution mode.Unfortunately, these timing assumptions are often set with little regard toactual communication guarantees of the underlying infrastructure -- inparticular, the variability of communication delays between processes indifferent nodes/servers. The higher communication variability holds especiallytrue for systems deployed in the public cloud since the cloud is a utilityshared by many users and organizations, making it prone to higher performancevariance due to noisy neighbor syndrome. In this work, we present Cloud LatencyTester (CLT), a simple tool that can help measure the variability ofcommunication delays between nodes to help engineers set proper values fortheir timing assumptions. We also provide our observational analysis of runningCLT in three major cloud providers and share the lessons we learned.

Cloudy Forecast: How Predictable is Communication Latency in the Cloud?