Tremulant: Latency in Serverless Platforms beyond the 99th Percentile

Abstract

Function-as-a-Service (FaaS) increases developer productivity by removing operational concerns such as managing hardware and software runtimes. Because function instances are started on demand, some requests must wait for a new instance, called a cold start. These are a common obstacle to more widespread adoption of FaaS, as they lead to unpredictable latency spikes that are not acceptable for some use cases. To solve this, many cold start optimizations have been implemented. However, comparatively little attention has been directed towards the slowest warm starts. With improvements in cold start times, slow warm starts emerge as a new problem for extreme tail events. By analyzing a dataset of several million requests across seven FaaS platforms, we show that the long tail of slow warm starts can be hundreds of times slower than their median performance, while a virtual machine we use as a baseline is substantially more consistent. We confirm this across four independent public datasets spanning 2020 to 2025, so the effect is neither new nor specific to one platform. Moreover, the warm share among the slowest calls starts to rise again at the highest percentiles: the most extreme latencies are not only cold starts, and cold-start mitigation alone cannot remove them.