In-Production Characterization of an Open Source Serverless Platform and New Scaling Strategies

Serverless computing has become more popular and evolved to support more complex tasks than the original Function as a Service (FaaS) model. The design of serverless systems has advanced to accommodate application demands and offer flexibility. Careful characterization of modern serverless systems and understanding of current gaps are warranted. Publicly available datasets on workloads in select production serverless systems do not fully represent all offerings or capture traces at the required time resolution to identify changes in application-level request-response patterns.

We characterize -and make available -production traces from a major public serverless provider with over 1.9 billion invocations spanning over two months. Our dataset is the first to characterize an open-source platform with large-scale trace data, millisecond-scale arrival times, and user configurations for pod concurrency and minimum pod scaling. Using this dataset, we provide new insights for optimizing serverless platforms.

With our insights, we design and implement FeMux, a serverless lifetime management system. FeMux multiplexes lightweight forecasters and uses a Representative Unified Metric (RUM) to decouple metrics from serverless platform implementations. This allows providers like us to update metrics flexibly or support multiple system objectives simultaneously. We prototype FeMux on the Knative platform and evaluate its benefits.