MXFaaS: Resource Sharing in Serverless Environments for Parallelism and Efficiency

Abstract

Although serverless computing is a popular paradigm, current serverless environments have high overheads. Recently, it has been shown that serverless workloads frequently exhibit bursts of invocations of the same function. Such pattern is not handled well in current platforms. Supporting it efficiently can speed-up serverless execution substantially. In this paper, we target this dominant pattern with a new serverless platform design named MXFaaS. MXFaaS improves function performance by efficiently multiplexing (i.e., sharing) processor cycles, I/O bandwidth, and memory/processor state between concurrently executing invocations of the same function. MXFaaS introduces a new container abstraction called MXContainer. To enable efficient use of processor cycles, an MXContainer carefully helps schedule same-function invocations for minimal response time. To enable efficient use of I/O bandwidth, an MXContainer coalesces remote storage accesses and remote function calls from same-function invocations. Finally, to enable efficient use of memory/processor state, an MXContainer first initializes the state of its container and only later, on demand, spawns a process per function invocation, so that all invocations can share unmodified memory state and hence minimize memory footprint. We implement MXFaaS in two serverless platforms and run diverse serverless benchmarks. With MXFaaS, serverless environments are much more efficient. Compared to a state-of-the-art serverless environment, MXFaaS on average speeds-up execution by 5.2×, reduces P99 tail latency by 7.4×, and improves throughput by 4.8×. In addition, it reduces the average memory usage by 3.4×.