  Function-as-a-Service (FaaS) has recently emerged as a new cloud computing
paradigm. It promises high utilization of data center resources through
allocating resources on demand at per-function request granularity. High
cold-start overheads, however, have been limiting FaaS systems' such potential.
Prior work has recognized that time redundancy exists across different cold
function invocations and has proposed varied snapshots that capture the
instantaneous execution state so allow for jump-starts through restoration.
However, it remains unclear what the cold-start performance limits are as the
previous snapshots employ different techniques and aredesigned for different
environments. In this paper, we summarize these snapshots from a taxonomic
perspective andpresent a model that depicts the cold-start performance
fromfirst principles. To approximate the performance limits, we propose a
snapshot design SnapFaaS. We evaluate SnapFaaS using real-world FaaS functions.
Our empirical results prove SnapFaaS' efficiency. It is 2-10x as fast as prior
work for most functions and achieves near-optimal cold-start performance.
