  One key to enabling high-performance serverless computing is to mitigate
cold-starts. Current solutions utilize a warm pool to keep function alive: a
warm-start can be analogous to a CPU cache-hit. However, modern cache has
multiple hierarchies and the last-level cache is shared among cores, whereas
the warm pool is limited to a single tenant for security concerns. Also, the
warm pool keep-alive policy can be further optimized using cache replacement
algorithms. In this paper, we borrow practical optimizations from caching, and
design FaasCamp, a caching-aided multi-tenant serverless computing framework.
FaasCamp extends the single-tier warm pool into multi-tiers, with a reclaim
pool introduced enabling secure function instance sharing among tenants. Also,
FaasCamp leverages machine learning to approximate the optimal cache
replacement policy to improve the warm rate. We have implemented a prototype
and conducted extensive experiments under multiple scenarios. The results show
that FaasCamp can outperform existing platforms with minimal overhead.
