Fast and Efficient Memory Reclamation For Serverless MicroVMs
Resource elasticity is one of the key defining characteristics of the Function-as-a-Service (FaaS) serverless computing paradigm. In order to provide strong multi-tenant isolation, FaaS providers commonly sandbox functions inside virtual machines (VMs or microVMs). While compute resources assigned t...
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Zusammenfassung: | Resource elasticity is one of the key defining characteristics of the
Function-as-a-Service (FaaS) serverless computing paradigm. In order to provide
strong multi-tenant isolation, FaaS providers commonly sandbox functions inside
virtual machines (VMs or microVMs). While compute resources assigned to
VM-sandboxed functions can be seamlessly adjusted on the fly, memory elasticity
remains challenging, especially when scaling down. State-of-the-art mechanisms
for VM memory elasticity suffer from increased reclaim latency when memory
needs to be released, compounded by CPU and memory bandwidth overheads. We
identify the obliviousness of the Linux memory manager to the virtually
hotplugged memory as the key issue hindering hot-unplug performance, and design
HotMem, a novel approach for fast and efficient VM memory hot(un)plug,
targeting VM-sandboxed serverless functions. Our key insight is that by
segregating virtually hotplugged memory regions from regular VM memory, we are
able to bound the lifetimes of allocations within these regions thus enabling
their fast and efficient reclamation. We implement HotMem in Linux v6.6 and our
evaluation shows that it is an order of magnitude faster than state-of-practice
to reclaim VM memory, while achieving the same P99 function latency with a
model that statically over-provisions VMs. |
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DOI: | 10.48550/arxiv.2411.12893 |