HotSwap: Enabling Live Dependency Sharing in Serverless Computing
Rui Li, Devesh Tiwari, and Gene Cooperman

TL;DR
HotSwap is a provider-side optimization for serverless computing that reduces cold-start latency by sharing pre-warmed dependency images across functions, especially benefiting skewed workloads.
Contribution
It introduces a cross-function pre-warming strategy that enables efficient dependency sharing while respecting cache constraints, improving cold-start times and resource utilization.
Findings
Accelerates dependency loading by 2.2 to 3.2 times on tested functions.
Saves 88% of cache space compared to function-specific pre-baking.
Effective in skewed production workloads with diverse dependencies.
Abstract
This work presents HotSwap, a novel provider-side cold-start optimization for serverless computing. This optimization reduces cold-start time when booting and loading dependencies at runtime inside a function container. Previous research has extensively focused on reducing cold-start latency for specific functions. However, little attention has been given to skewed production workloads. In such cases, cross-function optimization becomes essential. Without cross-function optimization, a cloud provider is left with two equally poor options: (i) Either the cloud provider gives up optimization for each function in the long tail (which is slow); or (ii) the cloud provider applies function-specific optimizations (e.g., cache function images) to every function in the long tail (which violates the vendor's cache constraints). HotSwap demonstrates cross-function optimization using a novel…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Distributed systems and fault tolerance · Cloud Computing and Resource Management
