CodeCrunch: Improving Serverless Performance via Function Compression and Cost-Aware Warmup Location Optimization
Rohan Basu Roy, Tirthak Patel, Rohan Garg, Devesh Tiwari
Abstract
Serverless computing has a critical problem of function cold starts. To minimize cold starts, state-of-the-art techniques predict function invocation times to warm them up. Warmed-up functions occupy space in memory and incur a keep-alive cost, which can become exceedingly prohibitive under bursty load. To address this issue, we design CodeCrunch, which introduces the concept of serverless function compression and exploits server heterogeneity to make serverless computing more efficient, especially under high memory pressure.
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