# InfiniCache: Exploiting Ephemeral Serverless Functions to Build a Cost-Effective Memory Cache

arXiv: https://arxiv.org/abs/2001.10483 · HTML: https://mlsanity.com/paper/2001.10483/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jan 2020.

## Built on by (most cited first, 2 of 2)

- [ServerlessLoRA: Enabling Low-Latency Serverless Multi-LoRA Serving](https://mlsanity.com/paper/2505.14468/) (2025)
- [FLStore: Efficient Federated Learning Storage for non-training workloads](https://mlsanity.com/paper/2503.00323/) (2025)

## Abstract (arXiv)

Internet-scale web applications are becoming increasingly storage-intensive and rely heavily on in-memory object caching to attain required I/O performance. We argue that the emerging serverless computing paradigm provides a well-suited, cost-effective platform for object caching. We present InfiniCache, a first-of-its-kind in-memory object caching system that is completely built and deployed atop ephemeral serverless functions. InfiniCache exploits and orchestrates serverless functions' memory resources to enable elastic pay-per-use caching. InfiniCache's design combines erasure coding, intelligent billed duration control, and an efficient data backup mechanism to maximize data availability and cost-effectiveness while balancing the risk of losing cached state and performance. We implement InfiniCache on AWS Lambda and show that it: (1) achieves 31 -- 96X tenant-side cost savings compared to AWS ElastiCache for a large-object-only production workload, (2) can effectively provide 95.4% data availability for each one hour window, and (3) enables comparative performance seen in a typical in-memory cache.