TrEnv-X: Transparently Share Serverless Execution Environments Across Different Functions and Nodes

Serverless computing is renowned for its computation elasticity, yet its full potential is often constrained by the requirement for functions to operate within local and dedicated background environments, resulting in limited memory elasticity. To address this limitation, this paper introduces TrEnv-X , a co-designed integration of the serverless platform with the operating system and CXL/RDMA-based remote memory pools. TrEnv-X ’s core innovations are repurposable sandboxes, which can be shared across different functions to decrease the associated creation overhead, and OS-level memory templates, which enable rapid state restoration from CXL/RDMA-based remote memory pools. To further demonstrate TrEnv-X ’s versatility, we generalize its design from traditional containers for microVM-based agent workloads and introduce new optimizations, including browser sharing and a page cache bypassing mechanism. Our evaluation shows that TrEnv-X achieves up to 7 × reduction in P99 latency and 48% memory savings for container-based functions. When applied to LLM agents, it reduces the P99 latency by up to 58% and memory usage by 61% compared to state-of-the-art systems like E2B.

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Publication Details

Journal
ACM Transactions on Computer Systems
Published
2026-03-28
DOI
https://doi.org/10.1145/3805475
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
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article

TrEnv-X: Transparently Share Serverless Execution Environments Across Different Functions and Nodes

Xuebin Liao, Yingdi Shan, Mengting Lu, Sixing Lin et al.
ACM Transactions on Computer Systems
Cloud Computing and Resource Management
article

TrEnv-X: Transparently Share Serverless Execution Environments Across Different Functions and Nodes

Xuebin Liao, Yingdi Shan, Mengting Lu, Sixing Lin, Zheng Liu, Teng Ma, Mengya Zhang, Jianda Huang, Ning Zhang, Yongwei Wu, Tao Ma, Kang Chen, Jinlei Jiang, Haifeng Gong
article en

Abstract

Serverless computing is renowned for its computation elasticity, yet its full potential is often constrained by the requirement for functions to operate within local and dedicated background environments, resulting in limited memory elasticity. To address this limitation, this paper introduces TrEnv-X , a co-designed integration of the serverless platform with the operating system and CXL/RDMA-based remote memory pools. TrEnv-X ’s core innovations are repurposable sandboxes, which can be shared across different functions to decrease the associated creation overhead, and OS-level memory templates, which enable rapid state restoration from CXL/RDMA-based remote memory pools. To further demonstrate TrEnv-X ’s versatility, we generalize its design from traditional containers for microVM-based agent workloads and introduce new optimizations, including browser sharing and a page cache bypassing mechanism. Our evaluation shows that TrEnv-X achieves up to 7 × reduction in P99 latency and 48% memory savings for container-based functions. When applied to LLM agents, it reduces the P99 latency by up to 58% and memory usage by 61% compared to state-of-the-art systems like E2B.

ACM Transactions on Computer Systems
Alibaba Group (United States) (US), Intel (United Kingdom) (GB), Zhejiang University (CN), Tsinghua University (CN)
Openalex Percentile: Top 4%
Cloud Computing and Resource Management
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