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 7x 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.

翻译：无服务器计算以其计算弹性著称，但其潜力常受限于函数需在本地专用后台环境中运行的要求，导致内存弹性受限。为解决此局限，本文提出TrEnv-X——一种将无服务器平台与操作系统及基于CXL/RDMA的远程内存池进行协同设计的集成方案。TrEnv-X的核心创新包括可重用的沙箱（可跨不同函数共享以降低创建开销）以及操作系统级内存模板（支持从基于CXL/RDMA的远程内存池快速恢复状态）。为进一步展示TrEnv-X的多功能性，我们将传统容器的设计泛化至基于微VM的代理工作负载，并引入包括浏览器共享和页面缓存绕过机制在内的新优化。评估表明：TrEnv-X对容器化函数可实现P99延迟降低7倍、内存节省48%；应用于LLM代理时，与E2B等现有最优系统相比，P99延迟降低58%、内存使用减少61%。