AI 中文总结
本文通过对86家机构101次访谈的实证分析，明确云边部署复杂、上手难是核心痛点，提出四类架构方向，指出分布式计算的主要障碍是基础设施复杂性，高级抽象可缓解该问题。
AI 中文摘要
云计算、边缘计算与物联网（IoT）的普及为分布式应用创造了前所未有的机遇，但这种架构转变带来了深刻的基础设施复杂性，成为开发者生产力与创新的重大障碍。本文基于对86家机构开展的101次半结构化访谈，对云原生开发实践、痛点及预期进行实证分析。研究发现量化验证了部署复杂性（38.6%）与上手难度（35.6%）是主要运营瓶颈，开发者对生产力（53.5%）与自动化（44.6%）的重视程度远超原始性能优化。基于上述实证见解，本文研究了四类可解决已验证痛点的架构方向：统一对象抽象（Object-as-a-Service）、通过内部开发者平台（Internal Developer Platforms）实现的平台工程、声明式AI/ML服务流水线，以及基于WebAssembly的轻量边缘运行时。此外，本文详述了采用新型基础设施范式所需的多利益相关方生态系统，强调安全性、运营集成与严格的多租户隔离是投入生产的先决条件。研究结果表明，分布式计算采用的主要障碍并非执行性能，而是基础设施复杂性，跨多种范式的声明式管控高级抽象为缓解该问题提供了可行的架构路径。
英文摘要
The proliferation of cloud, edge, and Internet of Things (IoT) computing has created unprecedented opportunities for distributed applications. However, this architectural shift introduces profound infrastructural complexity, acting as a significant barrier to developer productivity and innovation. In this paper, we present an empirical analysis based on 101 semi-structured interviews across 86 organizations to investigate the state of cloud-native development practices, pain points, and expectations. Our findings quantitatively validate that deployment complexity (38.6%) and onboarding difficulty (35.6%) are the dominant operational bottlenecks, while developers heavily prioritize productivity (53.5%) and automation (44.6%) over raw performance optimization. Based on these empirical insights, we examine four architectural directions that address the validated pain points: unified object abstractions (Object-as-a-Service), platform engineering via Internal Developer Platforms, declarative AI/ML serving pipelines, and lightweight edge runtimes based on WebAssembly. Furthermore, we detail the multi-stakeholder ecosystem required for adopting novel infrastructure paradigms, emphasizing that security, operational integration, and strict multi-tenant isolation are prerequisites for production readiness. Our results demonstrate that the primary barrier to distributed computing adoption is not execution performance but infrastructural complexity, and that declaratively governed, higher-level abstractions across multiple paradigms offer viable architectural paths toward alleviating it.
