Exploring Challenges in Developing Edge-Cloud-Native Applications Across Multiple Business Domains

2026-03-04

AI Summary

This study addresses the challenges faced by edge-cloud-native applications in cross-industry adoption, including fragmented toolchains, steep learning curves, and inconsistent performance across hybrid environments. Through in-depth interviews with practitioners from multiple sectors, the work offers the first systematic insight into the real-world pain points experienced by non-technical teams during digital transformation. It reveals that such teams prioritize productivity, service quality, and usability over cost alone. Grounded in qualitative analysis, the research identifies key platform design requirements centered on developer-friendliness, end-to-end lifecycle simplification, and SLA-aware orchestration, with a focus on distributed network computing, hybrid cloud management, and service-level agreement (SLA) assurance. These findings provide a practice-oriented roadmap for the evolution of converged cloud-network infrastructures.

Technology Category

• Machine Learning: Learning on the Edge & Model Compression
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Search and Optimization: Non-convex Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Data transparency and provenance

Abstract

As the convergence of cloud computing and advanced networking continues to reshape modern software development, edge-cloud-native paradigms have become essential for enabling scalable, resilient, and agile digital services that depend on high-performance, low-latency, and reliable communication. This study investigates the practical challenges of developing, deploying, and maintaining edge-cloud-native applications through in-depth interviews with professionals from diverse domains, including IT, finance, healthcare, education, and industry. Despite significant advancements in cloud technologies, practitioners, particularly those from non-technical backgrounds-continue to encounter substantial complexity stemming from fragmented toolchains, steep learning curves, and operational overhead of managing distributed networking and computing, ensuring consistent performance across hybrid environments, and navigating steep learning curves at the cloud-network boundary. Across sectors, participants consistently prioritized productivity, Quality of Service, and usability over conventional concerns such as cost or migration. These findings highlight the need for operationally simplified, SLA-aware, and developer-friendly platforms that streamline the full application lifecycle. This study contributes a practice-informed perspective to support the alignment of edge-cloud-native systems with the realities and needs of modern enterprises, offering critical insights for the advancement of seamless cloud-network convergence.

Problem

• edge-cloud-native
• development challenges
• distributed computing
• cloud-network convergence
• operational complexity

Innovation

• edge-cloud-native
• developer experience
• cross-domain challenges
• SLA-aware platforms
• cloud-network convergence