Edge computing places computing, storage and network functions at the site where data is generated to provide fundamental support for the Industrial Internet, smart transportation, urban sensing and other low-latency intelligent applications. As cloud-native technologies move from the central cloud to the edge, lightweight containers have gradually been used to run edge microservices, support device protocol adaptation and real-time inference. Edge nodes are highly heterogeneous in terms of processor architecture, memory capacity, network stability and security boundaries, and thus traditional container orchestration methods that assume a central cluster cannot be applied directly. Based on a review of research and industry data over the past three years on edge cloud-native container orchestration, this paper establishes a layered layout scheme of "cloud-side control, edge autonomy, lightweight nodes, and service proximity" to address the problem and puts forward optimisation strategies in terms of resource constraints, latency requirements, image startup speed, state persistence, and security isolation. The study proposes that container layout at the edge should aim to maximise the use of a single node and build a complete-stack decision-making system that covers all levels, networks and security to enhance business continuity, deployment efficiency and operational control.

Chenghao Shi. Research on Cloud Native Lightweight Container Layout Scheme for Edge Computing Scenarios. International Journal of Big Data Intelligent Technology (2026), Vol. 7, Issue 2: 20-30. https://doi.org/10.38007/IJBDIT.2026.070203.

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