Cloud-Native System Dynamics: Real-Time API Ingestion for Agri-Systems Management and Environmental Conflict Resolution

The application of Systems Thinking to agricultural supply chains provides critical insights into stakeholder dynamics, resource constraints, and environmental conflict. However, traditional System Dynamics models operate on static, retrospective datasets, rendering them incapable of capturing high-velocity fluctuations in cross-border agri-systems. This paper proposes a cloud-native architectural framework utilizing Amazon Web Services to construct a real-time, serverless pipeline for dynamic systems modeling. By deploying asynchronous Python middleware integrated with continuous data ingestion, the proposed system programmatically extracts live telemetry from agricultural nodes and logistics networks, instantly updating causal loop parameters and stock-and-flow variables. Preliminary architectural evaluations demonstrate that coupling enterprise cloud infrastructure with System Dynamics significantly reduces information asymmetry between conflicting stakeholders. This methodology provides management researchers and supply chain analysts with a deterministic, highly scalable technological foundation for resolving environmental conflicts through transparent, real-time data synthesis.