A Progressive Delivery Model with Enforced Cloud Data Governance for Consumer-Scale Digital Applications

Abstract

Consumer-scale digital applications operate under conflicting pressures: the need for rapid, continuous delivery (high-velocity deployment) and the mandate for strict data governance and regulatory compliance (e.g., GDPR, CCPA). Traditional delivery models lack the necessary safety mechanisms to enforce data policies during the feature rollout process, risking massive compliance violations during phased releases. This paper proposes the Progressive Delivery with Enforced Data Governance (PD-EDG) Model, an integrated architecture that leverages fine-grained control over feature exposure and couples it with automated, real-time data policy validation. PD-EDG utilizes a Context-Aware Feature Flagging (CAFF) system to progressively roll out features to user subsets, and crucially, integrates a Policy-as-Code (PaC) Data Governance Gateway (DGG) into the continuous delivery pipeline. The DGG acts as a gate, ensuring that the feature, in its current deployment stage, only accesses data governed by pre-approved compliance rules. The empirical evaluation demonstrates that PD-EDG achieved a $\mathbf{70\%}$ reduction in the exposure window for deployment-related policy violations compared to standard progressive delivery, and successfully prevented $\mathbf{100\%}$ of simulated data access non-compliance incidents during staged rollouts, confirming its efficacy in securing high-velocity consumer applications.