Strengthening U.S. Digital Infrastructure Through AI-Powered Cloud-Native Software Resilience and Secure Delivery Systems

Abstract

The growing dependence of government, healthcare, finance, energy, communications, transportation, and other critical sectors on software-intensive services has made cloud-native resilience and secure software delivery important components of U.S. digital infrastructure. Microservices, containers, orchestration platforms, and continuous integration and delivery pipelines improve scalability and release velocity, but they also introduce complex service dependencies, fragmented telemetry, cascading failures, vulnerable software components, and software supply-chain integrity risks. This study develops the AI-Powered Cloud-Native Resilience and Secure Delivery Framework (AICR-SDF), a conceptual artifact that connects critical-service requirements, cloud-native infrastructure, observability, AI-assisted operational intelligence, secure software delivery, and policy-governed response. The framework is developed using Design Science Research Methodology supported by an integrative literature review. Its technical foundations draw on established reliability, resilience, software-delivery, network-analysis, cybersecurity, and governance concepts, including availability and reliability functions, service-level objectives and error budgets, burn-rate analysis, DORA software-delivery metrics, network centrality, likelihood–impact risk assessment, the Common Vulnerability Scoring System, Supply-chain Levels for Software Artifacts, the NIST Secure Software Development Framework, and resilience-loss analysis. Four qualitative scenarios demonstrate how the framework distinguishes normal deployment, service degradation, an unverified software artifact, and cascading microservice failure. Ex ante evaluation examines requirements coverage, internal consistency, standards alignment, scenario applicability, governance adequacy, and implementability. The study contributes an integrated and policy-aware conceptual foundation for the future prototyping and empirical evaluation of resilient and securely delivered cloud-native services.