Governed Serverless Automation Ecosystem for AI-Driven Enterprise Integration and Sustainable Cloud Operations

Abstract

Governance, serverless, and automation facilitate enterprise integration that is adaptive, cost-effective, low-code, and capable of creating dynamic, context-aware, and value-adding workloads. This creates a need for policy-based management that simplifies implementation in multicloud scenarios. Serverless automation, enabled by event-driven workloads and dynamic resource provisioning for short-lived tasks, can operate in multicloud environments without being controlled by any provider. Introducing artificial intelligence facilitates improvements in scheduling and resource optimization. However, these benefits are not well understood, nor are these ecosystems properly managed. What governance is required for such serverless automation in an AI-enable enterprise integration setting? What does governance in serverless environments achieve? These questions are addressed through a structured research-product approach. The concept of serverless automation is first established, then applied to governance and a serverless context.
A critical perspective on governance emerges through examination of central concepts and their interplay within a formal control-compliance-risk framework. From a practical angle, governance focuses on preserving trust in business operation and service delivery. This leads to the consideration of a Cloud Automation Control Plane that governs the core events and processes of Cloud Automation on behalf of initiation parties. The enterprise integration layer can be made serverless to minimize code development, improve resilience, and enhance security with AI assistance. The AI inclusion can be exploited for intelligent workload and resource management without compromising the governing principles. These avenues in combination demonstrate that a clear governance model can enable sustainable Cloud AI Automation for the enterprises and the ecosystem.