Adaptive Multi-Cloud Architecture: An Intelligent, Secure and Policy-Aware Framework for Workload Orchestration

Multi-cloud computing enables organizations to distribute applications and data across services from multiple cloud providers. It can improve flexibility and reduce dependence on a single provider, but also creates operational complexity: providers expose different interfaces, performance varies over time, costs are difficult to compare, and security or data-residency rules may restrict where workloads can execute. This paper proposes an Adaptive Multi-Cloud Decision and Orchestration Framework (AMCDOF) that combines mandatory policy validation with multi-objective workload placement. The framework first classifies each workload and checks security, privacy, residency, and organizational constraints. Only eligible environments are ranked using a configurable score based on latency, expected cost, availability, performance, and operational risk. An orchestration controller deploys the workload, monitors runtime signals, and reevaluates placement when conditions change. The paper specifies a conceptual decision model, modular architecture, pseudocode, and an empirical evaluation plan. No measured performance improvement is claimed: the framework is a design proposal requiring implementation and controlled testing.