Multi-Tenant AI Applications on OCI: Design Patterns for Scalable and Secure Agent-as-a-Service Frameworks

This paper explores scalable design patterns and architectural strategies for deploying multi-tenant AI applications on Oracle Cloud Infrastructure (OCI) using an Agent-as-a-Service (AaaS) framework. It evaluates containerized and event-driven agent deployments, enforces multi-tenant isolation, and leverages reinforcement learning for dynamic autoscaling. The research identifies key architectural primitives and offers secure, reproducible implementation patterns aligned with OCI's native services, including Kubernetes (OKE), Terraform, IAM, and Observability. The proposed model enhances cost-efficiency, security, and lifecycle automation in AI microservices.