Elastic AI Orchestration for Multi-Cloud Enterprises
Keywords:
Multi-Cloud MLOps, Decentralized AI Development, Coordination-as-a-Service, Adaptive MLOps Orchestration, Best-of-Breed Cloud Strategy, Cross-Cloud Model Lifecycle Management, Continuous Integration and Deployment for ML, Vendor Lock-In Mitigation, Enterprise AI Governance, Policy-Driven Orchestration, Model Availability Optimization, Total Cost of Ownership Reduction, Distributed Training and Serving, Cloud-Agnostic MLOps Architectures, Operational Resilience, Dynamic Workload Placement, Regulatory-Compliant AI Operations, Enterprise Distribution Efficiency, MLOps Automation, Adaptive Resource Coordination.Abstract
Decentralization is widely recognized as an enabler of greater flexibility, responsiveness, and resilience in enterprise IT ecosystems. In AI development, those benefits can be realized with a best-of-breed multi-cloud MLOps deployment strategy. However, while tooling for Continuous Integration and Continuous Deployment is becoming increasingly easy to use and is usually available as-a-service on every cloud, Coordination As-A-Service for multi-cloud is rare. Making it worse, almost every MLOps Big Vendor provides a single-cloud solution, meaning that different aspects of the MLOps lifecycle cannot be independently chosen on the best cloud for the workload. As a result, multi-cloud MLOps is often created in an ad-hoc trial-and-error manner, causing vendor lock-in, poor maintainability, and higher development and operational costs. An adaptive MLOps Orchestration System is proposed, providing Coordination As-A-Service for multi-cloud MLOps. It enables governing and operating a multi-cloud MLOps deployment to fulfil enterprise policies and requirements while serving complex and changing enterprise distribution and efficiency needs. The study outcomes increase the quality and efficiency of enterprise MLOps by lowering the total cost of ownership, increasing model availability, and improving responsiveness to user demands while conforming to organisational policies and regulatory requirements with minimum effort.
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