Multi Tenant

Multi-tenancy focuses on efficiently sharing computing resources among multiple users or applications, addressing challenges like resource contention and performance isolation. Current research emphasizes developing parameter-efficient fine-tuning methods for large language models, optimizing in-memory indexing for vector databases, and employing machine learning to monitor and manage resource allocation in multi-tenant environments, including deep neural networks and federated learning. These advancements improve resource utilization, enhance performance, and enable scalable deployment of diverse applications in cloud and edge computing settings.