Intel® Trust Domain Extensions (Intel® TDX) is designed to isolate Trust Domain (TD) VMs from the hypervisor and other non-TD software on the host platform to enhance confidential computing from a broad range of software attacks. Federated Learning is a machine learning algorithm that allows a model to be trained across multiple decentralized nodes without explicitly exchanging local data samples. In this session, we describe the use case of running Federated Learning to train a global machine learning model collaboratively across a network of trust domains running on VMware® Cloud Foundation while keeping the sensitive data localized.