Your company has been training and deploying several ML models using TensorFlow on on-prem servers. The increasing complexity and costs associated with managing the training, updating, and deployment of these models have become a significant challenge. You are now tasked with identifying a cloud-based solution that not only reduces operational costs but also enhances efficiency and scalability. The solution should seamlessly integrate with TensorFlow and support the entire ML lifecycle, including training, evaluation, deployment, and version management. Considering these requirements, which two solutions would best address your company's needs? (Choose two.)