• Serve trained models for inference with TF Serving • Rapid prototyping with self-service Jupyter notebook from JupyterHub Simplified ML Workflow/Pipeline What is DevOps? • “A cross-disciplinary community config • Tensorflow, PyTorch, MXNet, Chainer, and more • JupyterHub to create and manage interactive Jupyter notebooks • Model serving – serve exported models with TF Serving or Seldon • Additional components Demo: Create End to End ML Pipelines with Argo Demo: Rapid prototyping with self-service Jupyter notebook from JupyterHub What’s Next? one) Solution is Kubernetes: • Highly Scalable • Easy to explore

A/B test 和滚动升级。 模型服务 实现对 GPU 集群资源进行管理，根 据用户作业请求自动分配和回收 GPU 资源。 GPU 集群管理 对接存储系统，管理数据集；提供 notebook 交互式代码开发和调试工 具；管理数据预处理批作业。 模型开发 海尔工业互联网 – 才云数据解决方案 海尔工业互联网 – 才云数据解决方案 海尔工业互联网 – 才云数据解决方案 海尔工业互联网