workflow and some of their shortcomings • Why DevOps? • Why Containers, Kubernetes, and Helm? • Intro to Kubeflow, Helm, Argo • Demos • Image classification with Inception v3 and transfer learning • Automate containers • Deploy ML components to Kubernetes with Kubeflow • Scale and test ML experiments with Helm • Manage training jobs and pipelines with Argo • Serve trained models for inference with TF Serving AI/ML • But, must ensure data scientist are not hindered by structure Why Containers, Kubernetes & Helm? • Container • Contains everything needed to run your application • Build once run anywhere •

运⾏行行和构建应⽤用 跑在 KUBERNETES 上的应⽤用 • k8s 基础资源之外 • 资源分组和整体状态 • 重⽤用 YAML 配置 • 版本化 • 启动依赖 • Helm 很棒，但是 …… 典型企业应⽤用的架构 CAICLOUD/RUDDER • 2 CRDs - Release, Release History • 1 控制器器 - Rudder aka https://github.com/caicloud/canary-release • https://github.com/caicloud/charts • https://github.com/caicloud/helm-registry Rudder 技术架构 ⼀一套基于 k8s 控制器器模式的原⽣生的应⽤用管理理 和编排运⾏行行时 安全性与扩展性：从 k8s 原⽣生模式中获益 状态可读：跟踪所有 k8s

streamnative.io 基础决定上层：Cloud-Native • State / Scale / Storage https://github.com/apache/pulsar-helm-chart streamnative.io 基础决定上层：Cloud-Native https://streamnative.io/blog/release/2020-08-18-anno