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Cloud Mesh MultiCluster-Route-Manager Application & Route Management VWA Controller (Vertical Workload Autoscaler) HPAPlus Controller HNA Controller Auto Scale CronHPA Controller CLB-Service/Ingress-Controller Support HPA, CronHPA, VWA (Vertical Workload Autoscaler) Ø Keep share memory during Pod upgrade Ø Scaled Up with LGV (Last Good Version) Ø Per Pod Per PV Ø Per Workload Per PV Ø Pod Auto Migrate when Quota for Biz A etcd DynamicQuota reconcile Prometheus +Grafana Commit workload and DynamicQuota, PriorityClass, Workload Annotations pod-resource-compressor MutatingWebhook DynamicQuota ValidatingWebhook

思考题： 有状态的复杂应用如何管理？ 基础设施能力还如何演进和透出？ 研发自己的诉求如何传达给运维和基础设施？ K8s 扩展能力的真实情况 我的 Zookeeper 该用 哪种K8s Workload 接入？ 你恐怕得写个 Operator…… Operator是啥？ CRD Controller Informer Reflector Event Handler Loop … 我们业务压力大 2. A list of overwritable parameters (schemas) 1.Description of the application Component 核心workload 可访问 可复制 长久运行 Server √ √ √ Singleton Server √ × √ Worker × √ √ Singleton Worker × × √ Task × as value Operational hint from developers to operators Component 从 CRD 到 扩展 Workload OpenFaaS CRD OpenFaaS 扩展Workload 可发现、可管理的运维能力：OAM Traits System 发现运维能力 查看能力用法 绑定能力给应用 提前暴露冲突 kubectl get traits

image - replicas - port 抽象 Deployment - image - replicas Service - port 原始 k8s API 资源 Workload - image - replicas Rollout - canary ArgoRollout - image - replicas - rollout Deployment interoperability Application Application Application Platform foo Platform bar Serverless baz Common Workload Types Manual Scaler K8s Operators Kubernetes + OAM K8s Plugin HPA Deployment scale-to-0 Function Configs (YAML) Revision Controller Scaling Controller Rollout Controller kubectl apply Workload Controller Kubernetes metrics traffic Workloads (YAML) Continuous Delivery is in k8s now

dev/v1alpha2 kind: Component metadata: name: frontend annotations: description: Container workload spec: workload: apiVersion: apps/v1 kind: Deployment spec: template: spec: containers: - name: web get deployment NAME REVISION AGE frontend-c8bb659c5 1 2d15h $ kubectl get components NAME WORKLOAD frontend deployment.apps.k8s.io Component：应用中的一个组成部分，例如容器、 Function或者云服务等 应用组件 运维能力 扩容策略 io services.k8s.io route route.core.oam.dev apps.k8s.io tls tls.core.oam.dev apps.k8s.io Workload 与 Trait 注册与发现机制 # 示例：将 Istio VirtualService 注册为平台 的流量管理能力 示例: 使用 OAM 模型管理应用 1. 创建应用组件 2. 绑定运维特征

Automation; kubebuilder + controller-runtime + helm Operator Capability Levels Installation of the workload • Operator deploys an Operand or configures off- cluster resources • Operator waits for managed resources to the user leveraging the status block of the Custom Resource Configuration of the workload • Operator provides configuration via the spec section of the Custom Resource • Operator reconciles configuration and updates to it with the status of the managed resources Upgrade of the managed workload • Operand can be upgraded in the process of upgrading the Operator, or • Operand can be upgraded

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Watches shared state through apiserver • Makes changes from current to desired • Policy-based workload scheduler • Topology aware • Assists with availability, performance and capacity • Affinity/Anti-Affinity VMs: Run & Move Containers Ÿ Kubernetes: Manage Container workload, Desired State Management, Decouple Service Interfaces & Backedn Workload Ÿ PKS: Manage Kubernetes Lifecycle & Underline Infrastructure

Cloud Native batch system (Volcano) development • IBM spectrum computing - Cluster resource and workload scheduling platform development l Gaps for Spark • Agenda l Why Spark on Kubernetes l Volcano proportion/namespace fair-share, job fair-share to share resource l Use task-topology to improve the spark workload efficiency. Summary p Queue priority p Queue reclaim p Queue plugin p Hierarchical queue p

NUMA? Memory intensive workloads Nearly all database servers (e.g. Oracle, MongoDB), present a workload which will attempt to detect and consume as much of the system’s memory as possible. Where does 14 Using a NUMA aware hypervisor to solve issues now VM composition guidelines • Assuming you workload fits with the footprint of a single node, compose worker node VMs as “walled gardens” corresponding