•Rack •NetworkDevice •ComputeAsset •Region/AZ •NetworkScope Provision •OS •Flavor •ComputeNode Configuration •Kernel params •Environment config •Network Kubernetes •Core components •Addon •Taint Operations Kubernetes Onboard Provision Configuration Kubernetes You need onboard something from nothing! Let’s model a datacenter running Kubernetes Onboard Provision Configuration Kubernetes After you define + Flavor + OS = ComputeNode Let’s model a datacenter running Kubernetes Onboard Provision Configuration Kubernetes After you define your fleet, you want a accessible compute node: Asset + Flavor +

1.4.8 <configuration> ilovejava.io/petclinic-app ${project.version} configuration> Project ilovejava.io/petclinic-app build Docker daemon build Docker context generate Extended Configuration JVM flags credentials labels environment variables extra files filesystem And a container configuration Tarball A Tarball B Tarball C /bin /usr /tmp /var /jdk /app.jar Environment variables, entrypoint, etc. Container configuration github.com/GoogleContainerTools/jib

"clickhouse.altinity.com/v1" kind: "ClickHouseInstallation" metadata: name: "demo-01" spec: configuration: clusters: - name: "demo" Здесь нет storage Еще вернемся к этому kubectl – наше всё "clickhouse.altinity.com/v1" kind: "ClickHouseInstallation" metadata: name: "demo-01" spec: configuration: clusters: - name: "demo" layout: shardsCount: 2 replicasCount: "clickhouse.altinity.com/v1" kind: "ClickHouseInstallation" metadata: name: "demo-01" spec: configuration: users: demo/password: secret demo/profile: default demo/networks/ip: "::/0"

Google does GKE On-Prem ● Turn-key, production-grade, conformant Kubernetes with best-practice configuration ● Easy upgrade path to the latest Kubernetes releases that have been validated and tested On-Prem ● Cluster environments are consistent (k8s version, OS image, plug-ins, components configuration) Orchestrate and manage on-prem containers just like GKE in the cloud Consistent operating Installation and Configuration $ gke-on-prem create cluster --dry-run Welcome! This command will take you through the installation of a cluster. --dry-run saves your configuration to a YAML file. Please

clean up finished build tasks after if finishes CronJob Spec schedule Cron style scheduler configuration concurrencyPolicy Job Template Concurrency policy of CronJob suspend Whether suspend latter Operator DevOps Service DevOps Manager CronJob k8s API MySQL k8s API MySQL MySQL • Pipeline configuration and history in MySQL • Logging in central logging service - ElasticSearch • Metric data in Update jobs status to buildjob Submit buildjob List/Watch buildjob Pod Pod Pod Pod Build task configuration - map to k8s Job, can also be a raw k8s job Job / Pod / Node info BuildJob / Job status Pipeline

"annotations": { "key1" : "value1", "key2" : "value2" } 类似以下信息可记录到Annotation中： 由declarative configuration layer管理的字段。将这些字段附加为Annotation，可将它们与客户端或服务器设置的默 认值、⾃动⽣成的字段或以及auto-sizing或auto-scaling的系统所设置的字段区分开。 原⽂ https://kubernetes.io/docs/concepts/workloads/controllers/daemonset/ 18-Daemon Set 78 Configuration Best Practices 本⽂档强调并整合了整个⽤户指南、⼊⻔⽂档和示例中引⼊的配置最佳实践。 这是⼀个“活”的⽂件。如果你想到的东⻄不在这个名单上，但可能对他⼈有⽤，请不要犹豫，提交issue或提交PR（pull 快速创建和暴露单个容器部署。有关示例，请参阅quick start guide 。 19-配置最佳实践 80 原⽂ https://kubernetes.io/docs/concepts/configuration/overview/ 19-配置最佳实践 81 Managing Compute Resources for Containers（管理容 器的计算资源） 译者按：本节中，笔者将r

2nd component - componentName: redis Open Application Model Platform 部署 应用配置 （Application Configuration） 面向应用维度配置运维能力与组件 apiVersion: core.oam.dev/v1alpha2 kind: TraitDefinition metadata: name: virtualservices Binding Rollout Ingress interpretability Infra Ops Application Configuration Application Configuration Application Configuration PaaS A PaaS B Serverless C Components Traits Components Traits

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 Operand • Operator is able to restore a backup of an Operand • Operator orchestrates complex re- configuration flows on the Operand • Operator implements fail-over and fail-back of clustered Operands •

Automatic service discovery allows engineers to not maintain any configuration for multi-data center deployments. Easy Configuration • Save 60% infrastructure cost per year per country. Cost-effective