caicancai commented on code in PR #810: URL: https://github.com/apache/flink-kubernetes-operator/pull/810#discussion_r1584453151
########## docs/content.zh/docs/concepts/overview.md: ########## @@ -24,78 +24,96 @@ specific language governing permissions and limitations under the License. --> -# Overview -Flink Kubernetes Operator acts as a control plane to manage the complete deployment lifecycle of Apache Flink applications. Although Flink’s native Kubernetes integration already allows you to directly deploy Flink applications on a running Kubernetes(k8s) cluster, [custom resources](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/) and the [operator pattern](https://kubernetes.io/docs/concepts/extend-kubernetes/operator/) have also become central to a Kubernetes native deployment experience. - -Flink Kubernetes Operator aims to capture the responsibilities of a human operator who is managing Flink deployments. Human operators have deep knowledge of how Flink deployments ought to behave, how to start clusters, how to deploy jobs, how to upgrade them and how to react if there are problems. The main goal of the operator is the automation of these activities, which cannot be achieved through the Flink native integration alone. - -## Features -### Core -- Fully-automated [Job Lifecycle Management]({{< ref "docs/custom-resource/job-management" >}}) - - Running, suspending and deleting applications - - Stateful and stateless application upgrades - - Triggering and managing savepoints - - Handling errors, rolling-back broken upgrades -- Multiple Flink version support: v1.15, v1.16, v1.17, v1.18 +<a name="overview"></a> + +# 概述 +Flink Kubernetes Operator 扮演控制平面的角色，用于管理 Apache Flink 应用程序的完整部署生命周期。尽管 Flink 的原生 Kubernetes 集成已经允许你直接在运行的 Kubernetes(k8s) 集群上部署 Flink 应用程序，但 [自定义资源](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/) 和 [operator 模式](https://kubernetes.io/docs/concepts/extend-kubernetes/operator/) 也已成为 Kubernetes 本地部署体验的核心。 + +Flink Kubernetes Operator 旨在承担管理 Flink deployments，这是 human operator 的职责。Human Operators 对 Flink 部署应该如何运行、如何启动集群、如何部署作业、如何升级作业以及出现问题时如何反应有着深入的了解。Operator 的主要目标是使这些活动自动化，而这无法仅通过 Flink 原生集成来实现。 + + +<a name="features"></a> + +## 特征 + +<a name="core"></a> + +### 核心 +- 全自动 [Job Lifecycle Management]({{< ref "docs/custom-resource/job-management" >}}) + - 运行、暂停和删除应用程序 + - 有状态和无状态应用程序升级 + - 保存点的触发和管理 + - 处理错误，回滚失败的升级 + - 多 Flink 版本支持：v1.15, v1.16, v1.17, v1.18 - [Deployment Modes]({{< ref "docs/custom-resource/overview#application-deployments" >}}): - - Application cluster - - Session cluster - - Session job + - 应用程序集群 + - 会话集群 + - 会话作业 - Built-in [High Availability](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/ha/kubernetes_ha/) - Extensible framework - [Custom validators]({{< ref "docs/operations/plugins#custom-flink-resource-validators" >}}) - [Custom resource listeners]({{< ref "docs/operations/plugins#custom-flink-resource-listeners" >}}) - Advanced [Configuration]({{< ref "docs/operations/configuration" >}}) management - - Default configurations with dynamic updates - - Per job configuration - - Environment variables + - 默认配置与动态更新 + - 作业配置 + - 任务管理器配置 - POD augmentation via [Pod Templates]({{< ref "docs/custom-resource/pod-template" >}}) - - Native Kubernetes POD definitions - - Layering (Base/JobManager/TaskManager overrides) + - 原生Kubernetes POD定义 + - 用于自定义容器和资源 - [Job Autoscaler]({{< ref "docs/custom-resource/autoscaler" >}}) - - Collect lag and utilization metrics - - Scale job vertices to the ideal parallelism - - Scale up and down as the load changes -### Operations + - 收集延迟和利用率指标 + - 将作业顶点调整到合适的并行度 + - 根据负载的变化进行扩展和缩减 + +<a name="operations"></a> + +### 运营 - Operator [Metrics]({{< ref "docs/operations/metrics-logging#metrics" >}}) - - Utilizes the well-established [Flink Metric System](https://nightlies.apache.org/flink/flink-docs-master/docs/ops/metrics) - - Pluggable metrics reporters - - Detailed resources and kubernetes api access metrics + - 使用成熟的 [Flink Metric System](https://nightlies.apache.org/flink/flink-docs-master/docs/ops/metrics) + - 可插拔的指标报告器 + - 详细的资源和 kubernetes api 访问指标 - Fully-customizable [Logging]({{< ref "docs/operations/metrics-logging#logging" >}}) - - Default log configuration - - Per job log configuration - - Sidecar based log forwarders -- Flink Web UI and REST Endpoint Access - - Fully supported Flink Native Kubernetes [service expose types](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/resource-providers/native_kubernetes/#accessing-flinks-web-ui) - - Dynamic [Ingress templates]({{< ref "docs/operations/ingress" >}}) + - 默认日志配置 + - 每个作业日志配置 + - 基于 sidecar 的日志转发器 +- Flink Web UI 和 REST 端点访问 + - 完整支持 Flink 原生 Kubernetes [服务暴露类型](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/resource-providers/native_kubernetes/#accessing-flinks-web-ui) + - 通过 [Ingress 模板]({{< ref "docs/operations/ingress" >}}) 动态暴露服务 - [Helm based installation]({{< ref "docs/operations/helm" >}}) - - Automated [RBAC configuration]({{< ref "docs/operations/rbac" >}}) - - Advanced customization techniques -- Up-to-date public repositories + - 一键部署 + - 高级定制化技术 +- 最新的公共存储库 - GitHub Container Registry [ghcr.io/apache/flink-kubernetes-operator](http://ghcr.io/apache/flink-kubernetes-operator) - DockerHub [https://hub.docker.com/r/apache/flink-kubernetes-operator](https://hub.docker.com/r/apache/flink-kubernetes-operator) -## Built-in Examples +<a name="built-in-examples"></a> + +## 内置示例 -The operator project comes with a wide variety of built in examples to show you how to use the operator functionality. -The examples are maintained as part of the operator repo and can be found [here](https://github.com/apache/flink-kubernetes-operator/tree/main/examples). +Operator 项目提供了各种内置示例，以展示如何使用 Operator 功能。这些示例作为 operator 存储库的一部分进行维护，可以在[这里](https://github.com/apache/flink-kubernetes-operator/tree/main/examples). -**What is covered:** +**涵盖以下:** + - 集群和会话部署 + - 检查点和保存点 + - Java, SQL 和 Python Flink 作业 + - 作业配置和任务管理器配置 Review Comment: yes，sorry removed ########## docs/content.zh/docs/concepts/overview.md: ########## @@ -24,78 +24,96 @@ specific language governing permissions and limitations under the License. --> -# Overview -Flink Kubernetes Operator acts as a control plane to manage the complete deployment lifecycle of Apache Flink applications. Although Flink’s native Kubernetes integration already allows you to directly deploy Flink applications on a running Kubernetes(k8s) cluster, [custom resources](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/) and the [operator pattern](https://kubernetes.io/docs/concepts/extend-kubernetes/operator/) have also become central to a Kubernetes native deployment experience. - -Flink Kubernetes Operator aims to capture the responsibilities of a human operator who is managing Flink deployments. Human operators have deep knowledge of how Flink deployments ought to behave, how to start clusters, how to deploy jobs, how to upgrade them and how to react if there are problems. The main goal of the operator is the automation of these activities, which cannot be achieved through the Flink native integration alone. - -## Features -### Core -- Fully-automated [Job Lifecycle Management]({{< ref "docs/custom-resource/job-management" >}}) - - Running, suspending and deleting applications - - Stateful and stateless application upgrades - - Triggering and managing savepoints - - Handling errors, rolling-back broken upgrades -- Multiple Flink version support: v1.15, v1.16, v1.17, v1.18 +<a name="overview"></a> + +# 概述 +Flink Kubernetes Operator 扮演控制平面的角色，用于管理 Apache Flink 应用程序的完整部署生命周期。尽管 Flink 的原生 Kubernetes 集成已经允许你直接在运行的 Kubernetes(k8s) 集群上部署 Flink 应用程序，但 [自定义资源](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/) 和 [operator 模式](https://kubernetes.io/docs/concepts/extend-kubernetes/operator/) 也已成为 Kubernetes 本地部署体验的核心。 + +Flink Kubernetes Operator 旨在承担管理 Flink deployments，这是 human operator 的职责。Human Operators 对 Flink 部署应该如何运行、如何启动集群、如何部署作业、如何升级作业以及出现问题时如何反应有着深入的了解。Operator 的主要目标是使这些活动自动化，而这无法仅通过 Flink 原生集成来实现。 + + +<a name="features"></a> + +## 特征 + +<a name="core"></a> + +### 核心 +- 全自动 [Job Lifecycle Management]({{< ref "docs/custom-resource/job-management" >}}) + - 运行、暂停和删除应用程序 + - 有状态和无状态应用程序升级 + - 保存点的触发和管理 + - 处理错误，回滚失败的升级 + - 多 Flink 版本支持：v1.15, v1.16, v1.17, v1.18 - [Deployment Modes]({{< ref "docs/custom-resource/overview#application-deployments" >}}): - - Application cluster - - Session cluster - - Session job + - 应用程序集群 + - 会话集群 + - 会话作业 - Built-in [High Availability](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/ha/kubernetes_ha/) - Extensible framework - [Custom validators]({{< ref "docs/operations/plugins#custom-flink-resource-validators" >}}) - [Custom resource listeners]({{< ref "docs/operations/plugins#custom-flink-resource-listeners" >}}) - Advanced [Configuration]({{< ref "docs/operations/configuration" >}}) management - - Default configurations with dynamic updates - - Per job configuration - - Environment variables + - 默认配置与动态更新 + - 作业配置 + - 任务管理器配置 - POD augmentation via [Pod Templates]({{< ref "docs/custom-resource/pod-template" >}}) - - Native Kubernetes POD definitions - - Layering (Base/JobManager/TaskManager overrides) + - 原生Kubernetes POD定义 + - 用于自定义容器和资源 - [Job Autoscaler]({{< ref "docs/custom-resource/autoscaler" >}}) - - Collect lag and utilization metrics - - Scale job vertices to the ideal parallelism - - Scale up and down as the load changes -### Operations + - 收集延迟和利用率指标 + - 将作业顶点调整到合适的并行度 + - 根据负载的变化进行扩展和缩减 + +<a name="operations"></a> + +### 运营 - Operator [Metrics]({{< ref "docs/operations/metrics-logging#metrics" >}}) - - Utilizes the well-established [Flink Metric System](https://nightlies.apache.org/flink/flink-docs-master/docs/ops/metrics) - - Pluggable metrics reporters - - Detailed resources and kubernetes api access metrics + - 使用成熟的 [Flink Metric System](https://nightlies.apache.org/flink/flink-docs-master/docs/ops/metrics) + - 可插拔的指标报告器 + - 详细的资源和 kubernetes api 访问指标 - Fully-customizable [Logging]({{< ref "docs/operations/metrics-logging#logging" >}}) - - Default log configuration - - Per job log configuration - - Sidecar based log forwarders -- Flink Web UI and REST Endpoint Access - - Fully supported Flink Native Kubernetes [service expose types](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/resource-providers/native_kubernetes/#accessing-flinks-web-ui) - - Dynamic [Ingress templates]({{< ref "docs/operations/ingress" >}}) + - 默认日志配置 + - 每个作业日志配置 + - 基于 sidecar 的日志转发器 +- Flink Web UI 和 REST 端点访问 + - 完整支持 Flink 原生 Kubernetes [服务暴露类型](https://nightlies.apache.org/flink/flink-docs-master/docs/deployment/resource-providers/native_kubernetes/#accessing-flinks-web-ui) + - 通过 [Ingress 模板]({{< ref "docs/operations/ingress" >}}) 动态暴露服务 - [Helm based installation]({{< ref "docs/operations/helm" >}}) - - Automated [RBAC configuration]({{< ref "docs/operations/rbac" >}}) - - Advanced customization techniques -- Up-to-date public repositories + - 一键部署 + - 高级定制化技术 +- 最新的公共存储库 - GitHub Container Registry [ghcr.io/apache/flink-kubernetes-operator](http://ghcr.io/apache/flink-kubernetes-operator) - DockerHub [https://hub.docker.com/r/apache/flink-kubernetes-operator](https://hub.docker.com/r/apache/flink-kubernetes-operator) -## Built-in Examples +<a name="built-in-examples"></a> + +## 内置示例 -The operator project comes with a wide variety of built in examples to show you how to use the operator functionality. -The examples are maintained as part of the operator repo and can be found [here](https://github.com/apache/flink-kubernetes-operator/tree/main/examples). +Operator 项目提供了各种内置示例，以展示如何使用 Operator 功能。这些示例作为 operator 存储库的一部分进行维护，可以在[这里](https://github.com/apache/flink-kubernetes-operator/tree/main/examples). -**What is covered:** +**涵盖以下:** + - 集群和会话部署 + - 检查点和保存点 + - Java, SQL 和 Python Flink 作业 + - 作业配置和任务管理器配置 + - 入口、日志记录和指标配置 Review Comment: done -- This is an automated message from the Apache Git Service. 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