From 908f68b0560de594025a88056be6e9ebf9f5f0dc Mon Sep 17 00:00:00 2001 From: lilin90 Date: Sat, 14 Sep 2024 15:54:52 +0800 Subject: [PATCH] v1.3: remove the auto scaling doc --- en/enable-tidb-cluster-auto-scaling.md | 221 ------------------------- en/tidb-operator-overview.md | 1 + zh/enable-tidb-cluster-auto-scaling.md | 217 ------------------------ zh/tidb-operator-overview.md | 1 + 4 files changed, 2 insertions(+), 438 deletions(-) delete mode 100644 en/enable-tidb-cluster-auto-scaling.md delete mode 100644 zh/enable-tidb-cluster-auto-scaling.md diff --git a/en/enable-tidb-cluster-auto-scaling.md b/en/enable-tidb-cluster-auto-scaling.md deleted file mode 100644 index 439b496ce5..0000000000 --- a/en/enable-tidb-cluster-auto-scaling.md +++ /dev/null @@ -1,221 +0,0 @@ ---- -title: Enable TiDB Cluster Auto-scaling in Kubernetes -summary: Learn how to use the TidbCluster auto-scaling feature. ---- - -# Enable TiDB Cluster Auto-scaling in Kubernetes - -TiDB has implemented an auto-scaling mechanism since v5.0 based on Kubernetes. You can enable the auto-scaling feature in TiDB Operator. This document introduces how to enable and use the auto-scaling feature for a TiDB cluster in Kubernetes. - -> **Warning:** -> -> * The auto-scaling feature is in the alpha stage. It is highly **not recommended** to enable this feature in the critical production environment. -> * It is recommended to try this feature in a test environment. PingCAP welcomes your comments and suggestions to help improve this feature. -> * Currently, the auto-scaling feature is based solely on CPU utilization. - -## Enable the auto-scaling feature - -The auto-scaling feature is disabled by default. To enable this feature, perform the following steps: - -1. Edit the `values.yaml` file of TiDB Operator and enable `AutoScaling` in the `features` option: - - ```yaml - features: - - AutoScaling=true - ``` - -2. Update TiDB Operator to make the configuration take effect. - - {{< copyable "shell-regular" >}} - - ```shell - helm upgrade tidb-operator pingcap/tidb-operator --version=${chart_version} --namespace=tidb-admin -f ${HOME}/tidb-operator/values-tidb-operator.yaml - ``` - -3. Confirm the resource configuration of the target TiDB cluster. - - Before using the auto-scaling feature on the target TiDB cluster, you need to configure the CPU setting of the corresponding components. For example, you need to configure `spec.tikv.requests.cpu` in TiKV: - - ```yaml - spec: - tikv: - requests: - cpu: "1" - tidb: - requests: - cpu: "1" - ``` - -## Define the auto-scaling behavior - -To define the auto-scaling behavior in the TiDB cluster, configure the `TidbClusterAutoScaler` CR object. The following is an example: - -```yaml -apiVersion: pingcap.com/v1alpha1 -kind: TidbClusterAutoScaler -metadata: - name: auto-scaling-demo -spec: - cluster: - name: auto-scaling-demo - tikv: - resources: - storage_small: - cpu: 1000m - memory: 2Gi - storage: 10Gi - count: 3 - rules: - cpu: - max_threshold: 0.8 - min_threshold: 0.2 - resource_types: - - storage_small - scaleInIntervalSeconds: 500 - scaleOutIntervalSeconds: 300 - tidb: - resources: - compute_small: - cpu: 1000m - memory: 2Gi - count: 3 - rules: - cpu: - max_threshold: 0.8 - min_threshold: 0.2 - resource_types: - - compute_small -``` - -### Implementation principles - -According to the configuration of the `TidbClusterAutoScaler` CR, TiDB Operator sends requests to PD to query the result of scaling. Based on the result, TiDB Operator makes use of the [heterogeneous cluster](deploy-heterogeneous-tidb-cluster.md) feature to create, update, or delete the heterogeneous TiDB cluster (only the TiDB component or the TiKV component is configured). In this way, the auto-scaling of the TiDB cluster is achieved. - -### Related fields - -* `spec.cluster`: the TiDB cluster to be elastically scheduled. - - * `name`: the name of the TiDB cluster. - * `namespace`: the namespace of the TiDB cluster. If not configured, this field is set to the same namespace as the `TidbClusterAutoScaler` CR by default. - -* `spec.tikv`: the configuration related to TiKV elastic scheduling. -* `spec.tikv.resources`: the resource types that TiKV can use for elastic scheduling. If not configured, this field is set to the same value as `spec.tikv.requests` in the `TidbCluster` CR corresponding to `spec.cluster`. - - * `cpu`: CPU configuration. - * `memory`: memory configuration. - * `storage`: storage configuration. - * `count`: the number of resources that the current configuration can use. If this field is not configured, there is no limit on resources. - -* `spec.tikv.rules`: the rules of TiKV elastic scheduling. Currently only CPU-based rules are supported. - - * `max_threshold`: If the average CPU utilization of all Pods is higher than `max_threshold`, the scaling-out operation is triggered. - * `min_threshold`: If the average CPU utilization of all Pods is lower than `min_threshold`, the scaling-in operation is triggered. - * `resource_types`: the resource types that can be used for CPU-based elastic scheduling. This field corresponds to `key` in `spec.tikv.resources[]`. If not configured, this field is set to all `key`s in `spec.tikv.resources[]` by default. - -* `spec.tikv.scaleInIntervalSeconds`: the interval between this scaling-in operation and the last scaling in/out operation. If not configured, the field is set to `500` by default, which means 500 seconds. -* `spec.tikv.scaleOutIntervalSeconds`: the interval between this scaling-out operation and the last scaling in/out operation. If not configured, the field is set to `300` by default, which means 300 seconds. -* `spec.tidb`: the configuration related to TiDB elastic scheduling. Other fields are the same as `spec.tikv`. - -For more information about configuration fields, refer to [API references](https://github.com/pingcap/tidb-operator/blob/master/docs/api-references/docs.md#basicautoscalerspec). - -## Example - -1. Run the following commands to quickly deploy a TiDB cluster with 3 PD instances, 3 TiKV instances, 2 TiDB instances, and the monitoring and the auto-scaling features. - - {{< copyable "shell-regular" >}} - - ```shell - kubectl apply -f https://raw.githubusercontent.com/pingcap/tidb-operator/v1.3.10/examples/auto-scale/tidb-cluster.yaml -n ${namespace} - ``` - - {{< copyable "shell-regular" >}} - - ```shell - kubectl apply -f https://raw.githubusercontent.com/pingcap/tidb-operator/v1.3.10/examples/auto-scale/tidb-monitor.yaml -n ${namespace} - ``` - - {{< copyable "shell-regular" >}} - - ```shell - kubectl apply -f https://raw.githubusercontent.com/pingcap/tidb-operator/v1.3.10/examples/auto-scale/tidb-cluster-auto-scaler.yaml -n ${namespace} - ``` - -2. Prepare data using [sysbench](https://github.com/akopytov/sysbench). - - Copy the following content and paste it to the local `sysbench.config` file: - - {{< copyable "" >}} - - ```config - mysql-host=${tidb_service_ip} - mysql-port=4000 - mysql-user=root - mysql-password= - mysql-db=test - time=120 - threads=20 - report-interval=5 - db-driver=mysql - ``` - - Prepare data by running the following command: - - {{< copyable "shell-regular" >}} - - ```shell - sysbench --config-file=${path}/sysbench.config oltp_point_select --tables=1 --table-size=20000 prepare - ``` - -3. Start the stress test: - - {{< copyable "shell-regular" >}} - - ```shell - sysbench --config-file=${path}/sysbench.config oltp_point_select --tables=1 --table-size=20000 run - ``` - - The command above will return the following result: - - ```sh - Initializing worker threads... - - Threads started! - - [ 5s ] thds: 20 tps: 37686.35 qps: 37686.35 (r/w/o: 37686.35/0.00/0.00) lat (ms,95%): 0.99 err/s: 0.00 reconn/s: 0.00 - [ 10s ] thds: 20 tps: 38487.20 qps: 38487.20 (r/w/o: 38487.20/0.00/0.00) lat (ms,95%): 0.95 err/s: 0.00 reconn/s: 0.00 - ``` - -4. Create a new terminal session and view the Pod changing status of the TiDB cluster by running the following command: - - {{< copyable "shell-regular" >}} - - ```shell - watch -n1 "kubectl -n ${namespace} get pod" - ``` - - The output is as follows: - - ```sh - auto-scaling-demo-discovery-fbd95b679-f4cb9 1/1 Running 0 17m - auto-scaling-demo-monitor-6857c58564-ftkp4 3/3 Running 0 17m - auto-scaling-demo-pd-0 1/1 Running 0 17m - auto-scaling-demo-tidb-0 2/2 Running 0 15m - auto-scaling-demo-tidb-1 2/2 Running 0 15m - auto-scaling-demo-tikv-0 1/1 Running 0 15m - auto-scaling-demo-tikv-1 1/1 Running 0 15m - auto-scaling-demo-tikv-2 1/1 Running 0 15m - ``` - - View the changing status of Pods and the TPS and QPS of sysbench. When new Pods are created in TiKV and TiDB, the TPS and QPS of sysbench increase significantly. - - After sysbench finishes the test, the newly created Pods in TiKV and TiDB disappear automatically. - -5. Destroy the environment by running the following commands: - - {{< copyable "shell-regular" >}} - - ```shell - kubectl delete tidbcluster auto-scaling-demo -n ${namespace} - kubectl delete tidbmonitor auto-scaling-demo -n ${namespace} - kubectl delete tidbclusterautoscaler auto-scaling-demo -n ${namespace} - ``` diff --git a/en/tidb-operator-overview.md b/en/tidb-operator-overview.md index a4b8d7f53e..9db14bbfd8 100644 --- a/en/tidb-operator-overview.md +++ b/en/tidb-operator-overview.md @@ -1,6 +1,7 @@ --- title: TiDB Operator Overview summary: Learn the overview of TiDB Operator. +aliases: ['/tidb-in-kubernetes/v1.3/enable-tidb-cluster-auto-scaling'] --- # TiDB Operator Overview diff --git a/zh/enable-tidb-cluster-auto-scaling.md b/zh/enable-tidb-cluster-auto-scaling.md deleted file mode 100644 index e7c39810bb..0000000000 --- a/zh/enable-tidb-cluster-auto-scaling.md +++ /dev/null @@ -1,217 +0,0 @@ ---- -title: 对 Kubernetes 上的 TiDB 集群启用自动弹性伸缩 -summary: 介绍如何对 Kubernetes 上的 TiDB 集群启用自动弹性伸缩。 ---- - -# 对 Kubernetes 上的 TiDB 集群启用自动弹性伸缩 - -基于 Kubernetes，TiDB 自 v5.0 起支持了全新的弹性伸缩算法，支持在 TiDB Operator 中开启自动弹性伸缩。本文介绍如何对 Kubernetes 上的 TiDB 集群开启和使用自动弹性伸缩。 - -> **警告：** -> -> * Kubernetes 上的 TiDB 集群自动弹性伸缩目前仍处于 Alpha 阶段，极其不推荐在关键、生产环境开启该特性。 -> * 推荐在测试环境中体验该特性，并反馈相关的建议与问题，帮助我们更好地提高这一特性。 -> * 目前仅支持基于 CPU 利用率的弹性伸缩。 - -## 开启弹性伸缩特性 - -TiDB Operator 的弹性伸缩特性默认关闭，要启用弹性伸缩特性，请执行以下步骤： - -1. 修改 TiDB Operator 的 `values.yaml` 文件，在 `features` 选项中开启 `AutoScaling`。 - - ```yaml - features: - - AutoScaling=true - ``` - -2. 更新 TiDB Operator 使更改生效。 - - {{< copyable "shell-regular" >}} - - ```shell - helm upgrade tidb-operator pingcap/tidb-operator --version=${chart_version} --namespace=tidb-admin -f ${HOME}/tidb-operator/values-tidb-operator.yaml - ``` - -3. 确认目标 TiDB 集群资源设置。 - - 目标 TiDB 集群在使用弹性伸缩前，需要提前设置好对应组件的 CPU。以 TiKV 为例，你需要配置 `spec.tikv.requests.cpu`： - - ```yaml - spec: - tikv: - requests: - cpu: "1" - tidb: - requests: - cpu: "1" - ``` - -## 定义 TiDB 集群的弹性伸缩行为 - -你可以通过 `TidbClusterAutoScaler` CR 对象来控制 TiDB 集群的弹性伸缩行为。 - -示例如下： - -```yaml -apiVersion: pingcap.com/v1alpha1 -kind: TidbClusterAutoScaler -metadata: - name: auto-scaling-demo -spec: - cluster: - name: auto-scaling-demo - tikv: - resources: - storage_small: - cpu: 1000m - memory: 2Gi - storage: 10Gi - count: 3 - rules: - cpu: - max_threshold: 0.8 - min_threshold: 0.2 - resource_types: - - storage_small - scaleInIntervalSeconds: 500 - scaleOutIntervalSeconds: 300 - tidb: - resources: - compute_small: - cpu: 1000m - memory: 2Gi - count: 3 - rules: - cpu: - max_threshold: 0.8 - min_threshold: 0.2 - resource_types: - - compute_small -``` - -### 原理介绍 - -TiDB Operator 会根据 `TidbClusterAutoScaler` CR 的配置，向 PD 发起请求，查询扩缩容结果，并根据 PD 返回的结果，利用[异构集群](deploy-heterogeneous-tidb-cluster.md)特性，创建、更新或者删除异构 TiDB 集群（只配置 TiDB 组件或者只配置 TiKV 组件），实现 TiDB 集群的弹性伸缩。 - -### 字段介绍 - -* `spec.cluster`：需要被弹性调度的 TiDB 集群。 - - * `name`：TiDB 集群名称。 - * `namespace`：TiDB 集群所在的命名空间。如果没有配置 `namespace`，会默认设置为和 `TidbClusterAutoScaler` CR 相同的命名空间。 - -* `spec.tikv`：TiKV 弹性调度相关配置。 -* `spec.tikv.resources`：TiKV 弹性调度可以选择的资源配置类型。如果没有配置，会默认设置为 `spec.cluster` 对应的 TidbCluster CR 中的 `spec.tikv.requests` 资源配置。 - - * `cpu`：CPU 配置。 - * `memory`：内存配置。 - * `storage`：存储配置。 - * `count`：当前资源配置可以使用的数量，如果不配置，则认为没有限制。 - -* `spec.tikv.rules`：TiKV 弹性调度规则，目前只支持 CPU 规则。 - - * `max_threshold`：所有 Pod CPU 平均利用率超过 `max_threshold` 会触发扩容操作。 - * `min_threshold`：所有 Pod CPU 平均利用率低于 `min_threshold` 会触发缩容操作。 - * `resource_types`：配置根据 CPU 规则弹性伸缩时可以使用的资源类型，对应 `spec.tikv.resources[]` 中的 `key`。如果没有配置，默认会设置为 `spec.tikv.resources[]` 中所有的 `key`。 - -* `spec.tikv.scaleInIntervalSeconds`：缩容距离上一次伸缩（扩容或者缩容）的冷却时间，如果没有配置，默认设置为 `500`，即 `500s`。 -* `spec.tikv.scaleOutIntervalSeconds`：扩容距离上一次伸缩（扩容或者缩容）的冷却时间，如果没有配置，默认设置为 `300`，即 `300s`。 -* `spec.tidb`：TiDB 弹性调度相关配置，下面的各个字段和 `spec.tikv` 一样。 - -更多配置字段可以参考 [API 文档](https://github.com/pingcap/tidb-operator/blob/master/docs/api-references/docs.md#basicautoscalerspec)。 - -## 演示示例 - -1. 执行以下命令在 Kubernetes 集群上快速安装一个 1 PD、3 TiKV、2 TiDB，并带有监控与弹性伸缩能力的 TiDB 集群。 - - {{< copyable "shell-regular" >}} - - ```shell - kubectl apply -f https://raw.githubusercontent.com/pingcap/tidb-operator/v1.3.10/examples/auto-scale/tidb-cluster.yaml -n ${namespace} - ``` - - {{< copyable "shell-regular" >}} - - ```shell - kubectl apply -f https://raw.githubusercontent.com/pingcap/tidb-operator/v1.3.10/examples/auto-scale/tidb-monitor.yaml -n ${namespace} - ``` - - {{< copyable "shell-regular" >}} - - ```shell - kubectl apply -f https://raw.githubusercontent.com/pingcap/tidb-operator/v1.3.10/examples/auto-scale/tidb-cluster-auto-scaler.yaml -n ${namespace} - ``` - -2. 使用 [sysbench](https://github.com/akopytov/sysbench) 工具准备数据。 - - 将以下内容复制到 `sysbench.config` 文件中： - - ```config - mysql-host=${tidb_service_ip} - mysql-port=4000 - mysql-user=root - mysql-password= - mysql-db=test - time=120 - threads=20 - report-interval=5 - db-driver=mysql - ``` - - 通过以下命令准备数据： - - {{< copyable "shell-regular" >}} - - ```shell - sysbench --config-file=${path}/sysbench.config oltp_point_select --tables=1 --table-size=20000 prepare - ``` - -3. 通过以下命令开始进行压测： - - {{< copyable "shell-regular" >}} - - ```shell - sysbench --config-file=${path}/sysbench.config oltp_point_select --tables=1 --table-size=20000 run - ``` - - 上述命令执行完毕后，出现如下输出： - - ```sh - Initializing worker threads... - - Threads started! - - [ 5s ] thds: 20 tps: 37686.35 qps: 37686.35 (r/w/o: 37686.35/0.00/0.00) lat (ms,95%): 0.99 err/s: 0.00 reconn/s: 0.00 - [ 10s ] thds: 20 tps: 38487.20 qps: 38487.20 (r/w/o: 38487.20/0.00/0.00) lat (ms,95%): 0.95 err/s: 0.00 reconn/s: 0.00 - ``` - -4. 新建一个会话终端，通过以下命令观察 TiDB 集群的 Pod 变化情况。 - - {{< copyable "shell-regular" >}} - - ```shell - watch -n1 "kubectl -n ${namespace} get pod" - ``` - - 出现如下输出: - - ```sh - auto-scaling-demo-discovery-fbd95b679-f4cb9 1/1 Running 0 17m - auto-scaling-demo-monitor-6857c58564-ftkp4 3/3 Running 0 17m - auto-scaling-demo-pd-0 1/1 Running 0 17m - auto-scaling-demo-tidb-0 2/2 Running 0 15m - auto-scaling-demo-tidb-1 2/2 Running 0 15m - auto-scaling-demo-tikv-0 1/1 Running 0 15m - auto-scaling-demo-tikv-1 1/1 Running 0 15m - auto-scaling-demo-tikv-2 1/1 Running 0 15m - ``` - - 观察 Pod 的变化情况和 sysbench 的 TPS 与 QPS，当 TiKV 与 TiDB Pod 新增时，sysbench 的 TPS 与 QPS 值有显著提升。当 sysbench 结束后，观察 Pod 变化情况，发现新增的 TiKV 与 TiDB Pod 自动消失。 - -5. 使用如下命令销毁环境： - - ```shell - kubectl delete tidbcluster auto-scaling-demo -n ${namespace} - kubectl delete tidbmonitor auto-scaling-demo -n ${namespace} - kubectl delete tidbclusterautoscaler auto-scaling-demo -n ${namespace} - ``` diff --git a/zh/tidb-operator-overview.md b/zh/tidb-operator-overview.md index e80b765f3c..a6ab88f92c 100644 --- a/zh/tidb-operator-overview.md +++ b/zh/tidb-operator-overview.md @@ -1,6 +1,7 @@ --- title: TiDB Operator 简介 summary: 介绍 TiDB Operator 的整体架构及使用方式。 +aliases: ['/zh/tidb-in-kubernetes/v1.3/enable-tidb-cluster-auto-scaling'] --- # TiDB Operator 简介