Add intro

_IGNORE/_StarRocks_intro.mdx

@@ -0,0 +1,22 @@
+---
+sidebar_label: Intro
+sidebar_position: 1
+---
+import FeatureList from '/src/components/Features/index.js'
+
+# StarRocks
+
+StarRocks is a next-gen, high-performance analytical data warehouse that enables real-time, multi-dimensional, and highly concurrent data analysis. StarRocks has an MPP architecture and is equipped with a fully vectorized execution engine, a columnar storage engine that supports real-time updates, and is powered by a rich set of features including a fully-customized cost-based optimizer (CBO), intelligent materialized view and more. StarRocks supports real-time and batch data ingestion from a variety of data sources. It also allows you to directly analyze data stored in data lakes with zero data migration.
+
+StarRocks is also compatible with MySQL protocols and can be easily connected using MySQL clients and popular BI tools. StarRocks is highly scalable, available, and easy to maintain. It is widely adopted in the industry, powering a variety of OLAP scenarios, such as real-time analytics, ad-hoc queries, data lake analytics and more.
+
+Join our [Slack channel](https://join.slack.com/t/starrocks/shared_invite/zt-z5zxqr0k-U5lrTVlgypRIV8RbnCIAzg) for live support, discussion, or latest community news. You can also follow us on [LinkedIn](https://www.linkedin.com/company/starrocks) to get first-hand updates on new features, events, and sharing.
+
+---
+
+### Popular topics
+
+<FeatureList />
+
+---
+

_IGNORE/card-styles.md

@@ -0,0 +1,53 @@
+./@docusaurus/theme-classic/lib/theme/DocCard/styles.module.css:.cardContainer {
+./@docusaurus/theme-classic/lib/theme/DocCard/styles.module.css:.cardContainer:hover {
+./@docusaurus/theme-classic/lib/theme/DocCard/styles.module.css:.cardContainer *:last-child {
+./@docusaurus/theme-classic/lib/theme/DocCard/index.js:      className={clsx('card padding--lg', styles.cardContainer)}>
+./@docusaurus/theme-classic/src/theme/DocCard/index.tsx:      className={clsx('card padding--lg', styles.cardContainer)}>
+./@docusaurus/theme-classic/src/theme/DocCard/styles.module.css:.cardContainer {
+./@docusaurus/theme-classic/src/theme/DocCard/styles.module.css:.cardContainer:hover {
+./@docusaurus/theme-classic/src/theme/DocCard/styles.module.css:.cardContainer *:last-child {
+
+### This sets the margin above the rows of cards
+
+```html
+<article class="col col--6 margin-bottom--lg">
+```
+
+### This contains all of the rows of cards:
+
+```html
+<section class="row list_node_modules-@docusaurus-theme-classic-lib-theme-DocCategoryGeneratedIndexPage-styles-module">
+```
+
+### This sets the space for a single card and the margin below it:
+
+```html
+<article class="col col--6 margin-bottom--lg">
+```
+
+### This is the card itself:
+
+```html
+<a class="card padding--lg cardContainer_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" href="/docs/introduction/what_is_starrocks">
+```
+
+
+### The card title:
+
+```html
+<h2 class="text--truncate cardTitle_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" title="What is StarRocks?">📄️ What is StarRocks?</h2>
+```
+
+
+### The text for the card (truncated):
+
+```html
+<p class="text--truncate cardDescription_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" title="StarRocks is a next-generation, blazing-fast massively parallel processing (MPP) database designed to make real-time analytics easy for enterprises. It is built to power sub-second queries at scale.">StarRocks is a next-generation, blazing-fast massively parallel processing (MPP) database designed to make real-time analytics easy for enterprises. It is built to power sub-second queries at scale.</p>
+```
+
+
+### Second column:
+
+```html
+</a></article><article class="col col--6 margin-bottom--lg"><a class="card padding--lg cardContainer_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" href="/docs/introduction/Architecture"><h2 class="text--truncate cardTitle_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" title="Architecture">📄️ Architecture</h2><p class="text--truncate cardDescription_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" title="StarRocks has a simple architecture. The entire system consists of only two types of components, frontends (FEs) and backends (BEs). StarRocks does not rely on any external components, simplifying deployment and maintenance. FEs and BEs can be horizontally scaled without service downtime. In addition, StarRocks has a replica mechanism for metadata and service data, which increases data reliability and efficiently prevents single points of failure (SPOFs).">StarRocks has a simple architecture. The entire system consists of only two types of components, frontends (FEs) and backends (BEs). StarRocks does not rely on any external components, simplifying deployment and maintenance. FEs and BEs can be horizontally scaled without service downtime. In addition, StarRocks has a replica mechanism for metadata and service data, which increases data reliability and efficiently prevents single points of failure (SPOFs).</p></a></article><article class="col col--6 margin-bottom--lg"><a class="card padding--lg cardContainer_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" href="/docs/introduction/Features"><h2 class="text--truncate cardTitle_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" title="Features">📄️ Features</h2><p class="text--truncate cardDescription_node_modules-@docusaurus-theme-classic-lib-theme-DocCard-styles-module" title="StarRocks offers a rich set of features to deliver a blazing-fast, real-time analytics experience on data at scale.">StarRocks offers a rich set of features to deliver a blazing-fast, real-time analytics experience on data at scale.</p></a></article></section>
+```

_IGNORE/testbuild-en

@@ -24,12 +24,18 @@ rm -rf ${WORKINGDIR}/versioned_docs/version-2.5
 mkdir ${WORKINGDIR}/versioned_docs/version-2.5
 cp -r docs/* ${WORKINGDIR}/versioned_docs/version-2.5
 
-# cleanup before running yarn build
+echo "cleanup before running yarn build"
 cd ${WORKINGDIR}
 rm -rf temp-en
 rm -rf temp-zh
 find . -type f -name TOC.md | xargs rm
-find . -type f -name StarRocks_intro.md | xargs rm
 
-npx docusaurus-mdx-checker
+echo "replacing StarRocks intro page\n\n"
+find . -type f -name "StarRocks_intro.md"  -print0 -exec cp _IGNORE/_StarRocks_intro.mdx "{}" \;
+
+echo "verifying Markdown"
+npx docusaurus-mdx-checker -c versioned_docs
+npx docusaurus-mdx-checker -c docs
+npx docusaurus-mdx-checker -c i18n
+
 yarn build

docs/examples/home.mdx

@@ -0,0 +1,19 @@
+---
+sidebar_label: Intro
+sidebar_position: 1
+---
+import FeatureList from '/src/components/Features/index.js'
+
+
+# Intro
+
+OLAP is REALLY good.
+
+---
+
+### Popular topics
+
+<FeatureList />
+
+---
+

src/components/Features/index.js

@@ -0,0 +1,136 @@
+import clsx from 'clsx';
+import Heading from '@theme/Heading';
+import styles from './styles.module.css';
+import React from 'react';
+import Link from '@docusaurus/Link';
+import Layout from '@theme/Layout';
+
+const FeatureList = [
+  {
+    title: 'Introduction',
+    url: '../category/introduction-to-starrocks',
+    description: (
+      <>
+        OLAP, features, architecture
+      </>
+    ),
+  },
+  {
+    title: 'Quick Start',
+    url: '../category/quick-start',
+    description: (
+      <>
+        Get up and running quickly.
+      </>
+    ),
+  },
+  {
+    title: 'Data Loading',
+    url: '../loading/Loading_intro',
+    description: (
+      <>
+        Clean, transform, and load
+      </>
+    ),
+  },
+  {
+    title: 'Table Design',
+    url: '../table_design/StarRocks_table_design',
+    description: (
+      <>
+        Tables, indexing, acceleration
+      </>
+    ),
+  },
+  {
+    title: 'Data Lakes',
+    url: '../category/query-data-lakes',
+    description: (
+      <>
+        Iceberg, Hive, Delta Lake, …
+      </>
+    ),
+  },
+  {
+    title: 'Work with semi-structured data',
+    url: '../category/semi-structured',
+    description: (
+      <>
+        JSON, map, struct, array
+      </>
+    ),
+  },
+  {
+    title: 'Integrations',
+    url: '../category/integrations',
+    description: (
+      <>
+        BI tools, IDEs, Cloud authentication, …
+      </>
+    ),
+  },
+  {
+    title: 'Administration',
+    url: '../category/administration',
+    description: (
+      <>
+        Scale, backups, roles and privileges, …
+      </>
+    ),
+  },
+  {
+    title: 'Reference',
+    url: '../category/reference',
+    description: (
+      <>
+        SQL, functions, error codes, …
+      </>
+    ),
+  },
+  {
+    title: 'FAQs',
+    url: '../category/faq',
+    description: (
+      <>
+        Frequently asked questions.
+      </>
+    ),
+  },
+  {
+    title: 'Benchmarks',
+    url: '../category/benchmarks',
+    description: (
+      <>
+        DB performance comparison benchmarks.
+      </>
+    ),
+  },
+];
+
+function Feature({url, title, description}) {
+  return (
+    <div className={clsx('col col--6')}>
+     <Link href={url} target="_self" className="card padding--lg cardContainer_fWXF">
+      <div className="text--center padding-horiz--md">
+        <Heading as="h3">{title}</Heading>
+        <p>{description}</p>
+      </div>
+     </Link>
+    </div>
+  );
+}
+
+
+export default function Features() {
+  return (
+    <section className={styles.features}>
+      <div className="container">
+        <div className="row">
+          {FeatureList.map((props, idx) => (
+            <Feature key={idx} {...props} />
+          ))}
+        </div>
+      </div>
+    </section>
+  );
+}

src/components/Features/styles.module.css

@@ -0,0 +1,11 @@
+.features {
+  display: flex;
+  align-items: center;
+  padding: 2rem 0;
+  width: 100%;
+}
+
+.featureSvg {
+  height: 200px;
+  width: 200px;
+}

versioned_docs/version-2.5/deployment/sr_operator.md

@@ -228,36 +228,41 @@ Run the command `kubectl -n starrocks edit src starrockscluster-sample` to confi
 
 Kubernetes also supports using `behavior` to customize scaling behaviors according to business scenarios, helping you achieve rapid or slow scaling or disable scaling. For more information about automatic scaling policies, see [Horizontal Pod Scaling](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/).
 
-The following is a [template](https://github.com/StarRocks/starrocks-kubernetes-operator/blob/main/examples/starrocks/starrocks-fe-and-cn-with-autoscaler.yaml) provided by StarRocks to help you configure automatic scaling policies:
+The following is a [template](https://github.com/StarRocks/starrocks-kubernetes-operator/blob/main/examples/starrocks/deploy_a_starrocks_cluster_with_cn.yaml) provided by StarRocks to help you configure automatic scaling policies:
 
 ```YAML
   starRocksCnSpec:
-    image: starrocks/cn-ubuntu:3.0-latest
+    image: starrocks/cn-ubuntu:latest
+    limits:
+      cpu: 16
+      memory: 64Gi
     requests:
-      cpu: 4
-      memory: 4Gi
+      cpu: 16
+      memory: 64Gi
     autoScalingPolicy: # Automatic scaling policy of the CN cluster.
       maxReplicas: 10 # The maximum number of CNs is set to 10.
       minReplicas: 1 # The minimum number of CNs is set to 1.
+      # operator creates an HPA resource based on the following field.
+      # see https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/ for more information.
       hpaPolicy:
         metrics: # Resource metrics
           - type: Resource
-            resource: 
-              name: memory # The average memory usage of CNs is specified as a resource metric.
+            resource:
+              name: memory  # The average memory usage of CNs is specified as a resource metric.
               target:
-                averageUtilization: 30 
-                # The elastic scaling threshold is 30%.
-                # When the average memory utilization of CNs exceeds 30%, the number of CNs increases for scale-out.
-                # When the average memory utilization of CNs is below 30%, the number of CNs decreases for scale-in.
+                # The elastic scaling threshold is 60%.
+                # When the average memory utilization of CNs exceeds 60%, the number of CNs increases for scale-out.
+                # When the average memory utilization of CNs is below 60%, the number of CNs decreases for scale-in.
+                averageUtilization: 60
                 type: Utilization
           - type: Resource
-            resource: 
+            resource:
               name: cpu # The average CPU utilization of CNs is specified as a resource metric.
               target:
-                averageUtilization: 60
                 # The elastic scaling threshold is 60%.
                 # When the average CPU utilization of CNs exceeds 60%, the number of CNs increases for scale-out.
                 # When the average CPU utilization of CNs is below 60%, the number of CNs decreases for scale-in.
+                averageUtilization: 60
                 type: Utilization
         behavior: #  The scaling behavior is customized according to business scenarios, helping you achieve rapid or slow scaling or disable scaling.
           scaleUp:

versioned_docs/version-2.5/introduction/StarRocks_intro.md

@@ -0,0 +1,22 @@
+---
+sidebar_label: Intro
+sidebar_position: 1
+---
+import FeatureList from '/src/components/Features/index.js'
+
+# StarRocks
+
+StarRocks is a next-gen, high-performance analytical data warehouse that enables real-time, multi-dimensional, and highly concurrent data analysis. StarRocks has an MPP architecture and is equipped with a fully vectorized execution engine, a columnar storage engine that supports real-time updates, and is powered by a rich set of features including a fully-customized cost-based optimizer (CBO), intelligent materialized view and more. StarRocks supports real-time and batch data ingestion from a variety of data sources. It also allows you to directly analyze data stored in data lakes with zero data migration.
+
+StarRocks is also compatible with MySQL protocols and can be easily connected using MySQL clients and popular BI tools. StarRocks is highly scalable, available, and easy to maintain. It is widely adopted in the industry, powering a variety of OLAP scenarios, such as real-time analytics, ad-hoc queries, data lake analytics and more.
+
+Join our [Slack channel](https://join.slack.com/t/starrocks/shared_invite/zt-z5zxqr0k-U5lrTVlgypRIV8RbnCIAzg) for live support, discussion, or latest community news. You can also follow us on [LinkedIn](https://www.linkedin.com/company/starrocks) to get first-hand updates on new features, events, and sharing.
+
+---
+
+### Popular topics
+
+<FeatureList />
+
+---
+