Cloud Native 7 min read

What’s New in SREWorks v1.4? Monorepo Frontend Revamp and Offline Install Guide

SREWorks v1.4 introduces a Monorepo‑based frontend architecture, upgrades build tools to Webpack 5 and Rollup, adds an offline installation baseline with pre‑packaged images, and provides detailed Helm commands for upgrading and deploying the platform in cloud‑native environments.

Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
What’s New in SREWorks v1.4? Monorepo Frontend Revamp and Offline Install Guide

1. Frontend Monorepo Refactor

After version v1.3, the SREWorks team collected extensive user feedback and decided to enhance offline installation capabilities while reorganizing the frontend engineering architecture. The project now follows a Monorepo model (single repository with multiple packages) using lerna and yarn workspace, splitting the code into a main package @sreworks/app and four sub‑packages: @sreworks/components, @sreworks/widgets, @sreworks/framework, and @sreworks/shared-utils.

Directory structure
Directory structure

Clearer module structure and dependency relationships.

Fine‑grained independent build units enable collaborative development and separate release cycles.

More efficient code reuse.

The build tools were also upgraded: the main package now uses Webpack 5, while sub‑packages use Rollup. Build time dropped from 74 seconds in v1.3 to 23 seconds (‑68 %), and bundle size was reduced from 5.4 MB to 1.6 MB (‑70 %).

2. Offline Installation

Earlier versions required internal Maven and PIP sources for a second‑stage build, which many users found problematic. In v1.4 the entire base (appId: flycore) is published to the Operations Marketplace, allowing the image and metadata to be treated as a "deployment baseline" embedded in the open‑source code.

The image list (59 images, ~5.9 GB) is maintained at GitHub . A rectangular tree diagram visualizes the images by size:

Image size tree
Image size tree

Example offline deployment commands (image registry set to sreworks.io/hub-test):

# Clone SREWorks
git clone http://github.com/alibaba/sreworks.git -b v1.4 sreworks
cd sreworks/chart/sreworks-chart

# Install SREWorks via Helm
helm install sreworks ./ \
  --create-namespace --namespace sreworks \
  --set global.accessMode="nodePort" \
  --set global.images.tag="v1.4" \
  --set appmanager.home.url="http://localhost:30767" \
  --set saas.onlyBase=true \
  --set global.images.registry="sreworks.io/hub-test" \
  --set global.images.imagePullPolicy="IfNotPresent" \
  --set appmanagerbase.kruise.manager.image.repository="sreworks.io/hub-test/kruise-manager" \
  --set appmanagerbase.mysql.image.registry="sreworks.io" \
  --set appmanagerbase.mysql.image.repository="hub-test/mysql" \
  --set appmanagerbase.zookeeper.image.registry="sreworks.io" \
  --set appmanagerbase.zookeeper.image.repository="hub-test/zookeeper" \
  --set appmanagerbase.redis.image.registry="sreworks.io" \
  --set appmanagerbase.redis.image.repository="hub-test/redis" \
  --set appmanagerbase.minio.image.registry="sreworks.io" \
  --set appmanagerbase.minio.image.repository="hub-test/minio"

3. Other Improvements

AppManager Kankio build logic optimized.

Default storage switched to rancher/local-path-provisioner, removing OpenEBS dependency.

SkyWalking upgraded from 8.5.0 to 9.3.0, fixing ES index initialization errors.

4. Upgrade Path to v1.4

Upgrading includes the base; the UI may be unavailable for 5‑10 minutes.

User‑developed cloud‑native applications remain unaffected (no restart), but SREWorks gateway traffic will be interrupted.

git clone http://github.com/alibaba/sreworks.git -b v1.4 sreworks
cd sreworks
./sbin/upgrade-cluster.sh --kubeconfig="****"

For issues, please open an Issue or submit a Pull Request on the GitHub repository.

SREWorks open‑source address: https://github.com/alibaba/sreworks

cloud-nativeMonorepoHelmoffline installationSREWorks
Alibaba Cloud Big Data AI Platform
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Alibaba Cloud Big Data AI Platform

The Alibaba Cloud Big Data AI Platform builds on Alibaba’s leading cloud infrastructure, big‑data and AI engineering capabilities, scenario algorithms, and extensive industry experience to offer enterprises and developers a one‑stop, cloud‑native big‑data and AI capability suite. It boosts AI development efficiency, enables large‑scale AI deployment across industries, and drives business value.

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