Attention Students! Join KubeSphere in OSPP 2025 — The Wonder Journey of Open Source Continues!

4 min readMay 15, 2025

The Summer of Open Source is a seasonal open-source initiative launched and long supported by the “Open Source Software Supply Chain Illumination Program” of the Institute of Software, Chinese Academy of Sciences. Its goal is to encourage students to actively participate in the development and maintenance of open-source software, cultivate and discover outstanding developers, promote the vigorous development of top-tier open-source communities, and contribute to the construction of the open-source software supply chain.

Since the inception of Summer of Open Source, the KubeSphere community has participated for four consecutive years, mentoring a total of 25 students across projects including KubeSphere, KubeKey, OpenFunction, and other core subprojects.

View Previous Projects:

Project Overview

For Summer of Open Source 2025, the KubeSphere community is releasing two advanced project tasks focused on AI and Kubernetes, inviting students from around the world to apply. Selected students will receive one-on-one mentorship from community experts, with opportunities to earn completion bonuses and long-term contribution opportunities.

Project 1: KubeSphere Community Q&A AI Assistant Based on LangGraph

Project Link:
https://summer-ospp.ac.cn/org/prodetail/256690088?list=org&navpage=org

Project Goal
Develop an intelligent Q&A system using LangGraph and the Milvus vector database, integrating KubeSphere’s knowledge base, documentation, and FAQs to build an Agentic RAG workflow. This will provide users with accurate and real-time technical support, improving the community experience and support efficiency.

Project Background
With the rapid growth of the KubeSphere community, the demand for technical support and Q&A is increasing. Traditional document retrieval and manual support are no longer sufficient. Leveraging LLMs and vector databases to build an Agentic RAG-based AI assistant can significantly improve community support, enabling users to access accurate technical information quickly while easing the burden on maintainers.

Project Difficulty: Advanced

Project Mentor

Haili Zhang
Email: haili.zhang@outlook.com

Development Scope

Build a knowledge base from KubeSphere docs, GitHub issues, and community discussions
Use Milvus for storing and indexing document content
Design an Agentic RAG workflow using LangGraph to handle the full Q&A pipeline
Develop adaptive retrieval strategies to enhance response relevance and accuracy
Build API interfaces to integrate the Q&A system with the KubeSphere console
Implement a context-aware dialogue system supporting multi-turn conversations

Tech Stack

Use LangGraph to implement workflows for query analysis, document retrieval, answer generation, and self-verification
Leverage Milvus for efficient similarity search across large document sets
Deploy open-source language models (e.g., Qwen2.5, GLM-4) to ensure availability and performance
Build a feedback mechanism for continuous quality improvement
Support multilingual capabilities for global users

Project 2: Implementing CodeSpace Functionality on KubeSphere

Project Link:
https://summer-ospp.ac.cn/org/prodetail/256690520?list=org&navpage=org

Project Goal
Implement a GitHub CodeSpace-like online web IDE using vscode-server, providing enhanced services in KubeSphere’s private cloud environments.

Project Background
GitHub CodeSpace is an innovative feature that supports the DevContainer protocol, enabling automatic development environment setup. It is very beginner-friendly and helps developers focus more on coding by removing setup hassles.

In private cloud environments, a lightweight CodeSpace is particularly useful for internal enterprise projects. This project will enable such functionality in KubeSphere.

Project Difficulty: Advanced

Project Mentor

Zhenfei Pei
Email: peizhenfei@cvte.com

Development Scope

Define a custom CRD to describe the full project configuration
Create configuration files in projects similar to DevContainer format
Develop an Operator to monitor CRDs and create DEV PODs accordingly
Use shared storage to store and persist source code

Tech Stack

Develop the Kubernetes Operator in Python
Design custom CRD schemas with reasonable defaults
Build a KubeSphere plugin for a simple frontend interface
Ensure support for at least Python, Java, and Node.js projects

Project Bonuses

Depending on the project difficulty, students can earn the following:

Advanced Project Completion Bonus: ¥12,000 (pre-tax)
Basic Project Completion Bonus: ¥8,000 (pre-tax)

Event Timeline

May 9 — June 9: Student-mentor communication & project application submission
June 10 — June 24: Application review (each student may apply for only one project)
June 25: Announcement of selected candidates

Students interested in the above two projects are welcome to directly contact the project mentors via email to discuss project details in advance and increase their chances of being selected!

👉 Project Application Portal