Fluid

Abstract

1. Introduction

Fluid is an open source Kubernetes-native Distributed Dataset Orchestrator and Accelerator for data-intensive applications, such as big data and AI applications. It is hosted by the Cloud Native Computing Foundation (CNCF) as an incubating project.

Implements the unified abstraction for datasets from multiple storage sources, with observability features to help users evaluate the need for scaling the cache system.

Offers a unified access interface for data operations with different runtimes, enabling access to third-party storage systems.

2. Objective

Fluid, elastic data abstraction and acceleration for BigData/AI applications in cloud. (Project under CNCF)

This project demonstrates how Go, Kubernetes can be applied to a real-world Blockchain & Cloud Computing problem.

3. Key Features / Modules

• Dataset Abstraction
• Scalable Cache Runtime
• Automated Data Operations
• Elasticity and Scheduling
• Runtime Platform Agnostic

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Go 1.20 or later
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/fluid-cloudnative/fluid.git
cd fluid

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Add a CI/CD pipeline with GitHub Actions
• Deploy to a public test network or cloud free tier
• Add monitoring and cost alerts

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Why does this problem need a blockchain or cloud-native design?
2. Explain the smart contract / infrastructure components and how they interact.
3. How are gas costs or cloud costs kept under control?
4. How is the system secured (keys, IAM, access control)?
5. How would the solution scale to many more users?

9. Source Code & License

This project is developed by fluid-cloudnative and published on GitHub under the Apache License 2.0. Please follow the license terms and credit the original author when you use or modify this code.