AnthonyByansi / ElastiCore

"ElastiCore" - A fault-tolerant distributed system in Go for massive data processing with data replication, load balancing, and scalability support.

ElastiCore - Fault-Tolerant Distributed Data Processing System in Go

📜 Introduction

ElastiCore is a robust and scalable fault-tolerant distributed system built in Go, designed to handle massive data processing with efficiency and resilience.

🎯 Key Features

• ✅ Fault Tolerance: Implements the Raft consensus algorithm for master node replication, ensuring high availability and reliability.
• ✅ Data Replication: Includes data replication mechanisms for enhanced data durability in case of node failures.
• ✅ Load Balancing: Utilizes a load balancer to evenly distribute incoming requests, optimizing resource utilization.
• ✅ Scalability: Easily scales horizontally by adding more worker nodes or master nodes to accommodate growing data processing demands.
• ✅ Security: Incorporates authentication and encryption for secure data transmission and access control.

🚀 How it Works

flowchart LR
    subgraph Master Node
    A[Master] -->|Task Distribution| B((Worker 1))
    A[Master] -->|Task Distribution| C((Worker 2))
    A[Master] -->|Task Distribution| D((Worker 3))
    end

    subgraph Worker Nodes
    B((Worker 1)) -->|Data Processing| E((Result 1))
    C((Worker 2)) -->|Data Processing| F((Result 2))
    D((Worker 3)) -->|Data Processing| G((Result 3))
    end

    subgraph Load Balancer
    H[Load Balancer] --> A[Master]
    end

    subgraph Data Storage
    E((Result 1)) -->|Data Replication| I((Data Store 1))
    F((Result 2)) -->|Data Replication| I((Data Store 1))
    G((Result 3)) -->|Data Replication| I((Data Store 1))
    end

    subgraph Clients
    J[Client 1] -->|Data Request| H[Load Balancer]
    J[Client 1] -->|Data Request| H[Load Balancer]
    J[Client 1] -->|Data Request| H[Load Balancer]
    end

• 💡 The "ElastiCore" system is orchestrated by the 🧠 "Master" node, which intelligently distributes tasks to 🛠️ "Worker" nodes.

• 💪 Each "Worker" node processes the assigned tasks with determination and produces valuable "Results." 🛠️

• ⚖️ The "Load Balancer" efficiently distributes incoming client requests across multiple "Master" nodes, ensuring fairness and resource optimization. ⚙️

• 📁 Data Replication: The processed 📊Results are replicated and stored in a 🗄️Data Store to ensure data durability and resilience in the face of potential failures.

• 💻 Client Interaction: 🧑‍💻Clients interact with the system by sending data processing requests to the 🚦Load Balancer, initiating the data processing workflow.

🔧 Installation and Usage

Refer to the documentation for installation instructions and detailed usage guidelines.

🧪 Testing

Run unit and integration tests using go test in the root directory.

📚 Documentation

For a high-level overview of the system architecture, API reference, and troubleshooting guide, check out our documentation.

📝 Contributing

Contributions are welcome! Please read our contribution guidelines before submitting a pull request.

📃 License

This project is licensed under the MIT License.

📞 Contact

Have questions or suggestions? Feel free to reach out to us at [e-mail].(In Review)

Let's build the future of data processing together! 🌟