# CoreState v2.0 - Next-Generation Advanced Backup System

## 1. Executive Summary

CoreState v2.0 is a high-performance, distributed backup system designed for reliability, scalability, and advanced feature support. It leverages a microservices architecture to provide a robust platform for backing up and restoring data across various environments. CoreState v2.0 introduces a sophisticated backup engine, advanced ML-based optimizations, and a modular design to support future enhancements and integrations.

The system is built with a polyglot technology stack, including Rust for the high-performance daemon, Kotlin/Java for backend services, Python for machine learning, and a web-based dashboard for user interaction. It is designed to be cloud-native, with support for Kubernetes deployment and various storage backends.

## 2. Architecture Overview

CoreState v2.0 is composed of several key components that work together to provide a comprehensive backup solution.

![Architecture Diagram](docs/architecture/overview.md)

### Core Components:

*   **Web Dashboard:** A React-based web interface for users to manage backups, monitor system status, and configure settings.
*   **Daemon:** A lightweight, high-performance agent written in Rust that runs on client machines to perform backup and restore operations.
*   **Backup Engine:** The core service, written in Kotlin, responsible for orchestrating the backup and restore workflows, including scheduling, data processing, and storage management.
*   **ML Optimizer:** A Python-based service that uses machine learning models to optimize backup schedules, detect anomalies, and predict storage needs.
*   **Sync Coordinator:** Manages data synchronization and consistency across distributed components.
*   **Storage HAL (Hardware Abstraction Layer):** Provides a unified interface for interacting with different storage backends (e.g., S3, Azure Blob, GCP Cloud Storage, local filesystems).

### Supporting Services:

*   **Analytics Engine:** Collects and processes system metrics for monitoring and reporting.
*   **Compression Engine:** Provides data compression services to reduce storage footprint.
*   **Deduplication Service:** Identifies and eliminates redundant data blocks to optimize storage.
*   **Encryption Service:** Manages data encryption and key management to ensure data security.
*   **Index Service:** Maintains an index of backed-up data for fast searching and retrieval.

## 3. Project Structure

The project is organized into the following directories:

```
CoreState-v2/
├── apps/                # Client applications (Web Dashboard, Daemon)
│   ├── android/
│   ├── daemon/
│   └── web-dashboard/
├── docs/                # Project documentation
│   ├── api/
│   └── architecture/
├── infrastructure/      # Infrastructure as Code (Kubernetes, Terraform)
│   ├── docker/
│   ├── kubernetes/
│   └── terraform/
├── ml/                  # Machine Learning models and datasets
│   ├── datasets/
│   └── models/
├── module/              # Kernel module for advanced features
│   ├── kernel_patches/
│   └── native/
├── services/            # Backend microservices
│   ├── analytics-engine/
│   ├── backup-engine/
│   ├── compression-engine/
│   ├── deduplication-service/
│   ├── encryption-service/
│   ├── index-service/
│   ├── ml-optimizer/
│   ├── storage-hal/
│   └── sync-coordinator/
├── shared/              # Shared libraries, contracts, and protobuf definitions
│   ├── contracts/
│   ├── libs/
│   └── proto/
├── tests/               # E2E, integration, performance, and unit tests
│   ├── e2e/
│   ├── integration/
│   ├── performance/
│   └── unit/
└── tools/               # Developer and operational tools
    ├── benchmarking/
    ├── cli/
    └── migration/
```

## 4. Feature Implementations

### 4.1. High-Performance Daemon

The CoreState Daemon is a native application written in Rust for maximum performance and minimal resource footprint on client systems. It is responsible for:

*   File system monitoring for changes.
*   Executing backup and restore tasks as directed by the Backup Engine.
*   Client-side encryption and compression.

### 4.2. ML-Powered Optimization

The ML Optimizer service provides intelligent features:

*   **Predictive Backups:** Analyzes data change patterns to predict optimal backup times.
*   **Anomaly Detection:** Identifies unusual activity that might indicate a ransomware attack or data corruption.
*   **Storage Optimization:** Recommends storage tiering strategies based on data access patterns.

### 4.3. Advanced Kernel-Level Features

For supported platforms, CoreState v2.0 can utilize a kernel module for advanced capabilities:

*   **CoW Snapshots:** Near-instantaneous, low-overhead snapshots using Copy-on-Write.
*   **Block-Level Tracking:** Efficiently tracks changed data blocks for incremental backups.
*   **Hardware Acceleration:** Integrates with hardware security modules (HSMs) for enhanced encryption performance.

### 4.4. Cloud-Native and Distributed

The system is designed for the cloud:

*   **Kubernetes-Native:** All services are containerized and can be deployed and managed with Kubernetes.
*   **Scalable:** Services can be scaled independently to meet demand.
*   **Resilient:** The distributed nature of the system ensures high availability.

## 5. Getting Started

### Prerequisites

*   Docker
*   Kubernetes (e.g., Minikube, Kind, or a cloud provider's EKS/AKS/GKE)
*   `kubectl`
*   `gradle` (for Backup Engine)
*   `rustc` and `cargo` (for Daemon)
*   `python` and `pip` (for ML Optimizer)
*   `npm` (for Web Dashboard)

### Building and Running

1.  **Build Services:** Each service in the `/services` directory contains instructions for building its Docker image. For example, for the Backup Engine:
    ```bash
    cd services/backup-engine
    ./gradlew build
    docker build -t corestate-backup-engine .
    ```

2.  **Deploy to Kubernetes:**
    ```bash
    kubectl apply -f infrastructure/kubernetes/
    ```

3.  **Build and Run Web Dashboard:**
    ```bash
    cd apps/web-dashboard
    npm install
    npm start
    ```

4.  **Build and Run Daemon:**
    ```bash
    cd apps/daemon
    cargo build --release
    ```

## 6. API and Communication

Services communicate via gRPC. Protocol definitions are located in the `shared/proto` directory.

*   [`backup.proto`](shared/proto/backup.proto): Defines messages and services for backup and restore operations.
*   [`sync.proto`](shared/proto/sync.proto): Defines messages and services for data synchronization.
*   [`analytics.proto`](shared/proto/analytics.proto): Defines messages and services for analytics and monitoring.

API documentation can be found in [`docs/api/grpc.md`](docs/api/grpc.md).

## 7. Contributing

Contributions are welcome! Please refer to the project's contribution guidelines and code of conduct.

## 8. License

This project is licensed under the [MIT License](LICENSE).