169 lines
7.1 KiB
Markdown
169 lines
7.1 KiB
Markdown
# CoreState v2.0 - Next-Generation Advanced Backup System
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## 1. Executive Summary
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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.
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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.
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## 2. Architecture Overview
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CoreState v2.0 is composed of several key components that work together to provide a comprehensive backup solution.
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### Core Components:
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* **Web Dashboard:** A React-based web interface for users to manage backups, monitor system status, and configure settings.
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* **Daemon:** A lightweight, high-performance agent written in Rust that runs on client machines to perform backup and restore operations.
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* **Backup Engine:** The core service, written in Kotlin, responsible for orchestrating the backup and restore workflows, including scheduling, data processing, and storage management.
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* **ML Optimizer:** A Python-based service that uses machine learning models to optimize backup schedules, detect anomalies, and predict storage needs.
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* **Sync Coordinator:** Manages data synchronization and consistency across distributed components.
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* **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).
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### Supporting Services:
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* **Analytics Engine:** Collects and processes system metrics for monitoring and reporting.
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* **Compression Engine:** Provides data compression services to reduce storage footprint.
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* **Deduplication Service:** Identifies and eliminates redundant data blocks to optimize storage.
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* **Encryption Service:** Manages data encryption and key management to ensure data security.
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* **Index Service:** Maintains an index of backed-up data for fast searching and retrieval.
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## 3. Project Structure
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The project is organized into the following directories:
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```
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CoreState-v2/
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├── apps/ # Client applications (Web Dashboard, Daemon)
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│ ├── android/
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│ ├── daemon/
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│ └── web-dashboard/
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├── docs/ # Project documentation
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│ ├── api/
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│ └── architecture/
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├── infrastructure/ # Infrastructure as Code (Kubernetes, Terraform)
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│ ├── docker/
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│ ├── kubernetes/
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│ └── terraform/
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├── ml/ # Machine Learning models and datasets
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│ ├── datasets/
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│ └── models/
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├── module/ # Kernel module for advanced features
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│ ├── kernel_patches/
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│ └── native/
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├── services/ # Backend microservices
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│ ├── analytics-engine/
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│ ├── backup-engine/
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│ ├── compression-engine/
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│ ├── deduplication-service/
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│ ├── encryption-service/
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│ ├── index-service/
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│ ├── ml-optimizer/
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│ ├── storage-hal/
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│ └── sync-coordinator/
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├── shared/ # Shared libraries, contracts, and protobuf definitions
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│ ├── contracts/
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│ ├── libs/
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│ └── proto/
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├── tests/ # E2E, integration, performance, and unit tests
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│ ├── e2e/
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│ ├── integration/
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│ ├── performance/
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│ └── unit/
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└── tools/ # Developer and operational tools
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├── benchmarking/
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├── cli/
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└── migration/
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```
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## 4. Feature Implementations
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### 4.1. High-Performance Daemon
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The CoreState Daemon is a native application written in Rust for maximum performance and minimal resource footprint on client systems. It is responsible for:
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* File system monitoring for changes.
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* Executing backup and restore tasks as directed by the Backup Engine.
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* Client-side encryption and compression.
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### 4.2. ML-Powered Optimization
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The ML Optimizer service provides intelligent features:
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* **Predictive Backups:** Analyzes data change patterns to predict optimal backup times.
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* **Anomaly Detection:** Identifies unusual activity that might indicate a ransomware attack or data corruption.
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* **Storage Optimization:** Recommends storage tiering strategies based on data access patterns.
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### 4.3. Advanced Kernel-Level Features
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For supported platforms, CoreState v2.0 can utilize a kernel module for advanced capabilities:
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* **CoW Snapshots:** Near-instantaneous, low-overhead snapshots using Copy-on-Write.
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* **Block-Level Tracking:** Efficiently tracks changed data blocks for incremental backups.
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* **Hardware Acceleration:** Integrates with hardware security modules (HSMs) for enhanced encryption performance.
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### 4.4. Cloud-Native and Distributed
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The system is designed for the cloud:
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* **Kubernetes-Native:** All services are containerized and can be deployed and managed with Kubernetes.
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* **Scalable:** Services can be scaled independently to meet demand.
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* **Resilient:** The distributed nature of the system ensures high availability.
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## 5. Getting Started
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### Prerequisites
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* Docker
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* Kubernetes (e.g., Minikube, Kind, or a cloud provider's EKS/AKS/GKE)
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* `kubectl`
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* `gradle` (for Backup Engine)
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* `rustc` and `cargo` (for Daemon)
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* `python` and `pip` (for ML Optimizer)
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* `npm` (for Web Dashboard)
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### Building and Running
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1. **Build Services:** Each service in the `/services` directory contains instructions for building its Docker image. For example, for the Backup Engine:
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```bash
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cd services/backup-engine
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./gradlew build
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docker build -t corestate-backup-engine .
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```
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2. **Deploy to Kubernetes:**
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```bash
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kubectl apply -f infrastructure/kubernetes/
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```
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3. **Build and Run Web Dashboard:**
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```bash
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cd apps/web-dashboard
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npm install
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npm start
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```
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4. **Build and Run Daemon:**
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```bash
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cd apps/daemon
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cargo build --release
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```
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## 6. API and Communication
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Services communicate via gRPC. Protocol definitions are located in the `shared/proto` directory.
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* [`backup.proto`](shared/proto/backup.proto): Defines messages and services for backup and restore operations.
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* [`sync.proto`](shared/proto/sync.proto): Defines messages and services for data synchronization.
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* [`analytics.proto`](shared/proto/analytics.proto): Defines messages and services for analytics and monitoring.
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API documentation can be found in [`docs/api/grpc.md`](docs/api/grpc.md).
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## 7. Contributing
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Contributions are welcome! Please refer to the project's contribution guidelines and code of conduct.
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## 8. License
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This project is licensed under the [MIT License](LICENSE). |