https://github.com/thetoriqul/docker-in-memory-storage
The project implements a microservice-based approach using Docker containers with tmpfs mounts for secure in-memory storage.
https://github.com/thetoriqul/docker-in-memory-storage
docker docker-microservice
Last synced: 26 days ago
JSON representation
The project implements a microservice-based approach using Docker containers with tmpfs mounts for secure in-memory storage.
- Host: GitHub
- URL: https://github.com/thetoriqul/docker-in-memory-storage
- Owner: TheToriqul
- Created: 2024-11-20T15:20:04.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-24T14:45:57.000Z (over 1 year ago)
- Last Synced: 2025-05-15T00:21:20.306Z (about 1 year ago)
- Topics: docker, docker-microservice
- Language: Python
- Homepage: https://thetoriqul.com
- Size: 390 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 🚀 Docker In-Memory Storage Implementation
[](https://github.com/TheToriqul/docker-in-memory-storage)
[](https://github.com/TheToriqul/docker-in-memory-storage/stargazers)
## 📋 Overview
This project demonstrates my implementation of secure in-memory storage using Docker containers with tmpfs mounts. Through this journey, I've explored handling sensitive configuration files, such as private keys and API credentials, ensuring they never touch the disk. The project showcases my understanding of container security best practices and memory-based filesystem management.
## 🏗 Technical Architecture
The project implements a microservice-based approach using Docker containers with tmpfs mounts for secure in-memory storage. Here's the high-level architecture:
```mermaid
flowchart TD
subgraph External
Client([Client Request])
Auth[Authentication]
CDN[Content Delivery]
end
subgraph LoadBalancer
LB{Load Balancer}
SSL[SSL Termination]
end
subgraph Security Zone
subgraph Container
Docker[Docker Container]
Python[Python Service]
Storage[(tmpfs Storage)]
Process[Data Processing]
Cache[[Redis Cache]]
Queue[[Message Queue]]
end
subgraph Database
Primary[(Primary DB)]
Replica[(Replica DB)]
end
subgraph Monitoring
Log[/Logging Service/]
Metrics[/Metrics Collection/]
Alert{Alert Manager}
end
end
Client -->|HTTPS Request| CDN
CDN -->|Forward| LB
LB -->|Route| SSL
SSL -->|Decrypt| Auth
Auth -->|Verify| Docker
Docker -->|Route| Python
Python -->|Temporary| Storage
Storage -->|Process| Process
Process -->|Response| Client
Python <-->|Cache Data| Cache
Python -->|Queue Job| Queue
Queue -->|Background| Process
Python -->|Write| Primary
Primary -->|Replicate| Replica
Docker -->|Container Logs| Log
Python -->|App Logs| Log
Process -->|Job Logs| Log
Log -->|Alert Rules| Alert
Docker -->|Health Data| Metrics
Python -->|Performance| Metrics
Metrics -->|Threshold| Alert
Alert -->|Notify| LB
```
## 💻 Technical Stack
- **Container Platform**: Docker
- **Programming Language**: Python 3.9
- **Base Image**: python:3.9-slim
- **Storage**: tmpfs (memory-based filesystem)
- **File System**: Alpine Linux
## ⭐ Key Features
1. Secure In-Memory Storage
- tmpfs mount implementation
- Memory-based file system configuration
- Secure data handling
2. Docker Configuration
- Custom Dockerfile setup
- Container security measures
- Resource limitation controls
3. Python Microservice
- Secure file operations
- Error handling
- Memory management
4. Security Features
- No disk persistence
- Isolated storage space
- Access control implementation
5. Performance Optimization
- Memory-only operations
- Efficient resource usage
- Quick data access
## 📚 Learning Journey
### Technical Mastery:
1. Docker container configuration and security
2. Memory-based filesystem implementation
3. Microservice architecture design
4. Secure data handling practices
5. Resource management and optimization
### Professional Development:
1. Security-first thinking
2. Documentation best practices
3. Problem-solving with containerization
4. System architecture design
5. Performance optimization techniques
## 🔄 Future Enhancements
View Planned Improvements
1. Implement multiple tmpfs mounts for different security levels
2. Add monitoring and logging capabilities
3. Develop automated testing suite
4. Implement data encryption at rest
5. Add horizontal scaling capabilities
6. Enhance error handling and recovery
## ⚙️ Installation
View Installation Details
### Prerequisites
- Docker installed on your system
- Python 3.9 or higher
- Basic understanding of containerization
### Setup Steps
1. Clone the repository:
```bash
git clone https://github.com/TheToriqul/docker-in-memory-storage.git
cd docker-in-memory-storage
```
2. Build the Docker image:
```bash
docker build -t my_microservice .
```
3. Run the container:
```bash
docker run --rm -d \
--mount type=tmpfs,dst=/app/tmp,tmpfs-size=16k,tmpfs-mode=1770 \
my_microservice
```
## 📖 Usage Guide
View Usage Details
### Basic Usage
The microservice automatically handles sensitive data in memory. To verify the setup:
1. Check container status:
```bash
docker ps
```
2. Inspect tmpfs mount:
```bash
docker inspect
```
### Troubleshooting
- Ensure tmpfs mount is properly configured
- Verify memory allocation is sufficient
- Check container logs for any errors
## 📫 Contact
- 📧 Email: toriqul.int@gmail.com
- 📱 Phone: +65 8936 7705, +8801765 939006
## 🔗 Project Links
- [GitHub Repository](https://github.com/TheToriqul/docker-in-memory-storage)
- [Documentation](https://github.com/TheToriqul/docker-in-memory-storage/blob/main/README.md)
## 👏 Acknowledgments
- [Poridhi for excellent labs](https://poridhi.io/)
- Docker documentation for tmpfs mount guidance
- Python community for microservice best practices
---
Feel free to explore, modify, and build upon this configuration as part of my learning journey. You're also welcome to learn from it, and I wish you the best of luck!