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# Interactive Floor Plan Application with Kubernetes
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## Application Description
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This application is an interactive floor plan visualization tool that displays sensor data on different floors of a building. Users can navigate between floors using the buttons at the bottom of the page and click on sensors to view their current data.
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## Container List
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1. **floorplan-webapp**
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- Web application container based on Python and Flask
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- Serves the frontend HTML, CSS, and JavaScript files
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- Provides an API endpoint for sensor data
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2. **mysql-db**
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- MySQL database container
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- Stores sensor information including position, floor, location, and values
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## Kubernetes Objects
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1. **Namespace**
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- `sensor-app`: Isolated environment for all application resources
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2. **Deployment**
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- `floorplan-webapp`: Manages the web application with 2 replicas for high availability
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3. **StatefulSet**
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- `mysql`: Manages the MySQL database instance with persistent storage
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4. **Services**
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- `floorplan-service`: NodePort service exposing the web application on port 30080
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- `mysql-service`: Headless service for MySQL database access
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5. **PersistentVolume**
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- `mysql-pv`: 1GB volume for MySQL data storage
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6. **PersistentVolumeClaim**
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- `mysql-pvc`: Claims storage from the persistent volume for MySQL
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## Network and Storage Configuration
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### Networks
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- The application uses Kubernetes' built-in networking
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- Web application connects to MySQL using the `mysql-service` DNS name
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- External access is provided through a NodePort service on port 30080
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### Storage
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- The MySQL database uses a persistent volume mounted at `/var/lib/mysql`
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- The persistent volume is backed by a hostPath at `/mnt/data` on the host machine
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## Container Configuration
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### Web Application Container
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- Based on Python 3.9 slim image
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- Installed packages: Flask, mysql-connector-python
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- Configured to connect to MySQL database using environment variables
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- Exposes port 5000
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### MySQL Container
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- Based on MySQL 8.0 image
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- Configured with empty root password for development purposes
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- Initializes with the sensors_db database and sample data
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- Exposes port 3306
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## Application Management
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### Preparation
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1. Make all scripts executable:
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```
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chmod +x prepare-app.sh start-app.sh stop-app.sh
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```
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2. Run the preparation script:
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```
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./prepare-app.sh
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```
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This will:
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- Create the required namespace
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- Prepare the persistent volume directory
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- Build the Docker images
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### Starting the Application
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1. Run the start script:
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```
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./start-app.sh
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```
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This will:
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- Apply all Kubernetes configurations
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- Wait for all components to be ready
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- Display the URL to access the application
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### Stopping the Application
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1. Run the stop script:
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```
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./stop-app.sh
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```
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This will:
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- Remove all Kubernetes objects created for the application
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- The persistent volume data will remain intact
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### Viewing the Application
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1. Open your web browser
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2. Navigate to the URL displayed after running the start script (typically http://[NODE-IP]:30080)
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3. You should see the interactive floor plan with sensors
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4. Use the buttons at the bottom to switch between floors
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# Interactive Floor Plan Application with Kubernetes
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## Application Description
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This application is an interactive floor plan visualization tool that displays sensor data on different floors of a building. Users can navigate between floors using the buttons at the bottom of the page and click on sensors to view their current data.
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## Container List
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1. **floorplan-webapp**
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- Web application container based on Python and Flask
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- Serves the frontend HTML, CSS, and JavaScript files
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- Provides an API endpoint for sensor data
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2. **mysql-db**
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- MySQL database container
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- Stores sensor information including position, floor, location, and values
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## Kubernetes Objects
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1. **Namespace**
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- `sensor-app`: Isolated environment for all application resources
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2. **Deployment**
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- `floorplan-webapp`: Manages the web application with 2 replicas for high availability
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3. **StatefulSet**
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- `mysql`: Manages the MySQL database instance with persistent storage
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4. **Services**
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- `floorplan-service`: NodePort service exposing the web application on port 30080
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- `mysql-service`: Headless service for MySQL database access
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5. **PersistentVolume**
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- `mysql-pv`: 1GB volume for MySQL data storage
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6. **PersistentVolumeClaim**
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- `mysql-pvc`: Claims storage from the persistent volume for MySQL
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## Network and Storage Configuration
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### Networks
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- The application uses Kubernetes' built-in networking
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- Web application connects to MySQL using the `mysql-service` DNS name
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- External access is provided through a NodePort service on port 8080
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### Storage
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- The MySQL database uses a persistent volume mounted at `/var/lib/mysql`
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- The persistent volume is backed by a hostPath at `/mnt/data` on the host machine
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## Container Configuration
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### Web Application Container
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- Based on Python 3.9 slim image
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- Installed packages: Flask, mysql-connector-python
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- Configured to connect to MySQL database using environment variables
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- Exposes port 5000
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### MySQL Container
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- Based on MySQL 8.0 image
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- Configured with empty root password for development purposes
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- Initializes with the sensors_db database and sample data
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- Exposes port 3306
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## Application Management
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### Preparation
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1. Make all scripts executable:
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```
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chmod +x prepare-app.sh start-app.sh stop-app.sh
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```
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2. Run the preparation script:
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```
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./prepare-app.sh
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```
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This will:
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- Create the required namespace
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- Prepare the persistent volume directory
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- Build the Docker images
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### Starting the Application
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1. Run the start script:
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```
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./start-app.sh
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```
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This will:
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- Apply all Kubernetes configurations
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- Wait for all components to be ready
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- Display the URL to access the application
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### Stopping the Application
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1. Run the stop script:
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```
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./stop-app.sh
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```
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This will:
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- Remove all Kubernetes objects created for the application
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- The persistent volume data will remain intact
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### Viewing the Application
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1. Open your web browser
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2. Navigate to the URL displayed after running the start script http://localhost:8080
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3. You should see the interactive floor plan with sensors
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4. Use the buttons at the bottom to switch between floors
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5. Click on sensors to view their data in the right panel
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