[INFO] Initializing machine learning training job. Model: Convolutional Neural Network Dataset: MNIST Hyperparameters: ;   - Learning Rate: 0.001;   - Batch Size: 64
[INFO] Loading training data. Training data loaded successfully. Number of training samples: 60,000
[INFO] Loading validation data. Validation data loaded successfully. Number of validation samples: 10,000
[INFO] Training started. Epoch 1/10;   - Loss: 0.532;   - Accuracy: 0.812 Epoch 2/10;   - Loss: 0.398;   - Accuracy: 0.874 Epoch 3/10;   - Loss: 0.325;   - Accuracy: 0.901 ... (training progress) Training completed.
[INFO] Validation started. Validation loss: 0.287 Validation accuracy: 0.915 Model performance meets validation criteria. Saving the model.
[INFO] Testing the trained model. Test loss: 0.298 Test accuracy: 0.910
[INFO] Deploying the trained model to production. Model deployment successful. API endpoint: http://your-api-endpoint/predict
[INFO] Monitoring system initialized. Monitoring metrics:;   - CPU Usage: 25%;   - Memory Usage: 40%;   - GPU Usage: 80%
[ALERT] High GPU Usage Detected! Scaling resources to handle increased load.
[INFO] Machine learning training job completed successfully. Total training time: 3 hours and 45 minutes.
[INFO] Cleaning up resources. Job artifacts removed. Training environment closed.
[INFO] Image processing web server started. Listening on port 8080.
[INFO] Received image processing request from client at IP address 192.168.1.100. Preprocessing image: resizing to 800x600 pixels. Image preprocessing completed successfully.
[INFO] Applying filters to enhance image details. Filters applied: sharpening, contrast adjustment. Image enhancement completed.
[INFO] Generating thumbnail for the processed image. Thumbnail generated successfully.
[INFO] Uploading processed image to the user's gallery. Image successfully added to the gallery. Image ID: 123456.
[INFO] Sending notification to the user: Image processing complete. Notification sent successfully.
[ERROR] Failed to process image due to corrupted file format. Informing the client about the issue. Client notified about the image processing failure.
[INFO] Image processing web server shutting down. Cleaning up resources. Server shutdown complete.