{"id":19541459,"url":"https://github.com/genesisblock3301/image_processing_pipeline","last_synced_at":"2026-02-04T11:44:23.099Z","repository":{"id":230882899,"uuid":"780362415","full_name":"GenesisBlock3301/image_processing_pipeline","owner":"GenesisBlock3301","description":"Create a serverless image processing pipeline using AWS SQS and Lambda. 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Here's a basic project idea using AWS SQS (Simple Queue Service) and Lambda:\n\n**Project Idea: Image Processing Pipeline**\n\n**Overview:**\nCreate a serverless image processing pipeline using AWS SQS and Lambda. This pipeline will allow users to upload images to an S3 bucket, trigger Lambda functions through SQS messages, process the images, and store the results back in another S3 bucket.\n\n**Components:**\n\n1. **S3 Buckets:**\n   - Input Bucket: Users will upload images to this bucket.\n   - Output Bucket: Processed images will be stored in this bucket.\n\n2. **SQS Queue:**\n   - Processing Queue: Whenever a new image is uploaded to the input bucket, a message will be sent to this queue to trigger the processing Lambda function.\n\n3. **Lambda Functions:**\n   - **Image Processor:** This Lambda function will be triggered by messages in the processing queue. It will retrieve the image from the input bucket, perform the required image processing tasks (e.g., resizing, applying filters), and store the processed image in the output bucket.\n   - **Queue Processor:** This Lambda function will be configured to monitor the input bucket. Whenever a new image is uploaded, it will send a message to the processing queue to trigger the image processing function.\n\n**Workflow:**\n\n1. User uploads an image to the input S3 bucket.\n2. The Queue Processor Lambda function detects the new image and sends a message to the processing queue.\n3. The Image Processor Lambda function is triggered by the message in the processing queue.\n4. The Image Processor Lambda function retrieves the image from the input bucket, processes it, and stores the processed image in the output bucket.\n\n**Additional Features:**\n\n- **Error Handling:** Implement error handling to manage failed processing attempts.\n- **Concurrency Control:** Configure SQS and Lambda to handle multiple concurrent processing requests efficiently.\n- **Monitoring and Logging:** Set up CloudWatch logs and metrics to monitor the performance and health of the pipeline.\n- **Security:** Implement appropriate IAM roles and policies to ensure secure access to S3 buckets and SQS queues.\n- **Notification:** Optionally, configure SNS (Simple Notification Service) to send notifications upon successful or failed image processing tasks.\n\n**Technologies Used:**\n- AWS Lambda\n- AWS SQS\n- AWS S3\n- AWS IAM\n- AWS CloudWatch (for logging and monitoring)\n\nThis project provides a scalable and cost-effective solution for image processing tasks, as it utilizes serverless computing and messaging services provided by AWS. You can extend this project by adding more complex image processing functionalities or integrating it with other AWS services as per your requirements.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenesisblock3301%2Fimage_processing_pipeline","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgenesisblock3301%2Fimage_processing_pipeline","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgenesisblock3301%2Fimage_processing_pipeline/lists"}