Category: Amazon Rekognition

A serverless face blurring service can provide a simpler way to process photos in workloads with large amounts of traffic. This post introduces an example application that blurs faces when images are saved in an S3 bucket. The S3 PutObject event invokes a Lambda function that uses Amazon Rekognition to detect faces and GraphicsMagick to process the images.

This post shows how you can add scaling support for a game via automation. The example uses Amazon Rekognition to check images for unacceptable content and uses asynchronous architecture patterns with Step Functions and HTTP WebPush.

This post shows how to deploy an imagery processing pipeline in the AWS Cloud. It is decoupled to allow both pre and post-processing extensions to be integrated into the pipeline more easily. Visit the code repository for further information.

This post discusses a fully serverless architecture for searching images based on their contents. It shows how this architecture is decoupled and stateless by using S3 events, SQS messages, an EventBridge bus, and Amazon Aurora Serverless.

Previously in this series, you deploy a simple workflow for processing image uploads in the Happy Path web application. In this post, you add progressively more complex functionality by deploying new versions of workflows.

In this blog post, I show how to use a serverless application to build and manage enterprise workflows at scale. This minimal-code solution is highly scalable and flexible, and can be modified easily to meet your needs.

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Enterprise customers frequently have repositories with thousands of documents, images and other media. While these contain valuable information for users, it’s often hard to index and search this content. One challenge is interpreting the data intelligently, and another issue is […]