Category: Serverless

JSONPath provides the flexibility to work on JSON objects and arrays inside the Step Functions states machine by reducing the amount of utility code. This post uses a sample application to highlight effective use of JSONPath and data filtering strategies that can be used in AWS Step Functions.

This post shows a number of solutions to create and share archetypes or layers across the company. With these archetypes, development teams can quickly bootstrap projects with company standards and best practices.

It’s best practice to store the output of the Lambda function in a different bucket or AWS resource than the source bucket. In cases where you need to store the processed object in the same bucket, I show three different designs to help minimize the risk of recursive invocations.

This blog post shows you how to integrate Amazon MWAA with Okta as your managed AWS SSO implementation. You can use this solution for your own use cases and enable Okta SSO and Amazon MWAA.

Having visibility on your AWS resources is the key to operating and growing successfully. In this first part of this series on serverless governance, I describe how you can get this visibility by using tags to organize and group your resources, and ease the search and management of related resources.

This post shows an architecture to share your business data with your trading partners using API Gateway, AWS Transfer for SFTP, Lambda, and Step Functions. This architecture enables organizations to quickly on-board partners, build event-driven pipelines, and streamline business processes.

Welcome to the 15th edition of the AWS Serverless ICYMI (in case you missed it) quarterly recap. Every quarter, we share all of the most recent product launches, feature enhancements, blog posts, webinars, Twitch live streams, and other interesting things that you might have missed!

This post shows how to use Step Functions, Lambda, EventBridge, S3, API Gateway HTTP APIs, and Amazon SQS to build a serverless API poller. I show how you can deploy a sample solution, process sample payload, and store it to S3.

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.

Schema Management is a non-trivial challenge in federated GQL systems. The highest risk to your system availability comes with the potential of introducing breaking schema change by one of the graphlets. Your system cannot serve any requests after that. There is the problem of the delayed feedback loop for the engineers working on schema changes and the impact of schema composition during runtime on the service latency.