People Matter more than Technology when Building Serverless Applications

I’ve been hitting the gas pretty hard on Rust lately and doubling down on my desire to see more Rust in Serverless. I feel strongly though that balance is important in anything in life. For every period of intense push, there needs to be time to pause and reflect. So for this article, I want to take a step back and hit some brake on my Rust content by looking at what’s really important when building Serverless applications.


Cognito Starter Kit with Rust and Lambda

Welcome to the Cognito Starter Kit with a large helping of Rust seasoned with some CDK. I’m a big believer in Cognito and the power it gives builders to customize the various signup and authentication workflows. With Cognito, you get a managed service that has flexible usage-based pricing, numerous hooks and configurations and the ability to use OAuth and OIDC in your workflows. Let’s dig in on the Cognito starter kit.


Leveraging the SDK to Publish an Event to EventBridge with Lambda and Rust

Following up on my popular Rust and Lambda article, I wanted to explore how to put an event on an AWS EventBridge Bus. If you aren’t familiar with AWS’ EventBridge, think of it as a highly scalable Event Router with built-in scheduling and data transformation. Let’s take a deeper look at putting events on EventBridge with Lambda and Rust.


Customize a Cognito Access Token with Rust

Identity and Access Management is a critical part of any application. And having a solution that provides customization can also be super important. Take for instance the ability to customize a Cognito Access token to extend functionality.

So many times developers and architects try and roll their own solution and while they do their best to meet OAuth and OIDC specifications, they just tend to fall short. Not to mention they end up with more maintenance and scaling issues than they planned. By leveraging a Serverless Identity Platform like Cognito, developers and architects gain a piece that takes care of the heavy lifting of identity and access for a user base of 1 to essentially as many as needed.

However, until very recently a gap in functionality that honestly allowed some insecure usage existed. Developers were using ID tokens as Access tokens because only those tokens could be customized within a Cognito sign-in workflow. That is no longer the case, as Access tokens can now be customized. I want to take a look at how to customize a Cognito Access Token with Rust.

AWS’ Cognito allows you to implement frictionless customer identity and access management that scales


API Gateway, Lambda, DynamoDB and Rust

It’s been a few weeks since I last wrote an article on using Rust with AWS. In the span of then and now, AWS officially released their Rust SDK for interacting with many of their services. If there was a barrier before this in my mind about using something in production that wasn’t generally available, that barrier is now gone. I also made a public commitment to building more examples in Rust in 2024 and while I’m a few weeks early, I just can’t contain my enthusiasm for learning this language that feels nothing like anything I’ve worked with before. Let’s take a look at building an API with API Gateway, Lambda, DynamoDB and Rust.


Partitioned S3 Bucket from DynamoDB

I’ve been working recently with some data that doesn’t naturally fit into my AWS HealthLake datastore. I have some additional information captured in a DynamoDB table that would be useful to blend with HealthLake but on its own is not an FHIR resource. I pondered on this for a while and came up with the idea of piping DynamoDB stream changes to S3 so that I could then pick up with AWS Glue. In this article, I want to show you an approach to building a partitioned S3 bucket from DynamoDB. Refining that further with Glue jobs, tables and crawlers will come later.


Consuming an SQS Event with Lambda and Rust

I’ve been trying to learn Rust for the better part of this year. My curiosity peaked a few years back when I learned the AWS-led Firecracker was developed with the language. And I’ve continued to want to learn it ever since. Fast-forward and I’m jumping both feet in. That’s usually how I work. I must admit that right now, I’m the most noob of noobs, but that’s not going to keep me from sharing what I’m up to and what I’m learning. For me, this blog is as much about sharing as it is about learning and communicating to those reading that it’s OK to be where you are in your journey. There are no straight lines. Only periods of growth and plateaus. In this article, I’ll walk you through consuming an SQS Event with Lambda and Rust.


WebSocket with AWS API Gateway

I was working recently with some backend code and I needed to communicate the success or failure of the result back to my UI. I instantly knew that I needed to put together a WebSocket to handle this interaction between the backend and the front end. With all the Serverless and non-Serverless options out there though, which way do I go? How about plain old WebSockets with AWS API Gateway and Serverless?


Analyzing and Correcting Errors with Advanced SQS Redrive

A good friend of mine is working on a really neat redrive tool with SQS and wanted to write an article to describe its purpose and use. I’m super honored that he asked me to share his writing on my blog. Please find below Adam Tran’s “Analyzing and Correcting Errors with Advanced SQS Redrive”

Analyzing and Correcting Errors with Advanced SQS Redrive

Analyzing dead-letter queues (DLQs) within the AWS ecosystem can be tricky. Receiving and analyzing messages via the AWS Console is very limited, and does not allow for the manipulation of messages in any sensible manner. Sure, you can redrive an entire DLQ, but what if you need to analyze thousands of messages or make changes?

There are many potential solutions to this problem, but a simple solution that I’ve developed is to download your queues’ messages locally where they can be analyzed with any tool of your choosing. I’ve defined a stateful directory structure to reflect where a message is in its journey of analysis so that you can make changes in whatever manner you deem appropriate.


DynamoDB Streams EventBridge Pipes Multiple Items

I’ve written a few articles lately on EventBridge Pipes and specifically around using them with DynamoDB Streams. I’ve written about Enrichment. And I’ve written about just straight Streaming. I believe that using EventBridge Pipes plays a nice part in a Serverless, Event-Driven approach. So in this article, I want to explore Streaming DynamoDB to EventBridge Pipes with multiple items in one table.

Several of the comments I received about Streaming DynamoDB to EventBridge Pipes were around, “What if I have multiple item collections in the same table?”. I intend to show a pattern for handling that exact problem in this article. At the bottom, you’ll find a working code sample that you can deploy and build on top of. I’ve used this exact setup in production, so rest assured that this is a great base to start from.