I’m excited to announce that I have not one but TWO new Pluralsight courses! Both Collecting Data on AWS and Storing Data on AWS are now available on Pluralsight!

I recently decided to branch out from my typical AWS realm and try out Microsoft Azure’s CosmosDB. Here’s a quick look at how the process went along with my off-the-cuff thoughts about the service.

Serverless development can speed up your development process a lot by moving infrastructure responsibilities over to cloud providers. However, when testing your application, it can be a challenge to mimic all the cloud services you’re relying on.

One useful tool to help do this when you’re writing Python code is moto. In this post, I’ll show you how to use the moto module in combination with pytest to help test your Python code when it interacts with AWS services like DynamoDB, S3 and others.

I recently created a project aimed at collecting the stories of people impacted by the COVID-19 pandemic called Voices of COVID. This project is designed to collect audio stories from people impacted by the pandemic and make them searchable. For more about the motivation behind it you can review this post. But for now, let’s look at how it’s put together!

Imagine you’re writing a serverless API using AWS Lambda and API Gateway. If you want to accept JSON payloads from POST requests that contain data created by your frontend client you may end up needing to validate that data to make sure it conforms to your expectations before you process it. Let’s look at a simple way of doing this with API Gateway’s JSON Schema validation.