In a recent training I learned something about DynamoDB streams that surprised me. I had expected that any PutItem, UpdateItem or DeleteItem API call would cause a record to appear in the stream of my table, but that’s not the case. The stream works a little different from what I expected and in this short article I’m going to explain to you how.
DynamoDB streams help you respond to changes in your tables, which is commonly used to create aggregations or trigger other workflows once data is updated. Getting a near-real-time view into these Streams can also be helpful during developing or debugging
You have probably seen architectures that use DynamoDB streams to perform change data capture on tables and Lambda functions to process those changes before. Today, we’ll do a deep dive into the underlying technology and explore how we can configure
Testing is one of the most critical activities in software development and using third-party APIs like DynamoDB in your code comes with challenges when writing tests. Today, I’ll show you how you can start writing tests for code that accesses Dynamo
I will show you how to implement pessimistic locking using Python with DynamoDB as our backend. Before we start, we’ll review the basics and discuss some of the design criteria we’re looking for. In an earlier post, I outlined to you how to im
Concurrent access to the same items in DynamoDB can lead to consistency problems. In this post I explain why that is and introduce optimistic locking as a technique to combat this issue.