DynamoDB allows us to store complex data structures and deeply nested objects, but this complexity isn’t free. In this post we take a look at how different Lambda configurations impact the read times from boto3. We examine how different resource configurations can improve the read time of the same item by more than a factor of 12.
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
In this post I’ll introduce DynamoDB, a very powerful fully managed NoSQL wide-column data store in AWS. We will talk about data structures, the APIs to read and write data, indexes, as well as performance and cost considerations. In the end you wil
Detect the crack in the window (or the lambda library) before it breaks: As we have seen during the last month, also well known libraries like log4j can have previously unknown vulnerabilities. Therefore scanning your Lambda application before deploying i
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
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.