AWS

Attending AWS re:Invent is always a highlight for me, and this year’s session, SVS407-R: Understanding AWS Lambda Event Source Mapping, turned out to be a goldmine of insights. As someone who builds and maintains event-driven architectures, I walked away with a deeper understanding of the complexities and best practices around Event Source Mapping (ESM), particularly in handling event streams from services like Amazon Kinesis, DynamoDB Streams, and Amazon SQS.

In this blog, we will provide a brief introduction to data governance and show how to implement it on AWS using DataZone. We will walk through a practical example involving a multi-account setup to manage and share data stored in S3 and Redshift, highlighting key steps and best practices along the way.

Moving Amazon Redshift to a new account and region might seem difficult, but it doesn’t have to be. You might need to follow regulations or reorganize your teams. In this guide, we will show you step by step how to move your Redshift data to a different account and region. After reading this guide, you will know how to do Redshift migrations easily, with minimal downtime and secure data. Let’s start and make your Redshift move simple!

AWS Redshift Query Editor v2 is a web-based tool that allows analysts to securely explore, share, and collaborate on data using SQL within a common notebook interface. It simplifies querying data with SQL and visualizing results with charts and graphs in just a few clicks.

In my previous blog, we explored enabling cross-account data sharing using AWS Lake Formation with Terraform. In this post, we’ll dive deeper into enhancing that setup with data filters. Lake Formation data filtering allows for column-level, row-level, and cell-level security. This blog will focus specifically on implementing cell-level security to fine-tune data access controls.

In the earlier blog post, I showcased the steps to achieve continuous deployment using GitHub Actions and AWS CodeBuild specifically for code deployment. Expanding on those principles, let’s delve into the next phase of our workflow — incorporating infrastructure deployment through Terraform.

In this blog post, I’ll guide you through setting up a Continuous Deployment pipeline using GitHub Actions and environments, focusing on both development and production stages.

There are two types of cross-account access

1. Storage cross-account access (S3 bucket is in a different account than the Lake Formation account)

2. Consumption cross-account access (Athena, Redshift Spectrum in a different account than the Lake Formation account)

In this guide, we will discuss the consumption cross-account access, enable cross-account Lake Formation access and use a lambda in Account-Target to execute a simple Athena query to access the data from Account-Source.

Redshift federated query lets you query and analyse data across multiple operational databases directly. In this blog I have explained how to setup Redshift to query across multiple Aurora instances cross-account.