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 this blog post, we’ll delve into the process of writing data into InfluxDB v3 using Go. Our focus will be on harnessing the capabilities of the influxdb3-go client library, particularly its support for annotated structs. Through a practical example, we’ll demonstrate how to convert a slice into a structured format and efficiently batch write it into InfluxDB.

In this blog post, we’ll delve into the process of creating a Pulumi Resource provider sourced from a Terraform Provider developed with the Terraform Plugin Framework. Our focus will be on leveraging the bridge package to facilitate this transition seamlessly. To illustrate, we’ll demonstrate bridging the InfluxDB Terraform provider to Pulumi.

Terraform is a powerful infrastructure as code tool that automates cloud infrastructure provisioning and management through simple configuration files. If you’re interested in learning more, I’ve written a short blog outlining some key components of Terraform.

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.