3 posts tagged with "versioned-migrations"

Python has been a top programming language for the past decade, known for its simplicity and rich ecosystem. Many companies use it to build web apps and server software, thanks to frameworks like Django and SQLAlchemy.

One of the most common (and often loathed) tasks when building backend applications is managing the database schema. As the app's data model evolves, developers need to modify the database schema to reflect those changes. This is where database schema migration tools come into play.

Introduction​

The Atlas Kubernetes Operator is a Kubernetes operator that enables you to manage your database schemas natively from your Kubernetes cluster. By exposing custom resource definitions (CRD) the operator extends the Kubernetes API to support database schema management.

In a previous blog post we demonstrated how to use the Atlas Operator for the declarative (state-based) workflow in which you define the desired state of your database schema in a Kubernetes manifest and the operator takes care of the rest.

State vs. versioned based migrations is a common and unresolved debate in the database schema management world, and we built Atlas to support both from the get-go.

Today, we are happy to announce v0.2.0 of the Atlas Kubernetes Operator which adds support support for the versioned migration workflow.

In this blog post we will demonstrate how to use the Atlas Operator this new workflow.

Introduction​

Today we are very excited to announce the release of Atlas Terraform Provider v0.4.0. This release brings some exciting new features and improvements to the provider which we will describe in this post.

In addition, this release is the first to be published under our new partnership with HashiCorp as a Technology Partner. Atlas is sometimes described as a "Terraform for Databases", so we have high hopes that this partnership will help us to bring many opportunities to create better ways for integrating database schema management into IaC workflows.