Having a visual representation of your data model can be helpful as it allows for easier comprehension of complex data structures, and enables developers to better understand and collaborate on the data model of the application they are building.

Entity relationship diagrams (ERDs) are a common way to visualize data models, by showing how data is stored in the database. ERDs are graphical representations of the entities, their attributes, and the way these entities are related to each other.

Today we are happy to announce the release of DjangoViz, a new tool for automatically creating ERDs from Django data models.

Introduction​

Atlas supports many ways to describe database schemas. Using Schema Loaders, Atlas gives users the flexibility to define schemas using plain SQL, a connection to another database or using Atlas HCL.

What is Atlas HCL?​

Introduction​

Today, we are excited to announce the release of Atlas v0.11.0, which introduces the Atlas Kubernetes Operator. This release is a major milestone in our mission to make Atlas the most robust and modern way to manage your database schemas. With the Atlas Kubernetes Operator, you can now manage your database schemas with Atlas from within your Kubernetes cluster.

In this release, we also introduce a new concept to Atlas - "Diff Policies" - which allow you to customize the way Atlas plans database migrations for you. This concept is directly related to the Kubernetes Operator, and we will explain how below.

What are Kubernetes Operators?​

Kubernetes has taken the cloud infrastructure world by storm mostly thanks to its declarative API. When working with Kubernetes, developers provide their cluster's desired configuration to the Kubernetes API, and Kubernetes is responsible for reconciling the actual state of the cluster with the desired state. This allows developers to focus on the desired state of their cluster, and let Kubernetes handle the complexities of how to get there.

Earlier today, we released v0.5.0 of the Atlas Terraform Provider. This release includes two changes that, in my opinion, are a great improvement to the experience of working with the Atlas Provider.

In this post, I will discuss these two changes and how they can help you to manage your database schemas with Terraform:

• Support for the docker:// driver for dev-databases.

• Support for defining the desired state of your database schema in plain SQL (and any other schema loader supported by Atlas).

Database schema migrations are an essential part of software development, allowing teams to evolve and refine their application's data model over time. However, with schema changes, it's not always smooth sailing, and migration failures can be disruptive and challenging to resolve.

As much as we'd like to believe that our schema migrations will be executed flawlessly, the reality is that things can and do go wrong. Whether it's due to human error, unforeseen complications, or technical constraints, migration failures can be a significant source of frustration for development teams. Anticipating and preparing for these issues is essential to minimize their impact on your project.

In this blog post, we'll explore the common causes of migration failures and demonstrate how Atlas can help you quickly recover from such failures and easily get back on track.

It's been only two weeks since the release of v0.10.0, but we are already back with more exciting features we want to share with you. Besides some more improvements and bug fixes, we added two new SQL analyzers to Atlas and the capability to have Atlas Cloud pick up a linting configuration file from your repository.

What is Platform Engineering​

A few months ago, an article on The New Stack made a lot of waves in our industry, claiming that "DevOps Is Dead" and that it will be superseded by Platform Engineering. I had the pleasure of discussing this topic with Armon Dadgar, who serves on Ariga's advisory board (but more famously is the co-founder and CTO of HashiCorp).

The DevOps movement challenged the software industry with a bold vision, Armon recalled: "If only we could meld the functions of Dev and Ops into the same human, a super-engineer that writes backend applications for breakfast, configures build systems and CI pipelines for lunch, and then puts out a database production fire for dinner, we would finally get total ownership and accountability."

However, Armon pointed out, in practice, things were more complex: "Outside of a few select companies that could hire and retain them, these people didn't actually exist." This realization has given rise to Platform Engineering. "We need developers to be able to self-serve and be responsible for their applications, but the complexity of modern cloud-native architectures is too big. To be efficient, organizations need to abstract these things away."

We are seeing platform teams being created everywhere as a response to this complexity. These teams are commissioned with the charter to maintain an Internal Developer Platform, which acts as a flexible abstraction to the complexity of managing applications in cloud-native architectures.

As applications evolve, database schema changes become inevitable. However, some types of changes can break the contract between the backend server and the database, leading to errors during deployment and application downtime. Ensuring that these breaking changes are detected and prevented is crucial for maintaining system stability and delivering a seamless user experience. In this post, we will explore how Atlas can help you prevent breaking schema changes from impacting your application.

It's been two months since the release of v0.9.0, so we figured it's about time to release a new version and share with you what we've accomplished so far, as well as what's to come in the upcoming weeks. Besides the many improvements and bug fixes in v0.10.0, we added two major features to Atlas that I want to share with you: schema loaders and the Community Preview of Atlas Cloud.

For a long time, one of the most common feature requests we've been getting from our users is the ability to manage their desired "schema state" using SQL. This is understandable, using Atlas DDL (HCL) can feel unfamiliar to some users, especially those who have never worked with Terraform before. For this reason, we're excited to announce the release of Atlas v0.9.0, which now fully supports SQL.