GitOps is a software development and deployment methodology that uses Git as the central repository for both code and infrastructure configuration, enabling automated and auditable deployments.

ArgoCD is a Kubernetes-native continuous delivery tool that implements GitOps principles. It uses a declarative approach to deploy applications to Kubernetes, ensuring that the desired state of the application is always maintained.

Kubernetes Operators are software extensions to Kubernetes that enable the automation and management of complex, application-specific, operational tasks with domain-specific knowledge within a Kubernetes cluster.

In this tutorial, we will use the Atlas Operator in tandem with Atlas Cloud and ArgoCD to create a slick, modern GitOps workflow for managing your database migrations natively in Kubernetes.

For the sake of brevity, we are going to split this guide into two parts:

1. In part one, we will show how to initialize an Atlas project, and create a CI/CD pipeline that will automatically plan, verify and store your database migrations in Atlas Cloud using GitHub Actions.
2. In part two, we will show how to deploy these migrations using the Atlas Operator and ArgoCD to demonstrate a complete GitOps workflow for database migrations.

Hi everyone!

It's been a few weeks since our last version announcement and today I'm happy to share with you
v0.15, which includes some very exciting improvements for Atlas:

• Interactive Declarative Migrations - Atlas supports a Terraform-like workflow for managing your database schema using the schema apply command. In this release we have added a new "Lint and Edit" mode to this command, which will analyze your schema changes for issues and will allow you to edit them interactively before applying them to your database.
• Functions and Stored Procedures - Atlas now supports creating and managing functions and stored procedures in your database schema.
• Postgres Domains - In addition, Atlas now supports Postgres Domains . A domain is essentially a data type with optional constraints (restrictions on the allowed set of values).
• TypeORM Integration - TypeORM is a popular ORM for Node.js. In this release, we are happy to announce the TypeORM integration, which allows you to automatically generate your database schema from your TypeORM entities, create visualizations and more.

Let's dive right in!

Introduction​

As your application's data model evolves, you will need to make changes to your database schema. In today's world, where teams are expected to own their infrastructure and ship code faster than ever, it is important to have a reliable and repeatable process for managing database schema changes.

Atlas lets you manage your database schema as code. It is a modern schema management tool that applies concepts from modern DevOps tools to database schema management. Using Atlas, teams can automatically plan, verify, deploy and monitor database schema changes.

Microsoft SQL Server, one of the longest-standing database engines in our business, was first released by Microsoft in 1989. MS-SQL is the go-to database for Windows environments in many industries.

In this guide, we will demonstrate how to use Atlas to automatically generate migrations for your Microsoft SQL Server databases.

Hi everyone!

I'm very happy to share with you some of the recent improvements to Atlas, specifcially around GitHub Actions. In August of last year, we released our first version of the GitHub Actions experience for Atlas. It was a modest start, which included the ability to verify the safety and correctness of schema migrations during the CI process.

Over the past year, we have slowly added more features to the GitHub Actions experience, including the ability to sync migration directories to Atlas Cloud, deploy migrations, and even install Atlas. As often happens with quickly evolving systems, we felt that the API became complex, carrying over use cases and experiences that have become obsolete or superseded by better ones since the initial release.

At Ariga, the team developing Atlas, we have written a document named the "R&D Manifesto", which lists some the principles that we commit to as individuals and as an organization. One of them is "Obsess over APIs and DevEx" - we believe that the key to building a successful product is to provide the best possible experience to our users, and that starts with clear, consistent and composable APIs that empower our users to achieve amazing feats of engineering.

With that in mind, our team has been working hard in the past few weeks to revamp the GitHub Actions experience for Atlas. Here's a quick summary of the changes:

1. We've moved all actions into a single repo - ariga/atlas-action. (With the exception of ariga/setup-atlas.)
2. The API has been reviewed and updated to make sure it is consistent among the different actions and with the rest of the Atlas ecosystem.
3. We've rewritten the code in Go, which is the language we use for all of our internal tools. This allows us to share code between the CLI and the GitHub Actions, and to provide a more consistent experience between the two. In addition, looking forward we have greatly simplified the process of adding new GitHub Actions as needed.

Introduction​

Sequelize is one of the most popular ORMs for Node.js. It supports a variety of databases, including MySQL, PostgreSQL, SQLite, and Microsoft SQL Server.

Atlas is a modern tool for managing your database schema. It allows you to inspect, plan, lint and execute schema changes to your database. It is designed to be used by developers, DBAs and DevOps engineers alike.

Atlas supports many ways to describe database schemas: Using Schema Loaders, plain SQL, a connection to another database or using Atlas HCL.

Today, I'm happy to announce that Atlas supports loading the desired schema from Sequelize projects. This means that Sequelize users can now use Atlas instead of the existing Sequelize CLI to manage their database schema.

By using Atlas, Sequelize users can now enjoy these benefits:

• A declarative migration flow - Atlas can operate like a "Terraform for databases", where by running atlas schema apply the application schema is applied on a target database.
• Automatic schema migration planning - Alternatively, Atlas can operate using a more traditional versioned migration flow. However, contrary to most tools, Atlas will automatically analyze the diff between the migration directory and the current application data model, and will produce correct and safe SQL migration files.
• CI for schema changes - Atlas can be used during CI to make sure you never merge a pull request that will break your database schema.
• Modern CD integrations - Atlas integrates seamlessly with modern deployment tools such as Kubernetes, Terraform, Helm, Flux, and ArgoCD. This allows you to deploy changes to your database schema as part of your existing deployment pipelines.
• Visualization - Atlas users can create beautiful, shareable ERDs of their application data model with a single command.
• .. and much more (read more about Atlas features)

Hi everyone!

It's been a few weeks since our last version announcement and today I'm happy to share with you
v0.14, which includes some very exciting improvements for Atlas:

• Checkpoints - as your migration directory grows, replaying it from scratch can become annoyingly slow. Checkpoints allow you to save the state of your database at a specific point in time and replay migrations from that point forward.
• Push to the Cloud - you can now push your migration directory to Atlas Cloud directly from the CLI. Think of it like docker push for your database migrations.
• JetBrains Editor Support - After launching our VSCode Extension a few months ago, our team has been hard at work to bring the same experience to JetBrains IDEs. Starting today, you can use Atlas directly from your favorite JetBrains IDEs (IntelliJ, PyCharm, GoLand, etc.) using the new Atlas plugin.

Let's dive right in!

TL;DR​

Atlas now supports AWS IAM authentication, which enables you to perform passwordless schema migrations on your RDS databases. To use it with Atlas, add the aws_rds_token data source to your atlas.hcl configuration file:

data "aws_rds_token" "mydb" {
  endpoint = "mydb.123456789012.us-east-1.rds.amazonaws.com:3306"
  username = "atlas"
}

To skip the intro and jump straight to the tutorial, click here.

We recently shipped a new feature in Atlas that enables developers to quickly create ERD (Entity Relationship Diagram) visualizations of their database schemas. Today, I want to show how this feature can be used in tandem with one of Atlas's core capabilities - "Schema Loaders" - to produce visualizations of GORM models.

But first, let's introduce the different characters in this story:

• Atlas - an open-source tool for managing database schemas.
• GORM - one of the most popular ORMs for Go.
• ERD - a diagram that shows the relationships between entities in a database. (we'll see an example in a minute)
• Schema Loaders - a feature in Atlas that allows users to load their database schemas from different sources.

In this blog post, we will create a toy GORM application, and show how you can use Atlas to visualize the database schema that GORM generates for you.

It's been just over two months since our last version announcement and today I'm super excited to share with you our latest release, v0.13, which includes some long-anticipated additions to Atlas:

• Atlas and Atlas Community Editions - we are making a change in the way Atlas is distributed. Starting today, we are making many of the features previously available only in the commercial version of Atlas available to everyone for free. More on this below.

• Support for SQL Views - SQL Views are virtual tables in a database created by a query and stored in the database. Starting today, you can manage views in your database using the same Atlas workflows you use for tables, indexes, foreign keys, etc.

• Microsoft SQL Server Driver Beta - Over the last few months, we have been working on a driver for MS-SQL with some of our enterprise design partners and are happy to make it available to you as a beta.

• Built-in schema visualization - Over the past year we released some tools to help developers visualize their database schemas using Entity Relationship Diagrams (ERDs). Starting today, you can use the atlas schema inspect --visualize command to create database ERDs directly from the command line.

• GitHub Action for Deployments - We recently received a request from the community to add a GitHub Action to streamline applying migrations directly from GitHub workflows. We thought this was a great idea and are happy to introduce ariga/atlas-deploy-action which you can use to deploy your migrations today.

• Type checking for schema files - As part of our continuous effort to make the experience of working with Atlas as smooth as possible, we are excited to ship a new engine for running type checks on your schema files.

This release is extra-packed with new features and improvements, so let's dive in!

Introduction​

When we started building Atlas a couple of years ago, we noticed that there was a substantial gap between what was then considered state-of-the-art in managing database schemas and the recent strides from Infrastructure-as-Code (IaC) to managing cloud infrastructure.

In this post, we review that gap and show how Atlas – along with its Terraform provider – can bridge the two domains.

As an aside, I usually try to keep blog posts practical and to the point, but occasionally think it’s worth it to zoom out and explain the grander ideas behind what we do.

If you’re looking for a quick and practical explanation of working with Atlas and Terraform, I recommend this YouTube video.