7 posts tagged with "postgres"

Testing your database schema shouldn't be an afterthought. Automating checks on your objects, constraints, and functions is critical to catching breaking changes before they hit production.

Enter pgTAP—which relies on traditional runtime assertions in an ephemeral database—and Atlas—which leverages a modern, declarative approach. This post breaks down how both tools handle schema testing and explains when you should swap out heavy runtime assertions for Atlas's lightweight lint rules.

Hey everyone!

We're excited to announce Atlas v1.2. This release brings column-level data lineage to Atlas Cloud, registry backups to your own cloud storage, a schema ownership policy for CI, and expanded database coverage.

Here is what you can find in this release:

• Column-Level Data Lineage - Trace how columns are derived from upstream sources across tables, views, and datasets in Atlas Cloud.
• Offline Access & Registry Backups - Back up Atlas Registry repositories to S3, GCS, or Azure Blob Storage. Atlas Pro license grants are cached in CI/CD environments, so your pipeline never has a single point of failure.
• Schema Ownership Policy - Enforce which GitHub users and teams can modify specific schema objects, closing the gap between CODEOWNERS and DDL access control.
• Database Driver Improvements - PostgreSQL routine permissions, user-mapping, and default ACLs; Snowflake tasks and pipes; Oracle UDTs; Expanded permissions for MSSQL, MySQL, and ClickHouse.

As applications grow, their underlying database schemas inevitably grow more complex. What often starts as an afterthought handled by a single developer quickly turns into a critical, high-risk responsibility that demands precision and discipline.

Tools like Flyway and Liquibase automate the application of schema changes, but they stop short of addressing the real pain points: planning and validating those changes before they hit production. These steps remain largely manual, error-prone, and disliked by most developers.

Atlas is designed to fill this gap by automating the entire lifecycle of schema changes. Inspired by Terraform, Atlas provides a declarative approach to database schema management, enabling teams to define their schemas as code and automate the planning, validation, and application of changes.

Why Terraform for Databases?​

Infrastructure teams have standardized on tools like Terraform to manage cloud resources declaratively. Databases, despite being critical infrastructure, often remain outside this workflow. Schema changes are still handled manually or with ad-hoc migration scripts, leading to drift, unpredictability, and production risks.

Hi everyone,

Thanks for joining us today for our v0.25 release announcement! In this version we are introducing a new feature that has been requested by many of you: support for Row-level Security Policies in PostgreSQL.

Additionally, we have made some minor changes to our pricing plans, more on that below.

Hi everyone,

I hope you are enjoying the holiday season, because we are here today with the first Atlas release of 2024: v0.17. It's been only a bit over a week since our last release, but we have some exciting new features we couldn't wait to share with you:

• Trigger Support - Atlas now supports managing triggers on MySQL, PostgreSQL, MariaDB and SQLite databases.
• Improved ERDs - You can now visualize your schema's SQL views, as well as create filters to select the specific database objects you wish to see.

Without further ado, let's dive in!

In part one, we demonstrated how to initialize an Atlas project, and create a CI/CD pipeline that automatically plans, verifies and stores your database migrations in Atlas Cloud using GitHub Actions.

In this part, we will show how to deploy these migrations using the Atlas Operator and ArgoCD to demonstrate a complete GitOps workflow for database migrations.

How to GitOps your Database Migrations on Kubernetes​

"We can wrap existing schema management solutions into containers, and run them in Kubernetes as Jobs. But that is SILLY. That is not how we work in Kubernetes."

-Viktor Farcic, DevOps ToolKit

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.