Pre-planning Schema Migrations

The atlas schema plan command allows users to pre-plan declarative schema migrations before applying them to the database. Once a migration is planned, reviewed, and approved, it can be applied using the atlas schema apply command to update the database to the desired state.

Note: If you are not familiar with the atlas schema apply command, please refer to the Applying Changes guide first.

Atlas Pro Feature

The atlas schema plan command is available exclusively to Pro users. To use this feature, run:

atlas login

Overview

The atlas schema apply command updates the database to the desired state defined by the user. These auto-planned schema changes can be approved in one of the following ways:

1. Reviewed and approved interactively by a human.
2. Auto-approved using the --auto-approve flag, though this may be risky in a production database.
3. Auto-reviewed based on the lint-review policy, which requires human review only if the linter detects issues. or errors.

These options depend on the database state and cannot predict whether the migration will succeed, fail, or abort. This is where atlas schema plan becomes useful.

The atlas schema plan command allows users to pre-plan, review, and approve migrations before executing atlas schema apply on the database. This enables users to preview and modify SQL changes, involve team members in the review process, and ensure that no human intervention is required during the atlas schema apply phase.

How does it work? In short (more details below), atlas schema plan generates a migration plan for the specified Schema Transition (State1 -> State2) and stores it in the Atlas Registry. During atlas schema apply, Atlas checks if there is an approved migration plan for the specific schema transition and applies it without recalculating SQL changes at runtime or requiring user-approval.

If users wish to modify the auto-generated migration plan, they can edit it locally and then push it to the Atlas Registry.

Local Example

Let's consider a simple example. We have a table users with two columns id and name, and we want to add a new column email to the table.

Example Setup

Before running atlas schema plan, let's ensure that a schema repository named app exists in Atlas Registry and there is a database containing the previous schema state (before our changes):

Schema Definition

schema.sql

CREATE TABLE users (
  id INTEGER PRIMARY KEY AUTOINCREMENT,
  name TEXT
);

Config File

atlas.hcl

env "local" {
  # URL to the target database.
  url = "sqlite://main.db"
  # URL to the dev-database.
  dev = "sqlite://dev?mode=memory"
  schema {
    # Desired schema state.
    src = "file://schema.sql"
    # Atlas Registry config.
    repo {
      name = "app"
    }
  }
}

We run atlas schema push to create the schema in Atlas Registry:

atlas schema push --env local

Schema: app
  -- Atlas URL: atlas://app
  -- Cloud URL: https://a8m.atlasgo.cloud/schemas/141733920781

Then, we run atlas schema apply to align the database with the schema state:

atlas schema apply --env local --auto-approve

Changing the Schema

At this stage, we want to add a non-nullable email column to the users table. Let's update the schema.sql file and then run atlas schema plan to generate a migration plan.

schema.sql

CREATE TABLE users (
  id INTEGER PRIMARY KEY AUTOINCREMENT,
  name TEXT,
  email TEXT NOT NULL
);

We run atlas schema plan to generate a migration plan for adding the email column to the users table:

atlas schema plan --env local

The output looks like this:

Planning migration from local database to file://schema.sql (1 statement in total):

  -- add column "email" to table: "users":
    -> ALTER TABLE `users` ADD COLUMN `email` text NOT NULL;

-------------------------------------------

Analyzing planned statements (1 in total):

  -- data dependent changes detected:
    -- L2: Adding a non-nullable "text" column "email" will fail in case table "users"
       is not empty https://atlasgo.io/lint/analyzers#MF103
  -- ok (346.192µs)

  -------------------------
  -- 5.038728ms
  -- 1 schema change
  -- 1 diagnostic
? Approve or abort the plan:
  ▸ Approve and push
    Abort

Data-Dependent Changes

Atlas detects data-dependent changes in the migration plan and provides a diagnostic message. In this case, it warns that adding the non-nullable email column, will fail if the users table is not empty. The recommended solution is to provide a default value for the new column. Let's fix this by adding a default value to the email column and re-run the atlas schema plan command.

schema.sql

CREATE TABLE users (
  id INTEGER PRIMARY KEY AUTOINCREMENT,
  name TEXT,
  email TEXT NOT NULL DEFAULT 'unknown'
);

Then, we run atlas schema plan again to generate a new migration plan, but this time, we approve it:

atlas schema plan --env local

Planning migration from local database to file://schema.sql (1 statement in total):

  -- add column "email" to table: "users":
    -> ALTER TABLE `users` ADD COLUMN `email` text NOT NULL DEFAULT 'unknown';

-------------------------------------------

Analyzing planned statements (1 in total):

  -- no diagnostics found

  -------------------------
  -- 6.393773ms
  -- 1 schema change
? Approve or abort the plan:
  ▸ Approve and push
    Abort

Once approved, the migration plan will be pushed to the Atlas Registry, and can be applied using atlas schema apply.

Plan Status: APPROVED
  -- Atlas URL: atlas://app/plans/20240923085308
  -- Cloud URL: https://a8m.atlasgo.cloud/schemas/141733920769/plans/210453397504

At this stage, we can run atlas schema apply to apply the changes to the database, on any environment, without re-calculating the SQL changes at runtime or requiring human intervention.

Applying approved migration using pre-planned file 20240923085308 (1 statement in total):

  -- add column "email" to table: "users"
    -> ALTER TABLE `users` ADD COLUMN `email` text NOT NULL DEFAULT 'unknown';
  -- ok (749.815µs)

  -------------------------
  -- 802.902µs
  -- 1 migration
  -- 1 sql statement

Atlas Registry

Atlas Registry allows you to store, version, and maintain a single source of truth for your database schemas and its migration plans. It is similar to Docker Hub, but for your schemas and migrations. In addition to functioning as storage, it is schema-aware and provides extra capabilities such as ER diagrams, SQL diffing, schema docs, and more.

Schema pushed with atlas schema push

Edit a Plan

One of the first questions that come to mind when comparing the declarative approach to the versioned approach is: How can I edit a migration plan? There are three ways to edit a migration plan:

1. Edit in-place:

   • Ensure the EDITOR environment variable is set (e.g., export EDITOR=vim).
   • Run atlas schema plan --edit to open the plan in the default editor. Upon closing, the plan will be pushed after approval.

2. Save, edit, and push:

   • Run atlas schema plan --save to save the plan to a file and edit it manually.
   • Run atlas schema plan push --file file://<path> to push the edited plan to the Atlas Registry.

3. Pull, edit, and push:

   • Pull a remote plan by running atlas schema plan pull --url atlas://<schema>/plans/<plan> > name.plan.hcl.
   • Open name.plan.hcl in the editor, and edit the migration attribute.
   • Push the edited plan to the Atlas Registry by running atlas schema plan push --file file://<path>.

To complete the example, let's edit the migration plan from the example above by changing all email columns with 'unknown' value to a computed email value:

1. We pull the plan first into a file named 20240923085308.plan.hcl:

atlas schema plan pull --url atlas://app/plans/20240923085308 > 20240923085308.plan.hcl

20240923085308.plan.hcl

plan "20240923085308" {
  from      = "vJYpErjN4kWJpw4nRaJcEX3xx/jExj4a05Ll3Y7gXr4="
  to        = "B5OVckDEeHcaSdYCUMEfYe8CZN85ahLkef44hfwCe2g="
  migration = <<-SQL
  -- Add column "email" to table: "users"
  ALTER TABLE `users` ADD COLUMN `email` text NOT NULL DEFAULT 'unknown';
  SQL
}

Note that the from and to are fingerprints of the schema states. They are used to identify the states in the schema transition. We will ignore them for now (without changing them, of course) and focus on the migration attribute.

2. We edit the migration attribute to change all rows with 'unknown' emails to a computed email value:

20240923085308.plan.hcl

plan "20240916133205" {
  from      = "vJYpErjN4kWJpw4nRaJcEX3xx/jExj4a05Ll3Y7gXr4="
  to        = "B5OVckDEeHcaSdYCUMEfYe8CZN85ahLkef44hfwCe2g="
  migration = <<-SQL
  -- Add column "email" to table: "users"
  ALTER TABLE `users` ADD COLUMN `email` text NOT NULL DEFAULT 'unknown';
  -- Change all unknown "email" columns with a new computed email
  UPDATE `users` SET `email` = PRINTF('%s+a8m@atlasgo.cloud', `name`) WHERE `email` = 'unknown';
  SQL
}

3. Then, we push the edited plan to the Atlas Registry:

atlas schema plan push --file file://20240923085308.plan.hcl

Planning migration statements (2 in total):

  -- add column "email" to table: "users":
    -> ALTER TABLE `users` ADD COLUMN `email` text NOT NULL DEFAULT 'unknown';
  -- change all unknown "email" columns with a new computed email
    -> UPDATE `users` SET `email` = PRINTF('%s+a8m@atlasgo.cloud', `name`) WHERE `email` = 'unknown';

-------------------------------------------

Analyzing planned statements (2 in total):

  -- no diagnostics found

  -------------------------
  -- 43.566575ms
  -- 2 schema changes
? Approve or abort the plan:
  ▸ Approve and push
    Abort

Once approved, the migration plan will be pushed to the Atlas Registry.

Schema Drift

Note that if your manual changes are not in sync with the desired state (i.e., do not bring the database to the desired state), Atlas will detect the schema drift and reject this migration plan.

4. Then, running atlas schema apply will apply the changes to the database, including the new UPDATE statement.

   Applying approved migration using pre-planned file 20240923085308 (2 statements in total):
   
     -- add column "email" to table: "users"
       -> ALTER TABLE `users` ADD COLUMN `email` text NOT NULL DEFAULT 'unknown';
     -- ok (826.977µs)
   
     -- change all unknown "email" columns with a new computed email
       -> UPDATE `users` SET `email` = PRINTF('%s+a8m@atlasgo.cloud', `name`) WHERE `email` = 'unknown';
     -- ok (447.152µs)
   
     -------------------------
     -- 1.353026ms
     -- 1 migration
     -- 2 sql statements

Push a Plan

By default, atlas schema plan proposes pushing the plan file to the Atlas registry. However, you can use the --save flag to dump the plan to a file, edit it, and then push it manually to the Atlas Registry using the atlas schema plan push command:

atlas schema plan push \
  --file file://<path-plan-file> \
  --env <config-env>

Approve a Plan

By default, atlas schema plan pushes plans in an APPROVED state to the registry. However, in some cases, we may prefer to create the plan in pending state, and later approve it manually or automatically after it passes the team's review.

There are two ways to create a plan in a pending state and approve it after review.

1. Manual workflow:
   1. Run the atlas schema plan command with the --pending flag. This creates the plan in pending state.
   2. Then, in order to approve the plan, either go to the Atlas Registry Web UI and approve the plan, or run the atlas schema plan approve command.
2. Automated (CI) workflow:
   1. When setting the schema/plan GitHub Action for your repository, Atlas automatically creates a plan in a pending state.
   2. Then, after the PR is merged, Atlas auto-approves the created plan in the registry.

Protected Flow

Users can protect their registry schemas by limiting who can push changes, push approved plans, or approve existing plans. To enable this for your schema, go to the schema repository settings in the registry and enable the Protected Flows option.

Pull a Plan

To pull a plan from the Atlas Registry, use the atlas schema plan pull command:

atlas schema plan pull \
  --url atlas://app/plans/add_email > add_email.plan.hcl

List Plans

To list all plans in the Atlas Registry for the given schema transition, use the atlas schema plan list command:

atlas schema plan list \
  --env local

Plan Status: APPROVED
  -- Atlas URL: atlas://app/plans/add_email
  -- Cloud URL: https://<tenant>.atlasgo.cloud/schemas/<schema-id>/plans/<plan-id>

Lint a Plan

To lint a plan (remote or local) before pushing it to the Atlas Registry, use the atlas schema plan lint command:

atlas schema plan lint \
  --file file://add_email.plan.hcl \
  --env local

Apply a Plan

Running atlas schema apply searches for a migration plan in the Atlas Registry and applies it to the database, if exists. However, in unusual cases, you might have multiple (approved) migration plans for the same schema transition store in the registry (e.g., one per environment). In that case, running atlas schema apply will abort with the following error:

Error: multiple pre-planned migrations were found in the registry for this schema transition.

  Current hash: vJYpErjN4kWJpw4nRaJcEX3xx/jExj4a05Ll3Y7gXr4=
  Desired hash: hna312Vk535aibL1hTRcBlxeyUvIwV6Mov7kfaZ2+3s=

Plans found:

  atlas://app/plans/<plan-one>
  atlas://app/plans/<plan-two>

To resolve the issue, either delete the conflicting plans or provide the plan URL explicitly using the --plan flag.

In this case, we either delete the conflicting plans from the Atlas Registry or provide the plan URL explicitly using the --plan flag:

Applying approved migration using pre-planned file 20240923085308 (2 statements in total):

  -- add column "email" to table: "users"
    -> ALTER TABLE `users` ADD COLUMN `email` text NOT NULL DEFAULT 'unknown';
  -- ok (789.621µs)

  -- change all unknown "email" columns with a new computed email
    -> UPDATE `users` SET `email` = PRINTF('%s+a8m@atlasgo.cloud', `name`) WHERE `email` = 'unknown';
  -- ok (883.177µs)

  -------------------------
  -- 1.77283ms
  -- 1 migration
  -- 2 sql statements

GitHub Actions

Atlas provides an official GitHub Actions integration to automatically plan, review, and approve declarative schema migrations during PR workflows. The example below demonstrates how to set up this workflow for your repository.

Plan Generated by atlas schema plan

Create a Schema Repository in Atlas Registry

For the purpose of the example, let's create a schema repository named demo in Atlas Registry with the following SQL schema:

Schema Definition

schema.sql

CREATE TABLE users (
  id BIGSERIAL PRIMARY KEY
);

Config File

atlas.hcl

env "dev" {
  # The URL to the dev-database.
  dev = "docker://postgres/15/dev?search_path=public"
  schema {
    # Desired schema state.
    src = "file://schema.sql"
    # Atlas Registry config.
    repo {
      name = "demo"
    }
  }
}

To create the schema repository in the Atlas Registry, run the following command:

atlas schema push --env dev

https://<your-tenant>.atlasgo.cloud/schemas/141733920769

Set Up the schema/push and schema/plan GitHub Actions

In order to keep our schema repository up-to-date with the latest changes, we can set up the schema/push GitHub Action. This action automatically pushes the schema to the Atlas Registry whenever changes are made to the SQL schema file:

.github/workflows/atlas-plan-push.yaml

name: Plan Declarative Migrations
on:
  push:
    branches:
      - master
    paths:
      - .github/workflows/atlas-plan-push.yaml
      - 'schema.sql' # Can be a path to HCL, ORM, other instead.
permissions:
  contents: read
jobs:
  push:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
        with:
          fetch-depth: 0
      - uses: ariga/setup-atlas@v0
        with:
          cloud-token: ${{ secrets.ATLAS_TOKEN }}
      - uses: ariga/atlas-action/schema/push@master
        with:
          env: dev # Use the "dev" environment from the atlas.hcl file.

ATLAS_TOKEN

To push the schema to Atlas Registry from your GitHub Action, set up a GitHub secret named ATLAS_TOKEN using your Atlas Cloud token. To create a token, follow these instructions.

Set Up the schema/plan GitHub Action

The last step is to update our workflow file (atlas-plan-push.yml) with the schema/plan and schema/plan/approve Actions:

• schema/plan - This action automatically plans the schema migration whenever changes are made to the SQL schema file. After a plan is created, it is pushed to the Atlas Registry in PENDING state, and waiting to be approved.
• schema/plan/approve - This action automatically approves the pending plan in the Atlas Registry after the PR is merged to the master branch.

To avoid a race condition between the push and plan workflows, we can merge them into a single workflow.

Plan Inputs

• from - Defines the current state of the schema to calculate the migration from. If not provided, Atlas will use the url in the atlas.hcl file (same as atlas schema apply). If the url attribute is not set, Atlas will use the last known state from the Atlas Registry.
• to - Defines the desired state of the schema to calculate the migration to. If not provided, Atlas will use the schema.src attribute in the atlas.hcl file.

.github/workflows/atlas-plan-push.yml

name: Plan Declarative Migrations
on:
  workflow_dispatch:
  push:
    branches:
      - master
    paths:
      - .github/workflows/atlas-plan-push.yaml
      - 'schema.sql'
  pull_request:
    branches:
      - master
    paths:
      - .github/workflows/atlas-plan-push.yaml
      - 'schema.sql'
permissions:
  contents: read
  pull-requests: write
jobs:
  plan:
    name: plan
    if: ${{ github.event_name == 'pull_request' }}
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Setup Atlas
        uses: ariga/setup-atlas@master
        with:
          cloud-token: ${{ secrets.ATLAS_TOKEN }}
      - name: Run schema plan
        uses: ariga/atlas-action/schema/plan@master
        env:
          GITHUB_TOKEN: ${{ github.token }}
        with:
          env: dev
  approve-push:
    name: approve-push
    if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }}
    runs-on: ubuntu-latest
    env:
      GITHUB_TOKEN: ${{ github.token }}
    steps:
      - uses: actions/checkout@v4
      - name: Setup Atlas
        uses: ariga/setup-atlas@v0
        with:
          cloud-token: ${{ secrets.ATLAS_TOKEN }}
      # Plan against the latest schema state (one before the PR).
      - name: Approve the plan
        id: plan-approve
        uses: ariga/atlas-action/schema/plan/approve@master
        with:
          env: dev
      # Push the schema after the plan is approved.
      - name: Push the schema
        id: schema-push
        uses: ariga/atlas-action/schema/push@master
        with:
          env: dev

Control the Plan using PR Description

Sometimes, there is a need to fine-tune the plan generated by Atlas. For example, you might want to add an UPDATE statement to the plan, preset the plan's transaction mode, or ignore certain linting rules.

One way to achieve this is by following the instructions in the PR description: pull the plan (or use plan --edit), make the required changes, and push it back to the Atlas Registry. Once the plan is pushed, the action can be re-triggered using the gh command:

Plan Generated by atlas schema plan

In addition to the local edit flow, you can add Atlas directives directly to the PR description to control the generated migration. These directives, similar to GitHub Slash Commands, are parsed by the schema/plan action and translated into Atlas migration directives. For example:

1. By default, migration linting flags destructive changes as errors unless configured otherwise. However, you can use the /atlas:nolint destructive directive in the PR description to append this directive to the plan and ignore linting diagnostics for destructive changes.

2. The schema apply command executes migration plans within a transaction unless set to none using the --txmode flag. Some migrations, however, cannot be run in a transaction. In such cases, you can use the /atlas:txmode none directive in the PR description to set the transaction mode to none, and Atlas will respect this during the schema apply stage.

Plan was controlled by the PR description