How does it handle zero-downtime deployments?

It enforces multi-step strategies for breaking changes, such as adding new columns before removing old ones, and utilizes concurrent index creation to prevent table locking.

Does this skill support specific database frameworks?

Yes, it provides standardized patterns and code examples for major frameworks including SQLAlchemy (Alembic), Ruby on Rails (ActiveRecord), and Sequelize (JavaScript).

What is the recommended standard for naming migration files?

The skill recommends using timestamp-based prefixes followed by descriptive actions (e.g., 20241118_add_email_to_users) to ensure execution order and clarity.

Why should I separate schema and data migrations?

Separation ensures that fast structural changes aren't blocked by slow operational data scripts, which makes rollbacks significantly safer and easier to debug.

Does it help with database performance during updates?

Yes, by advocating for concurrent indexing and batch-processing for large data updates to prevent resource exhaustion and long-running locks.

Backend Migration Standards

Name: Backend Migration Standards
Author: Activer007

byActiver007

数据库管理

Establishes best practices for creating reversible, zero-downtime database migrations with consistent naming and structure.

关于

The Backend Migration Standards skill provides Claude Code with a rigorous framework for managing database schema evolution safely and efficiently. It emphasizes mandatory reversibility, the strict separation of schema and data changes, and proven strategies for achieving zero-downtime deployments. By applying this skill, developers ensure that all database modifications—from adding columns and creating indexes to complex data transformations—adhere to industry-standard patterns that minimize production risks and prevent table locking across frameworks like SQLAlchemy, Rails, and Sequelize.

主要功能

0 GitHub stars
Concurrent index creation patterns for high-volume production tables
Zero-downtime deployment strategies for non-blocking database updates
Strict reversibility requirements for every schema change with mandatory rollback methods
Clear separation between structural schema changes and operational data migrations
Standardized naming conventions and idempotency checks for repeatable deployments

使用场景

Safely adding a NOT NULL column to a large production table without causing downtime
Executing batch-processed data transformations to avoid memory exhaustion and long transactions
Implementing multi-step column renames to maintain application uptime during transition

关于

主要功能

0 GitHub stars
Concurrent index creation patterns for high-volume production tables
Zero-downtime deployment strategies for non-blocking database updates
Strict reversibility requirements for every schema change with mandatory rollback methods
Clear separation between structural schema changes and operational data migrations
Standardized naming conventions and idempotency checks for repeatable deployments

使用场景

Safely adding a NOT NULL column to a large production table without causing downtime
Executing batch-processed data transformations to avoid memory exhaustion and long transactions
Implementing multi-step column renames to maintain application uptime during transition