Zero-Downtime PostgreSQL Migration: My Journey with DevCycle 🚀

Hello everyone! I'm Jackson Kasi, and I want to share how I tackled migrating a high-transaction PostgreSQL database from a self-hosted environment to the cloud without any downtime or data loss. This was crucial for our live production system, where even a few seconds of downtime could have serious consequences.

The Challenge 🎯

Imagine an application processing thousands of transactions every minute. Now, imagine needing to migrate its PostgreSQL database to a new environment—like moving from a self-hosted server to a cloud-based instance—without taking the system offline or risking data integrity. How do you pull off such a seamless transition?

That's the challenge we faced. We needed a strategy that would allow us to:

• Write to both the old and new databases simultaneously during the migration.
• Gradually switch read operations from the old database to the new one for specific user groups (like developers and testers).
• Ensure zero downtime and maintain data consistency throughout the process.

Without a solid plan, we risked data inconsistencies, system outages, and a poor user experience. That's when we turned to DevCycle.

Why DevCycle? 🛠️

Traditional migration methods can involve significant downtime or complex data syncing scripts. To avoid these pitfalls, we chose DevCycle, a feature flag management tool that let us dynamically control which database our application interacted with based on user contexts and feature flags. This made the migration smooth and flexible.

Key Benefits of Using DevCycle:

• Flexibility: Toggle database operations without redeploying the application.
• Control: Direct specific user groups to the new database for testing.
• Safety: Quickly revert to the old database if any issues arise.
• Zero Downtime: Keep the application running seamlessly during migration.

What I Built 🏗️

To meet our migration needs, I created a Proof of Concept (POC) using DevCycle's feature flags and Drizzle ORM for database operations. Here's an overview:

1. Dual Write Operations: During migration, all write operations go to both the old and new databases to keep data consistent.
2. Conditional Read Operations: Based on feature flags, certain user groups (like developers and testers) read from the new database, while others continue with the old one.
3. Zero Downtime: By managing read and write operations dynamically, we eliminate the need for system downtime.

How It Works: Step-by-Step Guide 📝

1. Setting Up Feature Flags in DevCycle

We defined two key feature flags:

• write: Controls write operations to the new database.
• read: Controls read operations from the new database.

ℹ️ Note: The old database always handles reads and writes by default.

2. Defining User Groups and Conditions

We set up conditions to target specific user groups:

• Testing Group:
  • Users with IDs 123 or 456.
  • Served the Testing Groups variant.
• Customer Group:
  • All other users.
  • Served the User Groups variant.

This setup allowed us to control who interacted with the new database.

3. Implementing Dual Write and Conditional Read in Code

In our server code, we evaluated feature flags based on user context:

• Write Operations:
  • If writeToNewDB is true, write to both databases.
  • If false, write only to the old database.
• Read Operations:
  • If readFromNewDB is true, read from the new database.
  • If false, read from the old database.

This logic ensured data consistency and allowed controlled testing.

4. Automating Data Sync with PostgreSQL's Publish-Subscribe 📡

ℹ️ Note: This step is still under development.

We plan to use PostgreSQL's Publish-Subscribe feature to synchronize data:

• The old database will publish changes.
• The new database will subscribe and update accordingly.

This will ensure both databases stay in sync without manual intervention.

5. Building Docker Containers and Scripts 🐳

ℹ️ Note: This step is also still under development.

We're working on creating custom Docker containers and shell scripts to automate:

• Database setup.
• Data synchronization.
• Application deployment.

Automation will make the process repeatable and less prone to errors.

6. Utilizing DevCycle's Management API for Dynamic Control 🔄

With DevCycle's Management API, we could:

• Update feature flags programmatically.
• Control rollout phases.
• Quickly switch read/write operations as needed.

7. Testing with Real Users 👥

We began testing by enabling the new database for specific users:

• Users from countries like India (IN) and United States (US).
• Users with a Pro subscription.

This allowed us to:

• Validate the new database under real-world conditions.
• Gather feedback and address any issues.
• Ensure performance met our standards.

8. Monitoring and Final Rollout 🎉

After successful testing:

• We monitored for errors using tools like Sentry.
• Confirmed data integrity and application performance.
• Gradually enabled the new database for all users.
• Disabled the old database, completing the migration.

[DevCycle]: DevCycle initialized
Listening on http://localhost:8000/
User context: { user_id: "123", country: "US" }
Write to old DB: true
Write to new DB: false
Read from old DB: true
Read from new DB: true
Reading from the new database.
Hurray! Migration completed successfully! 🥳

The Code Repository 📂

You can find the complete code on GitHub:

Geo Feature Flag Database Migration

My DevCycle Experience 🌟

Using DevCycle made the migration smooth and efficient.

Highlights:

• Flexibility: Easily toggle features without redeploying.
• Control: Direct specific users to the new database.
• Reliability: Quickly revert changes if needed.
• Zero Downtime: Users experienced no interruptions.

Community Support ❤️

The DevCycle Discord Community was fantastic! Their support helped us navigate challenges and optimize our implementation.

Feedback:

• Documentation: Clear and helpful.
• Integration: Simple with DevCycle SDK and OpenFeature Provider.

Conclusion 🏁

Migrating a high-transaction database without downtime is challenging but achievable with the right approach.

Key Takeaways:

• Feature Flags: Use them to control migrations dynamically.
• Dual Writes: Ensure data consistency across databases.
• Selective Testing: Roll out changes to specific user groups first.
• Automation: We're working on scripts and containers to streamline processes.
• Monitoring: Keep an eye on performance and errors throughout.

Thanks for reading! Feel free to check out the GitHub repository for more details and the full code. ⭐😊