Service Code and Database Schema Synchronization in Production Environment

To ensure that your microservices on AWS ECS and your database schema updates are synchronized effectively without causing service disruptions or inconsistencies, you can consider the following approaches:

1. Implement a Blue-Green Deployment Strategy

Useful when the databases and code are not backward/forward compatible.
Prepare a Green environment with the new code and the updated schema while the Blue environment continues to run the old code and schema.
Once the Green environment is fully tested and confirmed to be stable, switch traffic from the Blue to the Green environment.
The Blue environment can then be updated in a similar manner, ensuring that there is always a fallback available in case of issues.

How to Handle Incoming Requests During Transition

Drain Connections Gracefully: Before switching all traffic to the Green environment, start by gracefully draining existing connections from the Blue environment. This involves configuring the load balancer to stop directing new connections to the Blue environment while allowing existing connections to complete their processes.
Synchronize State: If your application involves session data or other stateful information, ensure that such states are either:
- Synchronized between the Blue and Green environments before the switch, or
- Stored in a shared service that is not affected by the switch (e.g., external databases, in-memory data grids).
Session Stickiness: Maintain session stickiness (persistent sessions) on the load balancer during the transition period. This ensures that users who are already connected to the Blue environment can continue their sessions uninterrupted until they naturally complete.

Data Handling and Synchronization

Data Replication: Set up data replication from the Blue environment to the Green environment. This can be done using database replication features, ensuring that any updates made in the Blue environment during the transition are mirrored in the Green environment's database.
Delayed Switch: In scenarios where complete immediate replication isn't feasible, consider delaying the traffic switch until you have a low-traffic window or until you're confident that most critical data has been replicated.
Write-Behind Caching: Implement write-behind caching strategies where writes are queued and synchronized with the database asynchronously. This can help manage data consistency across environments without impacting user experience.
Transactional Integrity: Ensure that transactions are managed properly during the switch. This might mean temporarily halting certain operations during the critical switch phase or using distributed transaction protocols if applicable.

After the Switch

Monitor the Old Environment: Keep the Blue environment running for a short period after the switch. Monitor for any stray requests or data anomalies and redirect these requests to the Green environment if necessary.
Final Data Sync: Perform a final synchronization of any residual data from the Blue to the Green environment after the initial traffic switch but before completely shutting down the Blue environment.
Archiving and Backup: Before fully decommissioning the Blue environment, ensure that all data is backed up and that any useful logs or diagnostic information is archived for future analysis if needed.

Implementation Tips

Automate as Much as Possible: Use scripts or automation tools to handle the steps involved in draining connections, synchronizing data, and switching traffic. Automation reduces the risk of human error and can speed up the process.
Test Thoroughly: Before implementing this approach in a production environment, thoroughly test the process in a staging environment. Simulate various scenarios, including failure modes, to understand how the system behaves.

By taking these steps, you can ensure that the transition from the Blue environment to the Green environment minimizes disruption, maintains data integrity, and provides a seamless experience to end users. This method requires careful planning and testing but is highly effective for zero-downtime deployments.

2. Expand and Contract Method

Phase 1: Expand

Add new schema elements without removing or altering existing structures. This can include adding new tables, columns, or constraints that the new version of the code will use.
Deploy the new version of the application that can operate with both the old and new schema. This version should be capable of determining which schema to interact with based on its availability and compatibility.
This approach ensures that if the new code encounters the old schema, it will still function correctly, albeit without utilizing the new features.

Phase 2: Contract

Once the new application code is live and stable, remove deprecated schema elements that are no longer needed by any version of the application.
The cleanup should be done as a separate deployment to ensure that there is no reliance on the outdated schema elements by the new application.
This phase effectively contracts the schema to its new desired state, removing any temporary or transitional elements.

Service Code and Database Schema Synchronization in Production Environment