From Monolith to Microservices in AWS: Patterns for Seamless Migration

From Monolith to Microservices in AWS: Patterns for Seamless Migration

Takahiro Iwasa
Takahiro Iwasa
2 min read
Microservices

Introduction

Let me introduce Monolith to Microservices patterns described in Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith. This book highlights the pros and cons of monoliths and microservices while describing that microservices are not a silver bullet for all challenges.

In this post, I’ll describe how to implement some of the patterns discussed in the book within AWS for a smoother migration experience.

Strangler Fig Application

The Strangler Fig Application pattern enables you to migrate functionality incrementally to microservices without requiring disruptive changes to your existing application.

Instead of rewriting the entire monolith in one go, you gradually create new microservices around the existing system. Over time, these services take over the monolith’s responsibilities, allowing for its eventual decommission.

Implementing Strangler Fig with AWS ALB

Using an Application Load Balancer (ALB), you can route requests to either the monolith or new microservices. ALB’s path-based routing feature facilitates this routing.

Strangler Fig with ALB

Implementing Strangler Fig with SQS

For message processing applications, AWS Lambda can analyze message contents and then enqueue them for processing by the monolith or microservices via SQS.

Strangler Fig with SQS

Parallel Run

The Parallel Run pattern allows you to call both the monolith and microservices simultaneously and store their results separately.

This approach is especially useful for high-risk migrations or major system changes, as it provides a safety net to compare outputs before making the final transition.

Parallel Run Pattern

Change Data Capture (CDC)

The Change Data Capture (CDC) pattern is another migration strategy, though it comes with significant challenges. As noted by the book’s author:

In general, I try to keep the use of this pattern to a minimum because of the challenges around some of the implementations of this pattern.

AWS supports the CDC pattern via Database Migration Service (DMS) and DynamoDB Streams.

This pattern enables you to reactively handle data changes in source databases, making it ideal for synchronizing data during migration.

Change Data Capture Pattern

Conclusion

Migrating from a monolithic architecture to microservices in AWS requires careful planning and the right strategies. Patterns like Strangler Fig Application, Parallel Run, and Change Data Capture provide a roadmap to transition effectively while mitigating risks.

Understanding the strengths and limitations of each pattern empowers you to make better architectural decisions for your application’s needs.

Happy Coding! 🚀

Takahiro Iwasa

Takahiro Iwasa

Software Developer at KAKEHASHI Inc.
Involved in the requirements definition, design, and development of cloud-native applications using AWS. Now, building a new prescription data collection platform at KAKEHASHI Inc. Japan AWS Top Engineers 2020-2023.