12 Proven Strategies to Seamlessly Migrate Your Monolith to Microservices

Your team has decided that the old, bulky monolith, although still functional, has become so large that maintaining it consumes more effort than adding new features. The following twelve tips aim to make the migration to microservices as smooth as possible.

#1 Know What You’re Doing

Rewriting a monolith is never easy; moving to microservices changes not only the code but also the organization’s operating model. You’ll need to learn a new, more complex tech stack and restructure teams into small cross‑functional units. Before starting, study the trade‑offs of microservices versus alternatives (e.g., modular monolith) and review example projects to understand how they work.

#2 Make a Detailed Plan

Breaking down a monolith requires extensive preparation because the legacy system must stay operational during the transition. Track migration tasks in tickets and treat them like any other sprint work. During planning, you must:

Untangle internal dependencies of the monolith.

Identify the required microservices.

Design data models for each microservice.

Develop a method to migrate and sync data between the monolith and microservice databases.

Design APIs and plan for backward compatibility.

Capture baseline performance metrics of the monolith.

Set availability and performance targets for the new system.

#3 Use a Monorepo

When you split the monolith, a large amount of code will move to new services. A monorepo lets you track these changes in one place and recover from failures faster. If the monolith already lives in a repository, simply create new folders for each microservice.

#4 Share CI Pipelines

During development you’ll continuously release new microservices while still deploying the monolith. Faster, lighter pipelines accelerate progress. When using a monorepo, keep pipelines fast by enabling change‑based execution or using repository‑aware build tools such as Bazel or Pants, and configure separate promotion pipelines for each microservice and the monolith.

Enable change‑based execution or use tools like Bazel/Pants to keep builds efficient.

Configure multiple promotion pipelines—one per microservice and one for the monolith—to support continuous deployment.

#5 Ensure Sufficient Testing

Automated testing gives confidence that refactoring does not introduce regressions. Adopt the testing pyramid: many unit tests, some integration tests, and a few acceptance tests. Run these tests locally as often as they run in the CI pipeline.

#6 Install an API Gateway or HTTP Reverse Proxy

When microservices are deployed, you must isolate inbound traffic. New functionality is served by microservices, while unfinished features remain in the monolith. Choose a routing method based on your needs:

API gateway: route calls based on authenticated user, cookies, feature flags, URI patterns, etc.

HTTP reverse proxy: similar routing for plain HTTP requests, typically forwarding UI traffic to the monolith initially.

After migration, the gateway and proxy remain as standard components for request forwarding, load balancing, and circuit breaking.

#7 Consider an All‑in‑One Container Model

If you plan to run microservices on containers or Kubernetes, containerization helps homogenize the infrastructure. Run the monolith in a container first, then develop and run microservices in containers, and finally learn Kubernetes to scale and shift traffic gradually.

Learn Docker and containers.

Run the monolith inside a container.

Develop and run microservices in containers.

After mastering containers, explore Kubernetes.

Gradually expand microservices and shift traffic.

#8 Warm Up to Change

Adopting microservices takes time; start with small, low‑risk services to build the right mindset, skills, and error‑handling practices without deadline pressure. Use this period to learn distributed computing concepts, define SLAs, set up monitoring and alerts, establish cross‑team communication channels, and decide on deployment strategies. A typical starter is an authentication service that routes login requests.

#9 Use Feature Flags

Feature flags let you toggle functionality without redeploying. During migration you can enable/disable parts of the monolith, experiment with alternative configurations, or run A/B tests. Typical workflow:

Identify a monolith feature to migrate.

Wrap the feature with a flag and redeploy the monolith.

Build and deploy the corresponding microservice.

Test the microservice.

When satisfied, turn off the feature in the monolith.

Repeat until migration is complete.

#10 Modularize the Monolith

Before a full rewrite, break the monolith into vertically stacked, interchangeable modules. Unlike classic layered monoliths, a modular monolith enforces communication through public APIs, keeping most code private and reducing inter‑module coupling.

Two patterns help refactor the monolith: the Strangler Fig and the Anticorruption Layer.

Strangler Fig

Gradually replace edge functionality by routing calls through a “strangler” façade that mimics legacy inputs/outputs, creating new modules that replace old code piece by piece.

Anticorruption Layer

When changes in one module could affect others, introduce a translation layer between fast‑changing modules and the monolith to prevent ripple effects.

#11 Decouple Data

Each microservice should own its private database to avoid tight data coupling. This often means denormalizing the shared monolith database into smaller, possibly redundant databases. After decoupling, implement mechanisms (e.g., data mirroring services) to keep old and new data synchronized during migration.

#12 Add Observability

The new system must be faster, more performant, and more scalable than the old one. Establish baseline metrics and logs before migration, then install centralized logging and monitoring services to provide the observability needed for any microservices application.

Conclusion

Migrating to microservices is challenging, but following these tips can reduce time and frustration. Iterate in small increments, rely on CI/CD for regression testing, keep everything in a single repository for easy rollback, and continuously monitor performance and reliability.