Monolith to microservices: step-by-step migration strategies
Senior Technical Content Marketing Manager
Migrating from a monolithic architecture to microservices represents one of the most significant architectural transformations an organization can undertake. While microservices offer compelling benefits in terms of scalability, resilience, and independent deployment, the journey from monolith to microservices is complex and fraught with potential pitfalls.
This article provides a systematic approach to this transformation, outlining practical strategies that minimize risk while incrementally delivering the benefits of microservices. Rather than advocating for a complete rewrite, these techniques focus on gradual migration that maintains business continuity throughout the transition.
Understanding the migration challenge
Breaking apart a monolith requires more than technical know-how—it demands a clear understanding of what makes microservices migration particularly challenging. Unlike greenfield development, you’re working with an existing system that likely serves critical business functions and cannot be disrupted.
The monolith typically contains tightly coupled components with shared data models, making clean separation difficult. Years of development have often created complex dependencies that aren’t fully documented or understood. The application may use older frameworks or libraries that don’t align well with microservices principles.
Beyond the technical challenges, organizational factors come into play. Teams structured around the monolith may need reorganization to align with service boundaries. Existing development, testing, and deployment processes designed for monolithic applications require significant updates to support microservices.
Database transformation presents particular challenges, as the monolith often uses a shared database with complex transaction patterns that are difficult to disentangle. Moving from this shared database to service-specific data stores requires careful planning and execution.
Preparation before migration
Successful migration requires thorough preparation before extracting the first service:
Assess monolith suitability
Not every monolith should be decomposed into microservices. Before committing to migration, evaluate whether your application truly benefits from this architecture. Applications with genuinely independent business domains, varying scaling needs, or requirements for independent deployment are good candidates.
Analyze your existing architecture to identify pain points that microservices would address. Are you struggling with long deployment cycles? Do different components need different scaling characteristics? Is team autonomy limited by the monolithic codebase? Clear answers to these questions help justify the migration effort.
Consider the application’s technology stack and whether it supports gradual migration. Some frameworks make incremental extraction more feasible than others. Applications built on modern web technologies often offer cleaner separation points than legacy systems with deeply embedded dependencies.
Build microservices capabilities
Before beginning migration, establish the infrastructure and practices necessary for microservices success. Implement CI/CD pipelines that support automated testing and deployment of independent services. Without this foundation, you’ll struggle to realize microservices benefits even after extraction.
Containerization technology like Docker provides standardized packaging for microservices, while orchestration platforms like Kubernetes manage deployment and scaling. Investing in this infrastructure early streamlines the migration process.
Service discovery, API gateways, and monitoring solutions address the operational complexity of distributed systems. These components should be in place before you have multiple services to manage. Similarly, implement logging and observability solutions that work across distributed environments.
Define service boundaries
Perhaps the most critical preparation step is defining appropriate service boundaries. Using domain-driven design principles, identify bounded contexts within your monolith—areas of functionality with minimal overlap that can operate independently.
Analyze business capabilities to identify potential service boundaries aligned with business functions rather than technical layers. Services should encapsulate specific business capabilities with clear interfaces to other domains.
Conduct event storming sessions with business and technical stakeholders to understand the flow of domain events through the system. These sessions often reveal natural boundaries where services can be separated with minimal disruption.
Map dependencies between components in the monolith to identify tightly coupled areas that will require special attention during extraction. Understanding these dependencies helps prioritize which services to extract first and which might need to move together.
Incremental migration patterns
Several proven patterns can guide the incremental extraction of services from a monolith:
Strangler fig pattern
The strangler fig pattern, introduced by Martin Fowler, provides a gradual approach to replacing functionality without a complete rewrite. Like the strangler fig vine that gradually envelops a host tree, this pattern involves building new services around the existing monolith until it can be completely replaced.
Implementation typically begins with an interception layer—often an API gateway or proxy—that routes requests either to the monolith or to new microservices based on configurable rules. As functionality moves to microservices, the routing rules change to direct more traffic to the new services.
This approach allows organizations to extract and replace functionality incrementally while maintaining a functioning system throughout the transition. It’s particularly effective for customer-facing applications where disruption must be minimized.
The strangler pattern works best when combined with clear functional boundaries. Extract complete business capabilities rather than technical components to ensure the new services provide business value immediately.
Parallel run pattern
For critical functionality where correctness is paramount, the parallel run pattern provides additional security during migration. In this approach, both the monolith and the new microservice process the same requests, but only the monolith’s response is returned to users initially.
The microservice’s responses are compared with the monolith’s responses to verify correctness without affecting users. This comparison can happen in real-time or through asynchronous analysis of logged responses.
Once confidence in the microservice reaches sufficient levels, traffic can be gradually shifted to the new implementation. This approach minimizes risk but requires additional infrastructure to duplicate requests and compare responses.
The parallel run pattern works well for complex business logic where subtle differences in implementation might lead to unexpected behavior. It provides concrete evidence that the microservice behaves identically to the monolith for all important scenarios.
Branch by abstraction
Within the monolith codebase itself, the branch by abstraction pattern facilitates gradual transition of internal components. This pattern creates an abstraction layer around functionality targeted for extraction, allowing multiple implementations to exist simultaneously.
Initially, the abstraction delegates to the existing monolith implementation. As the microservice develops, the monolith can be updated to call the external service through the same abstraction. Eventually, the old implementation is removed, leaving only the calls to the external service.
This pattern works particularly well for functionality that’s deeply embedded in the monolith and cannot be easily extracted through external interception. It allows for gradual transition while maintaining a functioning system throughout the process.
The abstraction layer also provides a clear demarcation of what functionality belongs to which service, helping enforce proper boundaries during and after the transition.
Data migration strategies
Perhaps the most challenging aspect of microservices migration involves transitioning from a shared database to service-specific data stores:
Database decomposition approaches
Several strategies exist for breaking apart a shared database. The simplest is to maintain the existing database initially but implement clear boundaries around which services can access which tables. This approach provides a starting point but doesn’t deliver the full benefits of independent data stores.
A more complete strategy involves creating separate databases for each microservice, with initial copying of data from the monolith database. This approach requires careful management of the transition period when data might exist in multiple places.
For complex scenarios, implementing a data access layer in the monolith can provide a transition mechanism. This layer initially accesses the monolith database but can gradually switch to calling microservices’ APIs for data access.
Managing data consistency
As data moves from a single database to multiple stores, transaction management becomes more complex. The simplest approach is to identify bounded contexts where consistency requirements allow for eventual consistency rather than immediate transactions.
For scenarios requiring transactions across services, patterns like sagas provide mechanisms to maintain consistency through choreographed or orchestrated sequences of local transactions. These patterns replace ACID transactions with compensating actions that can roll back changes when part of a process fails.
Event-driven architectures help maintain consistency by publishing events when data changes, allowing other services to update their data accordingly. This approach aligns well with domain-driven design principles and supports loose coupling between services.
Handling referential integrity
Moving from a single database with foreign key constraints to distributed data stores requires rethinking referential integrity. Service-specific databases often store references to entities owned by other services using identifiers rather than foreign keys.
These references require validation mechanisms different from traditional database constraints. Services might verify references by calling other services’ APIs, caching reference data locally, or implementing compensating actions when invalid references are detected.
In some cases, duplicating reference data provides a practical solution. For example, a service might store copies of essential information about related entities from other services, updating this information through events when the primary data changes.
Step-by-step migration roadmap
A successful migration follows a clear sequence of steps, each building on the previous work:
Start with non-critical services
Begin the migration with peripheral functionality that doesn’t impact core business operations. These services provide opportunities to establish patterns and practices with lower risk.
Good candidates include reporting services, notification systems, or batch processing components that operate asynchronously. These services often have clearer boundaries and fewer complex transactions spanning multiple domains.
Use these initial extractions to validate your infrastructure, deployment processes, and monitoring solutions. The experience gained with these services informs the approach for more critical components.
Implement API gateway
Early in the migration, implement an API gateway to manage routing between the monolith and new microservices. This component provides a stable interface for clients while enabling flexible routing as functionality moves between implementations.
The gateway also offers an opportunity to implement cross-cutting concerns like authentication, rate limiting, and request logging in a consistent manner across old and new components of the system.
As more services emerge, the gateway evolves to support service discovery, load balancing, and circuit breaking—essential capabilities for robust microservices architectures.
Extract bounded contexts iteratively
With initial services successfully deployed and the API gateway in place, begin extracting bounded contexts one by one. Prioritize contexts based on business value, technical feasibility, and dependency analysis.
Each extraction follows a similar pattern: identify the boundary, implement the new service, test thoroughly, deploy with parallel running if needed, and gradually transition traffic from the monolith to the new service.
Document patterns and lessons learned from each extraction to improve subsequent migrations. Build a repository of reusable components, templates, and patterns that accelerate the process while ensuring consistency.
Refactor the monolith as needed
As services are extracted, the monolith itself requires refactoring to support the new architecture. This refactoring might involve implementing the branch by abstraction pattern, cleaning up dependencies, or reorganizing code to align with emerging service boundaries.
In some cases, it’s beneficial to undertake preparatory refactoring before extraction to clarify boundaries and reduce coupling. This approach can simplify subsequent extraction but must be balanced against the risk of large-scale changes to the monolith.
Throughout the migration, maintain the health of the remaining monolith. Continue applying security patches, fixing bugs, and even implementing new features when necessary. The monolith remains a critical production system until the migration completes.
Address cross-cutting concerns
As the number of microservices grows, implement solutions for cross-cutting concerns like authentication, authorization, monitoring, and logging. These capabilities often begin as libraries shared across services but may evolve into infrastructure services that provide consistent functionality.
A service mesh like Istio or Linkerd can provide uniform handling of service-to-service communication, security, and observability. This infrastructure simplifies individual services by moving complex communication concerns to the platform layer.
Standardize patterns for common requirements like error handling, configuration management, and health checking. These standards ensure consistent behavior across services while reducing duplication of effort.
Testing and validation strategies
Comprehensive testing plays a critical role in successful migration:
Unit and integration testing
Maintain thorough unit test coverage for both the monolith and new microservices. These tests provide confidence that individual components behave as expected during and after migration.
As functionality moves from the monolith to microservices, migrate corresponding tests to ensure continued coverage. Update tests in the monolith that depend on extracted functionality to reflect the new architecture.
Integration tests that verify interactions between the monolith and new services become particularly important. These tests validate that the communication mechanisms, data translations, and error handling work correctly across the boundary.
Contract testing
As the number of service interactions grows, implement contract testing to verify that services meet their interface obligations. Tools like Pact or Spring Cloud Contract help define and verify these contracts.
Contract tests run against service interfaces to ensure they continue to meet the expectations of their consumers. These tests catch breaking changes before they impact other services, a particularly important capability during active migration.
By defining explicit contracts, teams gain confidence that their changes won’t unexpectedly break other components of the system. This confidence enables faster, more independent development even during the transition period.
Production validation
Beyond pre-deployment testing, implement validation mechanisms in production to verify that the migration doesn’t introduce issues. Feature flags allow gradual rollout of changes to subsets of users, limiting the impact of any problems.
Synthetic transactions that exercise critical paths through the system can detect issues before they affect users. These transactions run continuously in production, providing early warning of problems with the newly migrated functionality.
Comprehensive monitoring with clear alerts ensures quick detection and response to any issues. Dashboards that compare performance and error rates between the monolith and microservices implementations help identify subtle problems that might not appear in testing.
Organizational considerations
Successful microservices migration requires organizational changes alongside technical transformation:
Team restructuring
Traditional development teams organized around technical layers often don’t align well with microservices. Consider reorganizing into cross-functional teams responsible for specific services or business capabilities.
These teams should have end-to-end responsibility for their services, including development, testing, deployment, and operation. This reorganization might require new roles or skills within teams, particularly around operations and reliability engineering.
The transition to new team structures should align with the technical migration to avoid disrupting critical work. Some organizations implement hybrid models during the transition, with teams responsible for both monolith components and new microservices in the same domain.
Building microservices culture
Microservices require a different development culture focused on service ownership, API design, and distributed systems thinking. Invest in training and knowledge sharing to build these capabilities within development teams.
Establish communities of practice around key microservices concerns like API design, testing strategies, and observability. These communities share knowledge across teams and develop standards that ensure consistency without requiring centralized control.
Encourage experimentation and learning, recognizing that the first implementations might not be perfect. Create spaces for teams to share successes and failures, building a collective understanding of effective practices.
Governance and standards
While microservices enable team autonomy, some level of standardization remains essential for operational efficiency and system coherence. Implement lightweight governance that focuses on critical interfaces and capabilities rather than implementation details.
API standards ensure consistent patterns across services, making the overall system more comprehensible. Standards for observability, error handling, and resilience patterns help maintain operational quality across independently developed services.
DevOps platforms can enforce standards through templates, shared pipelines, and automated checks, reducing the cognitive load on development teams while ensuring consistency in key areas.
Implementing migration with CI/CD
Continuous Integration and Continuous Delivery play critical roles in successful microservices migration. These practices enable the rapid, reliable delivery essential for incremental migration.
As services are extracted from the monolith, they should immediately adopt modern CI/CD practices, even if the monolith itself uses more traditional deployment approaches. Each microservice should have its own deployment pipeline, enabling independent delivery.
CircleCI supports this transition through customizable workflows that accommodate both the evolving monolith and new microservices. Teams can start with simple pipelines for initial services, gradually adding more sophisticated testing, security scanning, and deployment stages as the migration progresses.
For organizations practicing Agile development, CircleCI’s integration with source control systems enables automated builds and tests for every change, providing rapid feedback on migration-related code. The platform’s orbs functionality allows teams to standardize common pipeline elements while maintaining service-specific configurations.
As the number of microservices grows, CircleCI’s workflow orchestration capabilities help manage the increasing complexity of building, testing, and deploying multiple interdependent services. Teams can create sophisticated pipelines that verify cross-service compatibility while still enabling independent deployment.
Conclusion
Migrating from a monolith to microservices is a journey that requires patience, careful planning, and incremental execution. By following a structured approach that prioritizes business continuity and risk management, organizations can successfully transform their architecture while continuing to deliver value to customers.
The strategies outlined in this article—from the strangler fig pattern to data migration approaches and organizational considerations—provide a comprehensive framework for this transformation. Each organization must adapt these strategies to their specific context, considering their technical landscape, business priorities, and team capabilities.
Remember that microservices are not an end goal but a means to achieve specific business objectives like improved delivery speed, better scalability, or enhanced resilience. Keep these objectives in focus throughout the migration, measuring progress against them rather than simply counting the number of services extracted.
With thoughtful planning, incremental execution, and continuous learning, your organization can successfully navigate the path from monolith to microservices, building a more flexible, scalable, and maintainable architecture for the future.
Ready to implement CI/CD pipelines for your monolith-to-microservices journey? Sign up for a free CircleCI account today and experience how continuous integration and delivery can help you transform your architecture while maintaining business continuity.
