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You can move from a modular monolith to microservices incrementally: keep the existing application running, put a routing seam in front of it, and move one cohesive capability at a time. During the transition, adapters can bridge old and new components, while a deliberate data plan establishes which system owns each record. Retire legacy code and structures only after dependencies are removed and the new path has been validated. This avoids a big-bang rewrite, but it does add temporary routing, synchronization, and operational complexity.
What changes—and what does not
This is an incremental replacement, not a project to rebuild the whole application before releasing anything. A façade or proxy sits between clients and the system. At first, it sends requests to the monolith; as capabilities are extracted, it routes selected requests to their new services and leaves the rest on the existing application. The client interface can remain stable where practical. AWS and Microsoft describe this approach in their guidance on the Strangler Fig pattern and its Microsoft implementation guidance.
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The monolith and services may coexist for a significant part of the migration. The goal is not to maximize the service count; it is to establish boundaries that let teams change and deploy meaningful business capabilities independently. Microservices are not automatically an improvement: distributing work can add latency, make tracing and debugging harder, and increase the operational burden, as AWS notes in its Well-Architected guidance on service architecture.
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Choose a capability that can become a real boundary
Start from business capabilities or subdomains, then verify the proposed boundary against the application’s actual dependencies. A module name is not evidence of independence. Trace calls between components, identify shared tables and writes, and note where deployment or transaction coupling crosses the proposed boundary. A lower-dependency edge capability may be a manageable first extraction, but it still needs a clear owner and a useful business purpose. AWS says decomposition patterns can be combined—for example, starting with business capabilities and refining boundaries by subdomain—in its monolith decomposition FAQ.
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Assess each candidate against these questions before moving it:
- Cohesion: Does the capability serve a distinct business need, or does its behavior depend on logic scattered across the application?
- Dependency direction: Which calls cross the proposed boundary? Can they pass through a stable interface instead of reaching into another component’s internals?
- Data ownership: Can the service become the clear owner of its data, or do shared tables, cross-domain joins, and writes make isolation impractical?
- Consistency and recovery: What delay can consumers tolerate if data is synchronized? How will you verify the copy and recover if cutover fails?
- Independent delivery: Can the service be built, released, monitored, and supported without coordinating every change with the monolith?
- Transition cost: What routing, adapters, synchronization, or duplicate-operation machinery will be needed temporarily, and what dependency removal will let you retire it?
Revisit those questions as the extraction progresses; service boundaries and data ownership should be demonstrated by the system’s behavior, not assumed from the initial design. Microsoft’s microservices readiness assessment covers independent deployability, data ownership, communication, and observability.
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Prepare the team and delivery system
An independently deployable service is also an independently operated unit. Before creating one, make sure the team can build and release it through automation, observe it in production, and respond when it fails. Plan for continuous integration and delivery, service ownership, monitoring, and support responsibilities. If every deployment still requires coordinated releases or nobody owns the service after launch, splitting the code has not yet delivered operational independence. Microsoft’s readiness guidance and AWS’s decomposition FAQ discuss these organizational and operational requirements.
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- Map the current seams. Record modules, data domains, synchronous calls, shared tables, and deployment dependencies. Confirm the dependency graph in the application rather than relying on names or diagrams alone.
- Install the routing seam. Put a façade or proxy in front of the application and initially route requests to the monolith. Design it for the required capacity and resilience; it must not become a bottleneck or a single point of failure. Microsoft describes this routing role in its Strangler Fig guidance.
- Select one cohesive capability. Choose a slice with manageable dependencies and a clear business boundary. Add a service for new functionality or move existing functionality behind the seam while leaving unrelated behavior in the monolith.
- Route only the selected behavior. Once the new service is ready, change the façade’s routing for that capability. Keep the client-facing contract stable where possible, and leave unextracted requests on the monolith.
- Bridge remaining cross-boundary calls. When old code needs extracted behavior, or a new service depends on behavior not yet moved, use an explicit adapter or anti-corruption layer. It translates between interfaces or conventions, rather than forcing both sides to adopt each other’s internals. Track its remaining callers so it can be removed deliberately.
- Move data under an explicit ownership plan. Decide which system is authoritative at each stage. If consumers need synchronized copies, state what delay they can tolerate and how they will handle it. For a database split, a common sequence is historical-data migration, change synchronization, consistency checks, cutover, and—after validation—removal of legacy tables and procedures.
- Repeat, simplify, and retire. Move dependent components as their boundaries become ready, then remove obsolete routes and adapters. Decommission the monolith only when its functionality and dependencies are gone. The façade is usually transitional, although Microsoft notes that it can remain as an adapter for legacy clients.
The sequence follows the incremental routing and replacement approach described by AWS and Microsoft; it is a pattern, not a universal schedule. The right boundaries and order depend on the application’s dependencies, data model, traffic, and team capabilities.
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Treat data migration as its own design problem
Extracting application code does not automatically give a service ownership of its data. If both the monolith and the new service write to the same tables indefinitely, the apparent service boundary may still be coupled to a shared database. Plan the transition by domain: specify the authoritative writer at each stage, which consumers need a copy, how updates reach them, and what consistency delay is acceptable.
When historical data must move, an initial load followed by change-data synchronization can keep the new store current while the old application remains active. Validate the new data against the source before routing production behavior to it. If synchronization is used to support legacy consumers, make clear that their copies may be eventually consistent; consumers must not assume immediate agreement unless the design provides it. AWS and Microsoft describe data synchronization and database decomposition considerations in their AWS Strangler Fig guidance and Microsoft guidance.
Rank #4
Keep rollback possible through the early cutover
Retain the old data structures and synchronization path while the new path is being validated and through the early cutover period. Define what evidence is sufficient to accept the new service and how to return traffic to the monolith if the checks fail. Removing legacy tables or procedures closes off a relatively simple rollback: restoring them and replaying changes later takes more effort and carries more risk. Microsoft’s Strangler Fig guidance explicitly treats database-object removal as a later step, after validation and cutover.
Compare extraction options by their transition costs
| Decision area | What to establish | Why it matters |
|---|---|---|
| Boundary quality | A cohesive, business-relevant capability with a plausible owner | A weak boundary can preserve internal coupling while adding a network hop. |
| Dependencies | Cross-boundary calls and a stable way to handle them | Unmanaged dependencies keep releases coordinated and make adapters permanent by default. |
| Data ownership | The authoritative writer, required copies, and treatment of shared tables | Unclear ownership makes consistency and cutover behavior difficult to reason about. |
| Recovery | Validation criteria, tolerated synchronization lag, and a rollback path | Dropping legacy structures too early makes recovery more difficult. |
| Independent delivery | Build, release, monitoring, and support without routine monolith coordination | Deployment independence requires both technical automation and team ownership. |
| Runtime and operations | Latency, availability, routing, tracing, debugging, and operating effort | Distributed calls introduce work that a single process may not require. |
| Temporary machinery | Façade, adapters, synchronization, and the conditions for removing each | The migration has value only if transitional complexity is tracked and eventually reduced. |
A façade lowers the risk of replacing the whole application at once, but it is transitional architecture with infrastructure and operating costs. Balance those costs against the risk reduction it provides, as Microsoft advises in its pattern guidance. AWS also warns that distributed compute can make latency requirements harder to meet and tracing, debugging, and operations more involved in its service architecture guidance.
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