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Split a service when a well-understood business capability needs independent deployment, scaling, reliability, or ownership—and the team can handle the extra operational work. Otherwise, keep the application as a modular monolith: clear internal boundaries without making every interaction a network call.
What is the difference between a monolith and microservices?
A monolith is an application deployed as one unit. Its components may still be organized into modules with distinct responsibilities; “monolith” does not have to mean one tangled block of code. In a modular monolith, those boundaries are enforced inside the application while modules can share a process and, where appropriate, a transaction.
A microservices architecture divides an application into separately operated services, each responsible for a capability and communicating with others through interfaces. A service can be deployed, scaled, and owned independently in principle. In practice, those benefits depend on keeping its dependencies and data ownership clear enough that it does not have to coordinate every change with the rest of the system.
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AWS Well-Architected guidance treats a modular monolith as a valid starting point that can evolve toward services as a product and its needs grow. The choice is not a one-time verdict on which architecture is “better”; it is a decision about whether the independence gained by a particular split is worth its cost.
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How do the two architectures compare?
| Concern | Modular monolith | Microservices |
|---|---|---|
| Deployment | Modules ship as part of the application release, even if teams maintain good internal boundaries. | A service can ship separately when its interface and dependencies allow it; tightly coupled services may still need coordinated releases. |
| Communication | Modules can call one another within a process, avoiding network hops for internal work. | Services communicate over a network, which adds latency, failure modes, and the need to observe interactions. |
| Data and transactions | Sharing a database or using an in-process transaction can make some consistency requirements simpler, though modules should still have deliberate ownership. | Each service should own its data where possible. Cross-service consistency and transactions require deliberate design and can become difficult if services constantly read or update one another’s data. |
| Scaling and failure isolation | The application may need to scale or recover as a unit, even when one module has a distinct load or availability profile. | A capability can be scaled or isolated separately when its workload or reliability needs justify independent operation. |
| Operational demands | Fewer separately operated components generally mean fewer service deployments and interactions to monitor and debug. | Teams must handle service discovery, deployment, monitoring, distributed testing, tracing, and incident response across components. |
| Team ownership | Teams can own modules, but changes spanning modules may still converge on a shared release. | Teams can own capabilities end to end if interfaces are stable; circular dependencies or frequent coordination can erase that independence. |
When should you split a service?
Make the case for a specific capability, not for “microservices” in general. A split is most compelling when one or more real constraints can be relieved by operating that capability independently—and the boundary is cohesive enough to do so.
- Release contention is real: A capability changes often, but shipping it requires coordinating a release of the entire application. Independent deployment could reduce that coupling.
- Its load or availability needs differ: One component needs a distinct scaling pattern, or its failures should not take down unrelated functionality. Separate operation may help, provided the system can manage the new dependencies.
- A team can own it end to end: A team has the domain knowledge and responsibility to maintain the service, its data, interface, deployment, and incidents without routine coordination for ordinary changes.
- The business boundary is understood: The capability or domain subdomain has a coherent purpose and a relatively stable interface. AWS guidance emphasizes that identifying such boundaries requires domain knowledge, not just rearranging code.
- It can own its data: The proposed service can make its own decisions without constant cross-service reads, writes, or transaction coordination.
These are reasons to investigate an extraction, not a guarantee that it will pay off. The decision also depends on whether the organization can support the resulting distributed system.
When should you keep the monolith?
Keep a modular monolith when it already meets delivery, performance, and reliability needs and there is no concrete problem that independent services would solve. It is often the better fit in these situations:
- The boundary is still unclear: If teams do not yet understand the business capability or its responsibilities, a service split can freeze a poor boundary into a harder-to-change interface.
- Changes routinely cross the proposed seam: If ordinary work requires coordinated edits or releases in several components, they may be one capability divided artificially.
- Strong consistency matters across the functionality: If a workflow depends on a single transaction, splitting it may replace a simple in-process operation with a harder consistency problem.
- The team or platform is not ready: Multiple services need support for deployment, discovery, monitoring, testing, debugging, and incident response. If that support would outweigh the independence gained, retain the simpler operating model.
- Communication would be chatty or latency-sensitive: Many network calls between services—or several network hops on a user-facing request—can undermine responsiveness and signal that the responsibilities belong together.
A modular monolith is not a failed intermediate state. It lets a team preserve internal structure and learn where boundaries belong before paying the costs of separate operation.
How can you assess a proposed boundary?
For each candidate service, answer these questions with the current application and a plausible extracted design in mind:
- What problem will the split solve? Name the specific release bottleneck, distinct scaling need, reliability concern, or ownership friction. If the answer is only “we need microservices,” the case is not yet concrete.
- What business capability does it represent? Map the functionality to a capability or domain subdomain. Check whether the proposed responsibility is coherent and whether the people closest to the domain agree on its limits.
- Can it change and ship independently? List the components, contracts, and teams that must change together. Microsoft architecture guidance recommends independent deployment and warns that interdependencies can force services to deploy together.
- Can it own its data and transactions? Identify which service is authoritative for each piece of data, who can update it, and how workflows spanning boundaries remain consistent. Frequent cross-service access or transaction coordination is a warning that the split may be premature or misplaced.
- What does a normal request require? Sketch the calls for a user-facing workflow. Count the service interactions and consider what happens when a dependency is slow or unavailable. Excessive interservice chatter is a sign that some functions may belong together.
- Who operates it? Identify the team and the deployment, monitoring, tracing, testing, and incident-response practices needed to support the service. An independent codebase without operational ownership is not independent in the useful sense.
There is no universal service count or percentage that determines the right answer. AWS and Microsoft guidance describes trade-offs, not a threshold that applies to every workload; the boundary, workload, and team capacity matter.
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How do you split services incrementally?
When a split is justified, it does not have to mean replacing the whole application at once. AWS’s Strangler Fig guidance describes gradually routing selected functionality to a replacement while the existing application continues to run. That transition still needs explicit performance and rollback planning.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitches- Start with the problem and map the domain. Document the pressure to change, then map the relevant business capabilities, modules, data, and transactions. Confirm that the proposed service boundary fits the domain rather than merely matching a convenient code or database boundary.
- Choose a low-dependency seam. Prefer a capability that can be owned and deployed with relatively few dependencies. Microsoft’s assessment guidance recommends beginning with edge services, rather than starting with a component entangled throughout the application.
- Define ownership and the interface. Decide which service owns the capability’s data and what contract other parts of the system use. Avoid an interface that exposes internal implementation details or requires frequent synchronized changes.
- Keep both sides working during transition. Route only the selected functionality to the replacement while the monolith continues serving the rest. Plan how traffic can be redirected if the new path fails, and account for the routing layer’s performance impact.
- Operate and reassess the boundary. Observe actual deployments, dependencies, latency, data consistency, and team coordination. If the service remains chatty, must be released in lockstep, or makes consistency difficult, reconsider whether it is too fine-grained or was extracted too early.
What are the warning signs of a bad split?
- Services that routinely need coordinated releases despite being nominally independent.
- Calls that cross service boundaries repeatedly to complete one ordinary operation.
- Multiple services that must update shared data or coordinate transactions to keep basic invariants intact.
- A user-facing path whose latency or reliability depends on an unnecessarily long chain of services.
- Teams that cannot make routine changes without negotiating with several other service owners.
- Operational overhead that consumes more capacity than the deployment, scaling, reliability, or ownership benefit the split was meant to provide.
These symptoms do not automatically prove that every service should be recombined. They are evidence to revisit the boundary, interaction pattern, data ownership, or reason for the split.
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