Microservices were supposed to make software easier to scale. Instead, many engineering teams discovered that they had scaled their architecture faster than they scaled their engineering organization. What started as a handful of services can eventually become dozens or hundreds of independently deployed components, each with its own database, monitoring, deployment pipeline, authentication rules, network policies, and failure modes. The application may be technically distributed, but the engineering workload becomes distributed too.
That is why 2026 is seeing renewed interest in something that was once considered old-fashioned: the monolith. The claim that 70% of teams are consolidating back to single codebases should be treated as a provocative headline rather than a verified industry-wide statistic. The more defensible observation is that engineering organizations are reassessing whether microservices actually solve their current problems or simply introduce another layer of operational complexity.
For many backend teams, the answer is increasingly a modular monolith: one deployable application, clearly separated internal modules, strong boundaries, and the option to extract services later when there is a genuine reason to do so.
Microservices Solved a Real Problem
Microservices did not become popular by accident. Large applications can become difficult to maintain when every feature lives inside one enormous codebase. Teams working on unrelated functionality can interfere with each other, releases become increasingly risky, and scaling one component may require scaling the entire application.
Microservices offered a different model. An organization could divide functionality into independently deployable services. A payments service could scale separately from a notification service. Different teams could own different domains. Individual components could use technologies that fit their specific requirements.
For organizations with large engineering teams and genuinely independent workloads, this model can work extremely well. The problem begins when microservices are introduced before the organization actually needs them.
The Hidden Cost of Distributed Backends
A monolith has an obvious cost: the codebase can become large and difficult to manage. Microservices introduce a different cost: distributed complexity.
A simple request may now travel through an API gateway, authentication service, user service, business service, message broker, database service, and external API. Every network boundary introduces another potential failure.
Timeouts become important. Retries become dangerous. Distributed tracing becomes necessary. Service discovery has to work. Authentication must be consistent. API contracts need to remain compatible. Deployment order can matter. Database transactions become more complicated.
The business feature may take a few hundred lines of code. The infrastructure required to operate it can take considerably more.
The Operational Tax Is Changing the Conversation
The biggest architectural question in 2026 is no longer simply, “Can microservices scale?” They clearly can. The better question is: Does the additional operational complexity create enough value for this particular system?
A team running a large global platform with independent domains, multiple engineering groups, and highly variable workloads may benefit from service-level isolation. A team building an internal application with ten engineers may gain very little from operating twenty independently deployed services.
Architecture should therefore follow organizational and product requirements rather than architectural fashion.
The Monolith Is Not the Same as a Big Ball of Mud
There is an important distinction between a monolith and an unstructured monolith. A poorly designed monolith can become a tightly coupled mess where every module depends on every other module.
A well-designed monolith can have strong internal boundaries. A backend might contain separate modules for identity, accounts, payments, orders, notifications, reporting, and administration. Each module can have defined responsibilities, interfaces, ownership rules, and testing boundaries while still running inside the same application.
This approach is often called a modular monolith. The deployment remains relatively simple, while the codebase retains architectural boundaries that make future extraction possible.
Why Modular Monoliths Are Getting Attention
The modular monolith occupies an interesting middle ground. It avoids some of the operational overhead associated with distributed systems while preserving separation inside the application.
Teams can have one repository, one application, strong internal modules, shared deployment, and clear ownership boundaries. If a particular module eventually develops a legitimate need for independent scaling, deployment, or ownership, it can potentially become a separate service.
That creates an important architectural advantage: teams do not have to predict the future. They can extract services when the business and technical requirements justify the cost.
Microservices Create More Failure Modes
Consider a traditional monolithic backend. A request reaches the application, business logic executes, and the database is queried.
Now consider a distributed implementation. The request may travel through multiple services before the final response is generated. A service may be unavailable. A network connection may time out. A downstream database may become slow. A message may be duplicated. A retry may trigger an operation twice. One service may deploy a breaking API change.
These are not theoretical concerns. Distributed systems require engineers to design explicitly for partial failure. A monolith does not eliminate failures, but fewer network boundaries can mean fewer distributed failure modes.
Debugging Is Different Too
Debugging a monolith can be straightforward. An engineer can often reproduce a request locally, inspect the call stack, examine database operations, and identify the failing module.
With microservices, the same investigation may require distributed traces, logs from multiple services, correlation IDs, message queues, deployment histories, and infrastructure metrics.
Observability becomes a fundamental requirement rather than an optional enhancement. This does not make microservices wrong. It simply means the organization has to be prepared to operate a distributed system.
Deployment Complexity Matters
Independent deployment is one of the major advantages of microservices. But independent deployment only creates value when teams actually need independent release cycles.
If five services always need to be changed together, tested together, and deployed together, separating them may not provide much practical independence. In some cases, the organization ends up with microservices that are technically independent but operationally coupled.
That is one of the clearest warning signs that service boundaries may have been created too early.
The Database Question
Database architecture is another major consideration. A monolith commonly works with a shared database, which makes transactions and reporting relatively straightforward.
Microservices encourage database ownership by service. That improves isolation but makes cross-service operations more complicated. A workflow that previously required one database transaction may now involve multiple services and potentially asynchronous coordination.
Engineers may need patterns such as event-driven workflows, sagas, idempotency, outbox processing, and eventual consistency. Those techniques are powerful, but they also increase application complexity.
If the business does not need that level of distribution, introducing it prematurely may create unnecessary engineering work.
Team Structure Should Influence Architecture
Architecture and organizational structure are closely connected. A company with dozens of autonomous engineering teams may benefit from services that map cleanly to team ownership. A small engineering group may struggle with the operational burden of maintaining many services.
This is why there is no universal answer to the microservices-versus-monolith debate. The architecture should reflect team size, domain boundaries, deployment requirements, scaling characteristics, reliability requirements, and organizational maturity.
Ignoring these factors can turn either architecture into a problem.
When Microservices Still Make Sense
Microservices remain a strong choice for certain backend environments. They can make sense when different domains need independent scaling, when multiple teams need independent ownership, when deployment boundaries are genuinely valuable, or when individual components have significantly different infrastructure requirements.
They can also be useful when a platform has clear domain boundaries and the organization already has mature observability, CI/CD, security, service ownership, and incident-management practices.
The important point is that microservices should solve a problem. They should not exist simply because a technology organization considers them the modern default.
When a Monolith Makes More Sense
A monolithic architecture can be appropriate when the product is still evolving rapidly, the engineering team is relatively small, business workflows are tightly connected, or operational simplicity is more valuable than independent service deployment.
It can also be a sensible choice for products where most components scale together. The decision becomes especially attractive when the alternative is a large collection of services that require significant infrastructure but provide little independent value.
The Rise of the “Monolith First” Approach
One architectural strategy gaining attention is to start with a modular monolith and extract services only when evidence justifies the move.
Instead of asking, “Which services should we create?” teams ask, “Which boundaries actually need to become services?”
This changes the architecture conversation. The initial system can remain relatively simple while engineers observe real production behavior.
Over time, specific modules may demonstrate clear reasons for separation. Perhaps one component needs dramatically different scaling. Perhaps another requires independent deployments. Perhaps a team needs full ownership of a particular domain.
Those are stronger reasons to create a service than simply following a predefined microservices diagram.
Do Not Confuse Fewer Services With Better Architecture
Consolidation is not automatically good architecture either. A massive monolith with no boundaries can become extremely difficult to maintain.
The objective should not be to minimize the number of services. The objective should be to minimize unnecessary complexity.
A well-structured monolith can be better suited to a particular workload than poorly designed microservices. Well-designed microservices can also be appropriate when independent scaling and ownership genuinely matter.
Architecture quality comes from appropriate boundaries, not from the number of repositories or deployments.
What Backend Teams Should Measure
Before migrating from microservices to a monolith, or splitting a monolith into services, teams should examine actual engineering data.
Useful measurements include deployment frequency, lead time for changes, incident frequency, mean time to recovery, infrastructure cost, service-to-service traffic, database complexity, developer onboarding time, build duration, test duration, and the number of services that must change for a typical feature.
These measurements often reveal whether the architecture is helping or creating friction. If a feature routinely requires coordinated changes across eight services, the organization may want to reconsider those boundaries. If one service has radically different scaling requirements and can operate independently, separation may be justified.
A Practical Migration Strategy
Organizations considering consolidation do not necessarily need to rewrite everything. A gradual approach is often safer.
Teams can identify tightly coupled services, establish module boundaries, move related functionality into a shared codebase, simplify service communication, and gradually retire infrastructure that no longer provides meaningful value.
The reverse is also possible. A modular monolith can provide a starting point for gradually extracting services when production evidence shows that separation is worthwhile.
This makes architecture evolutionary rather than irreversible.
Where Engineering Teams Fit Into the Decision
Engineering organizations such as GeekyAnts, Thoughtworks, and other product engineering teams work across both monolithic and distributed backend architectures. The important part is evaluating the application’s actual requirements before deciding whether functionality should remain within a modular codebase or become an independently operated service.
The architecture should support the product and engineering organization rather than forcing the organization to support the architecture.
What Engineering Leaders Should Ask in 2026
Before adopting or consolidating microservices, engineering leaders should ask: Are our services genuinely independently deployable? Do they have clear ownership? Do they scale independently? Are service boundaries aligned with business domains? How much time does the organization spend maintaining distributed infrastructure? How many requests cross service boundaries? How often do services need coordinated releases? Could strong module boundaries solve the problem without introducing network boundaries? Are observability and incident-management capabilities mature enough for the current architecture?
These questions provide more useful answers than simply asking whether microservices or monoliths are “better.”
FAQs
Is a monolith better than microservices in 2026?
Neither architecture is universally better. A monolith can reduce operational and networking complexity, while microservices can provide independent deployment, scaling, and ownership. The appropriate choice depends on the application’s requirements and the organization’s structure.
Are companies moving away from microservices?
Some organizations are consolidating services or adopting modular monoliths, but there is no reliable universal percentage showing that most companies are abandoning microservices. Many large-scale platforms continue to use microservices where service-level independence provides clear value.
What is a modular monolith?
A modular monolith is a single deployable application divided into well-defined internal modules. The modules maintain clear responsibilities and boundaries without requiring each domain to run as a separate service.
Why are teams reconsidering microservices?
Teams may reconsider microservices because of operational overhead, service-to-service communication, distributed debugging, deployment coordination, infrastructure costs, and database complexity. These concerns are particularly relevant when services do not need genuine independence.
Are microservices harder to maintain than monoliths?
Microservices can introduce additional operational responsibilities because teams must manage network communication, service discovery, observability, deployments, security, and distributed failure scenarios. A monolith can be simpler operationally but becomes difficult when its internal structure is poorly managed.
Can a monolith scale?
Yes. A monolithic application can scale vertically and horizontally, depending on its architecture and workload. A modular monolith can also be optimized internally before specific components are separated when independent scaling becomes necessary.
When should a monolith be split into microservices?
A split can make sense when a domain requires independent scaling, deployment, ownership, reliability characteristics, or technology choices that are difficult to achieve within the existing application.
Can companies migrate from microservices back to a monolith?
Yes. Consolidation can be performed incrementally by identifying tightly coupled services, bringing related functionality into a modular codebase, simplifying service communication, and retiring unnecessary infrastructure. A complete rewrite is not always required.
What is the biggest disadvantage of microservices?
One major disadvantage is distributed-system complexity. Multiple services introduce additional network, deployment, observability, security, and data-management concerns that teams must operate continuously.
What should backend teams choose in 2026?
Backend teams should evaluate workload characteristics, team structure, domain boundaries, scaling requirements, deployment independence, operational maturity, and total system complexity before choosing an architecture. Starting with a modular monolith can also preserve the option of introducing microservices later when there is a demonstrated need.
The Backend Architecture Reset
The architectural debate is moving away from “monolith versus microservices” and toward a more practical question: where should complexity live?
A monolith concentrates complexity inside the application. Microservices distribute complexity across applications, networks, infrastructure, deployments, data stores, and operational processes.
Neither approach eliminates complexity. They move it.
That is why the growing interest in modular monoliths is significant. Teams are realizing that they can preserve clean architecture and domain boundaries without immediately accepting the operational cost of a distributed system.
Microservices will remain important for many large-scale platforms. But for other teams, consolidation can reduce deployment overhead, simplify debugging, improve local development, and make backend systems easier to operate.
The strongest architecture in 2026 may therefore not be the one with the most services. It may be the one that introduces exactly as much distribution as the product, organization, and workload actually require.
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