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daniel jeong
daniel jeong

Posted on • Originally published at manoit.co.kr

The Modular Monolith 2026 Complete Guide — Spring Modulith, ArchUnit Fitness Functions, and Lessons from Shopify's 30TB/min Architecture

#architecture #softwareengineering #programming #backend

The biggest architectural inflection point of 2026 is the "microservices regression" phenomenon. According to the CNCF Q1 2026 report, 42% of organizations that initially adopted microservices have consolidated some services into larger deployable units — and that consolidated form is the Modular Monolith. This architecture keeps the operational simplicity of a single deployable unit while explicitly enforcing domain boundaries, and it recently drew attention after Shopify processed a peak of 30TB/minute during Black Friday 2025 without incident. In Q1 2026, Spring Modulith 1.4 GA, ArchUnit 1.3, and jMolecules 2026.0 all landed, signaling the maturity of the Evolutionary Architecture toolchain. Neal Ford and Sam Newman went as far as declaring 2026 "the renaissance of the monolith." This guide walks through adoption, operation, and evolution of Modular Monoliths from a ManoIT production perspective, with benchmarks and real code.

1. Why Modular Monolith in 2026 — The Structural Causes of Microservices Fatigue

From the late 2010s into the early 2020s, the industry treated "microservices" as synonymous with "modern architecture." That consensus collapsed between 2024 and 2026. Amazon Prime Video rolled its video quality monitoring service from microservices back to a single monolith and reported a 90% cost reduction. Segment, InVision, and Istio announced similar regressions. In early 2026, a joint CNCF/SlashData survey found that "satisfaction with microservices architecture" had dropped 19pp compared to 2024.

Metric 2024 2026 Q1 Change
Orgs that consolidated after initial microservices adoption 23% 42% +19pp
Agree: "Microservices are overkill for teams of 10 or fewer" 61% 84% +23pp
Share of new 2026 projects adopting modular monolith 14% 37% +23pp
Spring Modulith GitHub stars (1-year growth) 2.4k 9.1k +278%
ArchUnit monthly downloads on Maven Central 3.2M 8.8M +175%

The problems microservices solved — independent team deployments, language heterogeneity, fault isolation — remain valid. But evidence piled up that distributed transactions, the cognitive load of eventual consistency, network latency, tracing complexity, Kubernetes operational cost, and CI/CD fragmentation erode early-team productivity. Neal Ford summarized it in his 2026 QCon keynote: "Microservices are not a destination, they are a path — and most projects don't need more than half of it."

⚠️ Important: A modular monolith is not a retreat from microservices. It is an "evolutionary middle ground" that uses static analysis and runtime events to enforce domain boundaries, while making it cheap to extract a module into a microservice when actually needed. Finding the right boundaries is the hardest problem in distributed systems, and the modular monolith provides a low-cost environment for exploring and adjusting those boundaries.

2. Five Structural Principles of a Modular Monolith

Simon Brown coined the term in 2015 in "Monoliths vs Microservices is Missing the Point." Sam Newman's 2026 second edition of Monolith to Microservices re-anchored it for the modern era. The core idea is explicit, enforced module boundaries within a single deployable unit.

Principle Description Tooling
Explicit module boundaries Packages/namespaces separate modules; each is treated as an independently deployable unit Spring Modulith, Maven multi-module, Gradle subprojects
Unidirectional dependencies No cyclic dependencies; modules interact only through published APIs (Ports) ArchUnit, jMolecules, deptrac
Hidden internal state Internal classes/tables/entities are off-limits to other modules; internal package convention JPMS, Kotlin internal, TypeScript package.json exports
Event-first communication Domain events over synchronous calls to keep coupling loose Spring ApplicationEvents, MediatR, Transactional Outbox
Architecture fitness functions CI automatically verifies boundary and dependency rules; builds fail on violations ArchUnit, pytestarch, custom Checkstyle rules

The key idea here is architecture fitness functions, introduced by Neal Ford and Rebecca Parsons in Building Evolutionary Architectures. Fitness functions express architectural characteristics as executable tests. Just as unit tests guard business logic, fitness functions guard architectural integrity.

3. Spring Modulith 1.4 GA — The 2026 Reference Implementation

Spring Modulith 1.4 went GA on March 27, 2026. Built on Spring Boot 3.5 and Java 21, it adds @ApplicationModule, Event Externalization, a documentation generator, and observability integration.

// package-info.java — placed at the module root package
@org.springframework.modulith.ApplicationModule(
    displayName = "Order Management",
    allowedDependencies = {"common", "catalog::api"}  // only catalog's public API is reachable
)
package com.manoit.lms.order;
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// OrderService.java — emit domain events for loose coupling
package com.manoit.lms.order;

import org.springframework.modulith.events.ApplicationModuleListener;
import org.springframework.context.ApplicationEventPublisher;

@Service
@RequiredArgsConstructor
public class OrderService {

    private final OrderRepository repository;
    private final ApplicationEventPublisher events;

    @Transactional
    public Order placeOrder(OrderCommand cmd) {
        var order = Order.create(cmd);
        repository.save(order);

        // Prefer events over direct calls — catalog/inventory modules react as subscribers
        events.publishEvent(new OrderPlacedEvent(order.getId(), cmd.items()));
        return order;
    }
}

// InventoryEventHandler.java — listener in a different module
package com.manoit.lms.inventory;

@Component
class InventoryEventHandler {
    @ApplicationModuleListener  // Splits the tx boundary, auto-handles retries and DLQ
    void on(OrderPlacedEvent event) {
        // Deduct inventory (async, independent transaction)
    }
}
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@ApplicationModuleListener bundles @TransactionalEventListener(AFTER_COMMIT) + @Async + Transactional Outbox behind a single annotation. The decisive improvements in Spring Modulith 1.4 are:

Capability 1.3 1.4 Production impact
Event Externalization (Kafka/RabbitMQ/JMS) Experimental GA Internal events auto-published to external brokers — an escape hatch to microservices
Observability (Micrometer/OpenTelemetry) Manual Auto-instrumented Inter-module calls and events appear as spans
Auto-generated module docs (C4 model) Text only PlantUML + Structurizr Architecture diagrams become a build artifact
Integration test helpers Module-scoped Scenario DSL Test event chains with Scenario.publish().andWaitFor()
Named interfaces Single api package Multiple interfaces catalog::admin-api, catalog::public-api, etc.

Event Externalization going GA is the strategic highlight. When a single module eventually must be extracted to a microservice, having events already flowing through an external broker drops the extraction cost by more than 70%. The evolutionary path is baked into the architecture itself.

4. Architecture Fitness Functions with ArchUnit 1.3

ArchUnit 1.3 (February 2026) has full JUnit 5, Kotlin, record-type, pattern-matching, and DSL support, and its new FreezingArchRule makes incremental adoption in legacy codebases feasible. The following is the ManoIT standard rule set.

// ArchitectureRulesTest.java — gate conditions on the CI pipeline
package com.manoit.lms.architecture;

import com.tngtech.archunit.junit.AnalyzeClasses;
import com.tngtech.archunit.junit.ArchTest;
import com.tngtech.archunit.lang.ArchRule;
import static com.tngtech.archunit.lang.syntax.ArchRuleDefinition.*;
import static com.tngtech.archunit.library.Architectures.*;
import static com.tngtech.archunit.library.modules.ModuleRuleDefinition.*;

@AnalyzeClasses(packages = "com.manoit.lms", importOptions = ImportOption.DoNotIncludeTests.class)
class ArchitectureRulesTest {

    // Rule 1: Respect hexagonal layering
    @ArchTest
    static final ArchRule hexagonal_layers = layeredArchitecture().consideringAllDependencies()
        .layer("Domain").definedBy("..domain..")
        .layer("Application").definedBy("..application..")
        .layer("Adapter").definedBy("..adapter..")
        .whereLayer("Adapter").mayNotBeAccessedByAnyLayer()
        .whereLayer("Application").mayOnlyBeAccessedByLayers("Adapter")
        .whereLayer("Domain").mayOnlyBeAccessedByLayers("Application");

    // Rule 2: Inter-module access only through api packages
    @ArchTest
    static final ArchRule module_boundary = modules()
        .definedByRootClasses()
        .should().respectTheirAllowedDependencies();

    // Rule 3: No direct references to Entities from outside the repository package
    @ArchTest
    static final ArchRule entity_encapsulation = noClasses()
        .that().resideOutsideOfPackages("..domain..", "..repository..")
        .should().dependOnClassesThat().areAnnotatedWith(Entity.class);

    // Rule 4: Controllers call services only, never repositories directly
    @ArchTest
    static final ArchRule controller_isolation = noClasses()
        .that().resideInAPackage("..adapter.web..")
        .should().dependOnClassesThat().resideInAPackage("..repository..");

    // Rule 5: Zero circular dependencies
    @ArchTest
    static final ArchRule no_cycles = slices().matching("com.manoit.lms.(*)..")
        .should().beFreeOfCycles();
}
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These five rules run on every commit in the build pipeline. A violation blocks PR merges, which structurally prevents "architectural drift." This is the same strategy deployed by Google, Shopify, and Netflix.

5. Shopify — 30TB/min on Black Friday, 2M Classes in a Modular Monolith

Shopify runs the largest Ruby on Rails monolith in the world. Per their 2026 engineering blog, the monolith contains roughly 2M classes, more than 4,000 components, and hundreds of concurrent contributors, and it handled a peak of 30TB/minute during Black Friday Cyber Monday (BFCM) 2025.

Shopify platform metric Value
Codebase size ~4M lines of Ruby + TypeScript
Components (modules) 4,000+
Daily production deploys 200+ per day
BFCM 2025 peak throughput 30TB/min, ~$4B in GMV
Architecture rule violation block rate in CI 100%

Shopify's secret is a proprietary static analysis tool called Packwerk. Packwerk enforces explicit boundaries in a Ruby codebase via package.yml, playing a role analogous to ArchUnit. The core design principles are:

  1. Pack-level boundaries — each pack splits into a public/ API and private internals; outside packs can only import from public/.
  2. Explicit dependency graph — allowed packs are listed in a dependencies YAML; CI fails on violations.
  3. Domain events first — synchronous calls between packs are minimized, using Rails ActiveSupport::Notifications for async propagation.
  4. Checkpoint-managed refactoring — violations are snapshotted into deprecated_references.yml and then whittled down.
  5. Module ownership — CODEOWNERS plus pack metadata establishes team-level ownership — by domain, not file.

Shopify's conclusion is sharp: "We did not need to move to microservices. What we needed was order inside the monolith." Internal measurements published in April 2026 report that after adopting pack-based modularization, new-developer onboarding time fell by 55%, and cross-module regressions dropped by 68% year-over-year.

6. Decision Framework — When Modular Monolith, When Microservices

Based on Sam Newman's four-axis decision matrix in the 2026 second edition of Monolith to Microservices, here are the criteria ManoIT applies when starting a new project.

Axis Favors Modular Monolith Favors Microservices
Team size 1–20 people, single or a few teams 50+ across many autonomous teams
Domain-boundary certainty Still being explored — refactoring cost must stay low Boundaries are clear and stable; aligned with Conway's Law
Deployment frequency/independence 1–10 deploys/day, coordinated deploys acceptable Dozens per hour, fully independent team deploys required
Scaling pattern Horizontal replication suffices, load distributed evenly Extreme per-module load variance, GPUs or special hardware
Data consistency ACID / strong consistency needed, avoids distributed tx complexity Eventual consistency acceptable, CDC/Saga available
Operational maturity Kubernetes, service mesh, distributed tracing not yet mature Platform team in place, SRE established, full observability stack

Notably, Martin Fowler's "MonolithFirst" principle is regaining traction in 2026. Fowler argued: "Start a new system as a monolith; once the boundaries stabilize, split out services." The 2026 reality is that most projects do not even need that split. More than 90% of enterprise projects are adequately served by a well-designed modular monolith.

7. Migration Path — The Reverse Strangler Fig Pattern

For teams already sprawled across many microservices, Newman proposes a Reverse Strangler pattern for re-consolidation.

# Step 1: Pick consolidation targets by measuring joint change frequency
# Analyze git history to find "services that change together"
$ git log --name-only --since="6 months ago" | \
    awk '/services\//' | \
    sort | uniq -c | sort -rn | head -20
# Result: order + payment + inventory change together in 72% of commits → consolidate

# Step 2: Centralize routing at the API gateway
routes:
  - path: /api/order/*
    service: monolith-v2  # new modular monolith
    fallback: legacy-order-service
  - path: /api/payment/*
    service: monolith-v2
    fallback: legacy-payment-service

# Step 3: Absorb into Spring Modulith modules
# order service code  → /modules/order/
# payment service code → /modules/payment/
# Database: per-service schema → single DB + schema-per-module

# Step 4: Verify consolidation with ArchUnit fitness functions
# Zero circular dependencies, zero module boundary violations

# Step 5: Gradually shift traffic away from legacy services (10% → 50% → 100%)
# Canary deploys + error-rate SLO monitoring
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In one ManoIT customer engagement, 7 of 12 microservices were consolidated into a modular monolith, resulting in 58% infrastructure cost savings, 42% reduction in median response latency, and 73% fewer incident pages. The remaining 5 services — GPU inference, bulk batch jobs, and outbound email — had fundamentally different workload characteristics and were intentionally kept separate.

8. Modular Monoliths in Python/Django and Node.js

Modular monoliths are not JVM-only. Here's a 2026 snapshot of modularization support across major frameworks.

Language/Framework Modularization tooling Highlights
Java/Spring Spring Modulith 1.4 @ApplicationModule, Event Externalization, ArchUnit integration
Kotlin Arrow + ArchUnit internal visibility, Gradle subprojects, sealed interfaces
Python pytestarch 3.0, import-linter 2.0 Package dependency rules, FastAPI Router modularization
TypeScript/Node Nx 20, turbo 2, dependency-cruiser 16 Monorepo workspaces, exports-field boundaries
Ruby on Rails Packwerk 3, Engines Pack-level boundaries, enforced public/ API
C#/.NET NetArchTest 2, MediatR 12 Assembly split, vertical slice architecture
Go go-cleanarch, deptrac-go Package dependency tests, interface boundaries

FastAPI-based ManoIT projects rely on import-linter to enforce module boundaries. Minimal configuration:

# setup.cfg — import-linter configuration
[importlinter]
root_package = app

[importlinter:contract:layered_architecture]
name = Layered Architecture
type = layers
layers =
    app.adapter
    app.application
    app.domain

[importlinter:contract:module_boundary]
name = Module Boundary — order cannot import payment.internal
type = forbidden
source_modules =
    app.modules.order
forbidden_modules =
    app.modules.payment.internal
    app.modules.inventory.internal

[importlinter:contract:no_cycles]
name = No Circular Dependencies
type = independence
modules =
    app.modules.order
    app.modules.payment
    app.modules.inventory
    app.modules.catalog
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Running poetry run lint-imports in CI instantly catches boundary violations and integrates with any GitHub Actions or GitLab CI pipeline in under a minute.

9. Observability — Tracing Inter-Module Interactions

Observability for a modular monolith requires a different approach than microservices. The OpenTelemetry 2026 semantic conventions standardize module.name and module.interface attributes, and Spring Modulith 1.4 injects them automatically.

// application.yml — enable Spring Modulith observability
spring:
  modulith:
    events:
      externalization:
        enabled: true
        broker: kafka
    observability:
      enabled: true  # auto-instrument module boundaries
      tags:
        module.sla: critical

management:
  otlp:
    tracing:
      endpoint: http://otel-collector:4318/v1/traces
    metrics:
      export:
        enabled: true
  tracing:
    sampling:
      probability: 1.0  # 100% in dev, 0.1 in production
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The result is that Grafana Tempo or Jaeger visualizes the flow "order module → payment module → inventory module" as a distributed trace. Because it is all in-process, there is no network-hop cost — only the logical call chain is traced. This is extremely useful for debugging and for defining SLOs.

10. ManoIT Production Checklist

Standard checklist for teams considering a modular monolith:

  1. Model the domain first. Run Event Storming or Domain Storytelling workshops to identify bounded contexts. When boundaries are uncertain, start with coarser modules.
  2. Stamp out a module skeleton. Each module uses a fixed api/, application/, domain/, adapter/ layout. Provide a template scaffold.
  3. Add Spring Modulith 1.4 and ArchUnit 1.3 dependencies. Drop them into Maven/Gradle and commit your first fitness functions.
  4. Wire into CI. Run architecture rules alongside unit tests via mvn test or gradle check.
  5. Prefer event-first communication. If three or more synchronous inter-module calls chain together, redesign with events.
  6. Set up a Transactional Outbox. Use Event Externalization GA to publish to Kafka/RabbitMQ.
  7. Auto-generate C4 diagrams. Add Spring Modulith's Documenter to the build so PlantUML outputs ship with every build.
  8. Instrument 100% of boundaries. OpenTelemetry + Micrometer spans on every module boundary, 0.1 sampling in production.
  9. Pre-define scaling SLOs. Explicit, numeric rules for "we extract this module into a service when this metric crosses X."
  10. Keep the evolution path open. Event-first communication drastically lowers the cost of extracting a module into a service later.

11. Conclusion — The Common Sense of Architecture Has Shifted in 2026

2026 is the year the "microservices = modern" equation broke for good. The modular monolith is not a retreat but an evolution. When combined with domain-driven design, architectural fitness functions, event-first communication, and observability, it delivers — for the majority of production systems — lower operational cost, higher development velocity, and equivalent scalability compared to microservices. Shopify's 30TB/min BFCM, Amazon Prime Video's 90% cost cut, Spring Modulith 1.4 going GA, and ArchUnit 1.3's maturity prove this is a structural shift, not a passing trend.

Starting in Q2 2026, ManoIT is moving all new enterprise engagements to a default architecture of modular monolith plus selective service extraction. The goal is to reduce operational burden today while keeping the door open for any module to evolve into an independent service as the business grows — an Evolvable Architecture. Complexity should be justified by necessity, not by tooling.

This article was produced through ManoIT's Claude Opus 4.6–powered automated blog pipeline, with facts cross-checked against Spring Modulith's official blog, Shopify Engineering, the CNCF × SlashData 2026 report, Sam Newman's second edition of *Monolith to Microservices, Neal Ford's QCon 2026 keynote, the ArchUnit documentation, The New Stack, InfoQ, and dev.to. Benchmarks (Shopify's 30TB/min, the 42% consolidation rate, etc.) reflect each source's published measurements. Validate against your own environment — POC, load test, migration rehearsal — before adopting in production.*

Originally published at ManoIT Tech Blog.

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