concept#Architecture#Software Engineering#Platform#Reliability

Monolithic Architecture

An architectural style that consolidates all application functions into a single cohesive codebase.

Monolithic architecture bundles all components of an application into a single codebase and runtime.

Maturity

Established

Cognitive loadMedium

Classification

ComplexityMedium
Impact areaTechnical
Decision typeArchitectural
Organizational maturityIntermediate

Technical context

Integrations

Monolithic database solutions (e.g., relational DB)Central authentication servicesCI/CD tools for mono-repositories

Principles & goals

Principles

Promote modularity within the codebaseFavor a single deployment unit and simple pipelinesDefine clear interfaces and responsibilities

Value stream stage

Build

Organizational level

Enterprise, Domain, Team

Use cases & scenarios

Use cases

Scenarios

Compromises

Risks

Monolith can become a development bottleneck
Scaling can become costly and inefficient
Technical debt from lacking modularity

Best practices

Define clear module boundaries and APIs within the monolith
Automate end-to-end tests to secure critical flows
Make monitoring and health checks centrally available

I/O & resources

Inputs

Existing codebase or new monolith design
Infrastructure for central deployments
Team with full product context

Outputs

Unified application unit
Central CI/CD pipeline
Clearly defined module boundaries inside the codebase

Resources

Description

Monolithic architecture bundles all components of an application into a single codebase and runtime. It simplifies development, testing and deployment for small teams but makes fine-grained scaling and independent releases harder. Suitability depends on team size, business constraints and operational cost trade-offs.

✔Benefits

Simpler local development and debugging
Lower coordination overhead between teams
Consistent versioning and deployment

✖Limitations

Difficult fine-grained scaling of individual features
Higher risk of change due to tight coupling
Longer build and test times as codebase grows

Trade-offs

Metrics

Build duration
Time to complete a full build; affects feedback loops.
Release frequency
Number of releases per time period; indicates delivery agility.
Median recovery time
Time to recover after an outage; measures availability impact.

Examples & implementations

Classical monolith web application

A single WAR/JAR containing UI, business logic and data access in one codebase.

On-premise ERP system

Large centrally operated ERP with tightly coupled modules and shared deployments.

Monolith as a first step before microservices

MVP starts monolithic to get quick market feedback and later be split selectively.

Implementation steps

Analyze domains and identify modules

Introduce consistent build and release processes

Gradually introduce interfaces and contracts

⚠️ Technical debt & bottlenecks

Technical debt

Shared utility classes without versioning
Monolithic data models without clear ownership
Missing test coverage for integration layers

Known bottlenecks

Build timeDeploy durationDatabase locking

Misuse examples

Monolith scales uncontrollably by adding features without modularity
Trying to run several divergent domains inside one monolith
Lack of tests leads to unstable releases

Typical traps

Overestimating how long a monolith remains acceptable
Underestimating operational costs during scaling
Ignoring necessary modularization efforts

Required skills

Strong understanding of modular code architectureExperience with monolithic testing and CIOperational knowledge for scaling and monitoring

Architectural drivers

Performance and scaling requirementsTime-to-market and development speedOperational complexity and cost

Constraints

• Limited infrastructure granularity
• Monolithic data models hinder isolation
• Dependency on shared libraries