Catalog
concept#Architecture#Software Engineering#DevOps#Reliability

Application Architecture

Concept for structuring application modules, interfaces and runtime behavior to guide scalability, maintainability and integration.

Application architecture defines the high-level structure and interaction patterns of software applications, including module boundaries, communication styles, and deployment topology.
Established
High

Classification

  • High
  • Technical
  • Architectural
  • Advanced

Technical context

CI/CD tooling (Jenkins, GitHub Actions)Observability stack (Prometheus, Grafana)API gateway and identity provider

Principles & goals

Clear module boundaries and explicit interfacesDesign for changeability and observable runtimeClear responsibilities and ownership
Build
Enterprise, Domain, Team

Use cases & scenarios

Compromises

  • Over-architecting without business benefit
  • Inconsistent interfaces due to missing governance
  • Performance hotspots due to incorrect partitioning
  • Pragmatic modularization by domain
  • Integrate automated tests and observability early
  • Version APIs and keep contracts stable

I/O & resources

  • Business requirements and SLAs
  • Existing system documentation
  • Non-functional requirements (performance, security)
  • Architecture documents and decision matrix
  • Interface and integration concept
  • Roadmap for migration and implementation

Description

Application architecture defines the high-level structure and interaction patterns of software applications, including module boundaries, communication styles, and deployment topology. It guides cross-cutting concerns such as scalability, maintainability and integration, providing trade-offs for technology and organizational decisions during system design and evolution.

✔

  • Improved scalability through appropriate decoupling
  • Higher maintainability via modular structure
  • Lower risk in releases and deployments

✖

  • Initial effort and increased design complexity
  • Not all requirements justify heavy decoupling
  • Coordination overhead between teams in distributed architectures

  • Throughput (requests/s)

    Measures the architecture's capacity under load.

  • Mean Time To Recover (MTTR)

    Indicates how fast a system is restored after failures.

  • Release frequency

    Indicates how often functional changes are delivered.

E‑commerce platform redesign

Decomposed a monolithic shop into domain-oriented services to improve scalability and speed up feature delivery.

Payment service integration

Implemented a standardized integration layer and security model for multiple payment providers.

Multi-tenant SaaS

Architecture with tenant-aware data handling and isolated deployment pipelines for cost efficiency and performance guarantees.

1

Prioritize quality attributes and use cases

2

Design architecture options and evaluate them with prototypes

3

Establish governance and interface contracts

4

Introduce incrementally with monitoring and feedback

⚠️ Technical debt & bottlenecks

  • Tight coupling between modules without clear interfaces
  • Outdated libraries and incompatible APIs
  • Lack of deployment automation
Deployment complexityData sharding and consistencyLatency-sensitive integrations
  • Introducing microservices without clear ownership leads to inconsistency
  • Optimizing the monolith completely instead of targeted modularization
  • Ignoring operational costs in cloud design
  • Specifying technical details too early before domain understanding
  • Missing metrics for architecture decisions
  • No feedback loops with operations teams
Software architecture and domain analysisNetworking and infrastructure knowledgeExperience with deployment and observability strategies
ScalabilityMaintainabilitySecurity and compliance requirements
  • • Regulatory requirements
  • • Existing infrastructure and legacy systems
  • • Budget and timeline constraints