https://chatgpt.com/c/6a8b88b1-96c0-83ec-babd-b0d67f5c22f3
Summary and riff on: https://www.reddit.com/r/EnterpriseArchitect/comments/1eq3kyw/what_are_the_differences_between_conceptual/
The thread’s main takeaway is that architecture terminology is inconsistent across organisations and disciplines, but a useful hierarchy emerges: Contextual → Conceptual → Logical → Physical, with Application Architecture being a domain/view, not necessarily another level. (Reddit)
| Level | Main question | What it describes | Typical contents |
|---|---|---|---|
| Contextual | Why? | Business motivation and environment | Drivers, stakeholders, goals, problems, opportunities, external context |
| Conceptual | What are we trying to achieve? | High-level shape of the solution | Capabilities, business services, system context, major concepts, scope and boundaries |
| Logical | How should it work, independent of implementation? | Functional decomposition and relationships | Logical components/services, responsibilities, data flows, integrations, logical data models, security responsibilities |
| Physical | How exactly will it be implemented? | Concrete implementation | Technologies, products, databases, servers/cloud services, networks, clusters, redundancy, persistence, deployment configuration |
This four-level interpretation is explicitly mentioned in the thread as a TOGAF-style model: Contextual = why; Conceptual = business services; Logical = business/data/application/technology without implementation details; Physical = actual assets and implementation details. (Reddit)
This is the highest level and establishes why the architecture exists.
Think:
“We need customers to be able to search our property inventory using natural language.”
You would generally show business actors, objectives, major capabilities, external systems and boundaries. There should be little or no solution design.
Conceptual architecture starts describing what the solution consists of, but remains deliberately abstract and business-oriented.
For example:
User
↓
Property Search
↓
Property Information
Or perhaps:
Search Experience
|
+-- Query Understanding
+-- Property Retrieval
+-- Ranking
The thread characterises this as useful for business cases, executive alignment, defining scope and communicating the opportunity before getting deeply technical. (Reddit)
A useful distinction is:
Contextual: Why are we doing this?
Conceptual: What major capabilities/concepts are required?
Logical architecture decomposes the conceptual solution into functional components and their relationships, while avoiding commitment to specific implementation technologies.
For example:
Query API
↓
Query Understanding
↓
Retrieval Orchestrator
↙ ↘
Lexical Vector
Retrieval Retrieval
↘ ↙
Fusion
↓
Ranker
The important characteristic is that these represent responsibilities, rather than necessarily deployable services.
One commenter gives a particularly useful systems-engineering definition: logical/functional architecture describes the functions a system requires and how those functions are grouped; later those functions are allocated onto physical implementation components. (Reddit)
So:
Logical component:
"Relational datastore"
Physical component:
"Amazon Aurora PostgreSQL 16"
Similarly:
Logical:
Vector retrieval
Physical:
Qdrant 1.x cluster running on GKE
The thread also makes the useful point that logical architecture can span several domains:
Logical Business Architecture
Logical Application Architecture
Logical Data Architecture
Logical Technology Architecture
So logical architecture ≠ application architecture. Application architecture can itself be represented logically or physically. (Reddit)
Physical architecture maps those logical responsibilities onto actual technologies and implementation units.
For example:
Cloud Load Balancer
↓
QUAPI Kubernetes Service
↓
Retrieval Orchestrator pod
↙ ↘
OpenSearch Qdrant
cluster cluster
↘ ↙
Ranker pod
It may include things such as:
The thread describes this as the low-level implementation of the logical architecture. (Reddit)
This is where the thread contains some disagreement.
One interpretation is:
Application architecture = the logical view of applications and their relationships.
For example:
Home Loan Application
├── Credit Check System
├── Valuation System
└── Document Management System
The applications themselves are treated as components, without showing their internals. (Reddit)
Another commenter uses Application Architecture to mean the internal architecture of an individual application:
API layer
↓
Domain/service layer
↓
Repository/data-access layer
↓
Database
including coding patterns, persistence, security and monitoring. (Reddit)
I think the cleanest way to reconcile these is to treat Application Architecture as a subject/domain rather than an abstraction level:
Architecture domain
↓
Application Architecture
/ \
Logical view Physical view
For example:
Logical application architecture
--------------------------------
Search API
Query Understanding
Retrieval
Ranking
Physical application architecture
---------------------------------
FastAPI service
Python package
vLLM endpoint
OpenSearch 3.x
Qdrant cluster
GKE deployment
That avoids making “Application” compete with conceptual/logical/physical.
Connecting this to the distinction you were exploring previously, I would not treat deployment and runtime as additional levels after physical.
Instead there are two different dimensions:
ABSTRACTION LEVEL
Contextual
↓
Conceptual
↓
Logical
↓
Physical
VIEWPOINT
Functional / component
Data
Application
Integration
Deployment
Runtime / data flow
Security
Network
etc.
So you can have, for example:
Logical architecture
Query Understanding → Retrieval → Ranking
Physical component architecture
QUAPI → OpenSearch/Qdrant → Ranking Service
Deployment architecture
GKE
├── QUAPI pods
├── Retrieval pods
└── Ranking pods
OpenSearch managed cluster
Qdrant cluster
Runtime/data-flow architecture
HTTP request
↓
QUAPI
↓ 15 ms
Query Understanding
↓
parallel retrieval
├── OpenSearch
└── Qdrant
↓
RRF
↓
reranker
↓
response
So my preferred mental model from the thread would be:
Architecture abstraction
────────────────────────
Contextual
WHY
↓
Conceptual
WHAT
↓
Logical
HOW, abstractly
↓
Physical
HOW, concretely
Orthogonal viewpoints
─────────────────────
Business
Application
Data
Integration
Security
Technology
Deployment
Runtime / data-flow
That is more robust than trying to put terms such as application architecture, deployment architecture and runtime architecture into the same hierarchy as conceptual/logical/physical. The Reddit discussion itself repeatedly points out that mixing those different classification systems is the main source of confusion. (Reddit)