Enterprise Architecture
Ten editions on the architecture patterns enterprise systems are actually built from — what each one buys, what it costs, and the conditions under which it stops paying.
- Editions
- 10
- Written by
- Neeraj Kumar
- Published
- 10 of 10
- Running
- August 27, 2026 — September 9, 2026
Enterprise Architecture Field Notes — the complete series
All ten editions in one document, in series order, with the diagram from each.
Download the field guide
No. 01 Layered Architecture: Start With Clear Boundaries
Architecture gets complicated when boundaries become blurry. Why one of the longest-standing patterns in enterprise software is still one of the most useful — and what goes wrong when its layers become folders rather than decisions.
No. 02 Modular Monolith: Modularity Before Distribution
Microservices are not the only way to achieve modularity, and for many systems they are not where I would start. What one deployment unit with real internal boundaries buys you — and how that design deteriorates.
No. 03 Microservices: Independence Has an Operational Cost
Microservices solve organizational and scaling problems, not fashion problems. The operational responsibilities that arrive with a distributed system, and the question worth asking instead of “should we use microservices?”
No. 04 Event-Driven Architecture: React Without Making Everything Wait
Sometimes the fastest way to scale a workflow is to stop making every system wait for every other system. Events do not remove complexity — they relocate it, and the relocation has to be designed.
No. 05 Service-Oriented Architecture: The Lessons Still Matter
Before microservices became fashionable, enterprises were already trying to solve service boundaries. What SOA got right, what it taught us the hard way, and why dismissing it as old architecture misses the point.
No. 06 Microkernel Architecture: Keep the Core Small
Keep the core small, then extend capability around it. Why a stable core with disciplined extension contracts lets teams innovate at the edges — and what turns a plug-in ecosystem into version drift.
No. 07 Space-Based Architecture: When Memory Becomes Part of the Design
At high transaction volumes the database can become the system's shared bottleneck. What it means to move frequently accessed state into a distributed in-memory grid, and the responsibilities that come with it.
No. 08 Pipeline Architecture: Make Every Stage Observable
Complex work becomes easier to manage when it moves through clear stages. The strength of a pipeline is not sequential execution — it is being able to understand and operate the flow.
No. 09 Data Platform Architecture: Storage Is Not the Product
Many AI problems eventually reveal themselves as data problems. Organizations often begin with the model; I usually look underneath it. What separates a data lake from a data platform.
No. 10 Architecture for AI and Agents: Models Are Only One Layer
The model may be the most visible component of an AI system, but it is only one part of the architecture. What changes when agents stop generating text and start taking actions.
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