Practical Distributed Systems Architecture
Real architecture cases, decision frameworks, and technology trade-offs from production systems: migrations, data-heavy flows, reliability, and system evolution.
Serhii Veremiienko — Distributed Systems Architect with a backend background. I write about migrations, data-heavy systems, reliability, architecture trade-offs, and decisions that have to survive production reality.
Cases from Practice
Real systems, real constraints, real trade-offs.
MS SQL -> PostgreSQL Migration
How to migrate with validation, rollback thinking, and minimal operational drama.
Test Automation in a Large Monolith
Where backend E2E confidence actually comes from when the system is already big.
AWS Cost Optimization
How to save 500k/year on infrastructure.
Redshift Analytics Without Overengineering
How to keep analytics useful without turning the platform into a second product too early.
Decision-Making Algorithm
I do not start with tools. I start with the problem, the constraints, and what must be validated with facts.
- 01
Problem
Define the real engineering problem before choosing an implementation path.
- 02
Constraints
Make the business, delivery, operational, and data limits explicit.
- 03
Options
Compare realistic solution paths instead of arguing from defaults.
- 04
POC
Validate the risky assumptions early when facts are still cheap to collect.
- 05
Implementation
Turn the decision into something teams can build, run, and maintain.
- 06
Validation
Measure correctness, rollout safety, and operating reality after the change.
Problem-Oriented Architecture Learning
The evolution of applications and engineering competence through the lens of real problems.
System Evolution Framework
A compact staged view of how systems evolve from MVP to scale, reliability, and stronger ownership.
Engineer Growth
How engineering judgment grows from local execution to system-level ownership as systems become more complex.