Topic guide
Architecture & Distributed Systems
Software architecture is the set of boundaries, data flows, and operational decisions that determine how a system behaves as it changes and fails. These articles focus on those decisions in working systems: queues and streams, event delivery, idempotency, scaling, and safe evolution.
The practical questions
- Choosing between queues, streams, and event buses
- Designing retry-safe and idempotent operations
- Scaling systems without hiding their constraints
- Changing production systems without avoidable downtime
Articles on Architecture & Distributed Systems
10 articles, ordered by topical relevance.
Event-Driven Architecture Without Kafka
Most teams reach for Kafka too early. Here is how to build a production event bus with Celery and Redis, the patterns that make it reliable, and the four conditions where Kafka actually earns its place.
architecture · kafka · software engineering · redis · celery · event drivenThe Difference Between a Queue and a Stream
Queues move work forward. Streams preserve a history consumers can read from. That difference changes ownership, replay, and failure handling.
architecture · kafka · redis · software engineeringIdempotency Is Not a Nice-to-Have
Every retry, webhook, and payment system depends on idempotency. Most engineers treat it as an afterthought. Here is what happens when they do, and what it actually takes to build operations that are safe to repeat.
architecture · distributed systems · software engineeringAI Scalability: What It Actually Means for Software Architecture
AI can generate working software quickly, but AI scalability depends on architecture, constraints, and disciplined engineering after the proof of concept.
architecture · scalability · ai · software engineeringIndexes are not free
Adding an index speeds up reads. It also slows down writes, increases storage, and adds a maintenance burden that compounds over time.
postgres · database · architecture · software engineeringThe Cost of Making Everything Real Time
Real time sounds like an obvious improvement until you price it. The useful question is not how fast the data can arrive, it is how often anyone actually acts on it.
data · architecture · product engineering · software engineeringWhy RAG Fails in Production
Most RAG systems fail at retrieval, not generation. The fix is usually better evidence, ranking, and product logic.
ai · llms · architecture · software engineeringWhat Zero-Downtime Deployment Actually Requires
Zero-downtime deployment depends on overlapping versions, safe traffic shifts, and database changes that work before and after release.
devops · architecture · database · software engineeringWhat a Data Pipeline Actually Is
ETL has three letters. Most people can explain two of them. The third is where teams make decisions that shape who owns data, when it is trustworthy, and how hard it is to change.
data · architecture · engineering · software engineeringSafe Database Migrations at Scale
A migration that passes in staging can lock a busy production table for minutes. The difference is not the migration. It is the assumptions behind it.
postgres · database · architecture · software engineering