Practical engineering insights from the frontlines. Deep dives into data architecture, infrastructure economics, and system design.
Every AI coding session starts from zero. Architecture decisions, progress, and hard-won lessons disappear between conversations. The Agentic Context System fixes this with a structured file approach that gives AI persistent memory across sessions.
A complete hands-on guide to Kubernetes covering 18 essential concepts. Follow along step-by-step on your own computer. Every command works, every example runs.
Decomposition is a tool, not a goal. This guide examines why boundaries exist, what they cost, when they pay off, and how to think about system design from first principles rather than best-practice cargo culting.
How we built this blog using Astro, TypeScript, and open-source tools. A comprehensive look at our layout architecture, responsive design system, CSS tokens, and the engineering decisions behind every pixel.
What if you could see every line of code that runs your platform? A thought experiment about transparent infrastructure, built on the shoulders of giants. None of this exists yet, but maybe it should.
A deep dive into the streaming vs batch processing paradigm, exploring when to use each approach, the architectural trade-offs, and practical decision frameworks.
Streaming vs batch processing, modern data stacks, and architectural patterns.
Cost analysis, vendor comparisons, and build-vs-buy decisions.
Practical patterns, operational complexity, and real-world trade-offs.
I'm Boyan Balev, a software engineer focused on data infrastructure and distributed systems. This blog shares practical insights from building and operating data platforms at scale.
Every article comes from real experience in the trenches - no ivory tower architectures, just patterns that work in production.