Practical engineering insights from the frontlines. Deep dives into data architecture, infrastructure economics, and system design.
StoryMost people learn data engineering as a vendor list. Here is the other way: a small set of forces, and the moves engineers make to relieve them. We start with one cron job copying one database, push until it breaks, and by the end we have designed a planetary clickstream platform together.
StoryAn agent loop has no memory of what it meant, so the architecture quietly decays. Vader moves the meaning outside the loop: a human writes a constitution of invariants, a compiler turns each into a check the agent cannot argue with, and a lock stops the agent from silencing it. Gate the model, free the code.
StoryMost people learn system design as a glossary. Here is the other way: a small set of forces, and the moves engineers make to relieve them. We start with one box, push until it breaks, and by the end we have designed YouTube together.
StoryA field guide to API design from first principles. REST, SOAP, gRPC, GraphQL, Webhooks, WebSockets, and WebRTC, and the questions that pick them for you.
StoryGraphQL hands you a question REST answers for you by default: where does each rule live? A working theory of GraphQL APIs that hold up at scale.
Why every transformer ever built carries a structural flaw from 2015, and how the Kimi team fixed it by recognizing a pattern the field already solved once.
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.