Tiny explainers grouped by topic. Spend less time Googling, more time building.
A production-focused guide to right-sizing pools, setting timeouts that prevent stalls, and fixing Postgres/MySQL “too many clients/connections” errors with app and proxy patterns.
How to profile CPU and memory in live Node, Python, and Go systems without guessing, plus how to read the flamegraphs you get back.
Trade-offs, pitfalls, and production-ready code with SQL, Node, FastAPI, MongoDB and Elasticsearch examples.
Fixed/sliding windows, token & leaky buckets, GCRA, and real-world implementations (Redis, NGINX, Envoy). Covers headers, bursts, backoff, multi‑DC, and tuning.
Freshness, validators, and directives: Cache-Control, ETag/Last-Modified, Vary, s-maxage, stale-while-revalidate, immutable. Patterns for APIs, HTML, and assets—plus CDN tips.
The event loop is where fast UIs quietly get won or lost: tasks, microtasks, rendering, and the patterns that keep 60fps intact.
Multi-stage builds, cache-friendly layering, non-root users, and sane defaults for ENTRYPOINT/CMD, healthchecks, and secrets. Copy‑paste patterns for Node, Python, and Go.
Indexes make some queries disappear and others slower. This walks through the patterns that matter and the traps that quietly hurt writes.
From DNS lookup to TLS to paint: the shortest useful tour of what the browser actually does after you hit Enter.
A fundamental database performance problem: why N+1 happens, how to spot it, and fixes with eager loading/batching in popular ORMs (Django, Rails, Prisma/Sequelize, SQLAlchemy).
Concurrency is about dealing with lots of things at once; parallelism is about doing lots of things at once. Here’s the mental model, practical examples, and when to use each.
A fast primer on in-memory, distributed, and CDN caching—what they are, when to use each, and how they boost latency, throughput, and cost efficiency.