#Performance
— 7 posts
Caching Strategies Beyond 'Just Add Redis'
Cache-aside, write-through, write-behind, read-replicas, edge caches, HTTP ETags, and stale-while-revalidate — how to pick the right caching pattern and how to invalidate without tears.
Backpressure and Flow Control in Async Systems
When a producer outpaces its consumer — Node streams, Go channels, Rust async, RxJS, and Kafka consumer lag. The patterns that actually keep memory in check.
PostgreSQL Internals: MVCC, VACUUM, and HOT Updates
How Postgres actually stores rows — tuples, xmin/xmax, HOT updates, table bloat, and why VACUUM is the most misunderstood command in your database.
React Server Components: Practical Patterns for Production
Server Components change the mental model of React development. After building two production apps with RSC, here are the patterns that work, the pitfalls to avoid, and when client components are still the right call.
PostgreSQL Performance Tuning: Lessons from Production
After optimizing PostgreSQL for three high-traffic production systems, I've compiled the tuning strategies that actually moved the needle — from indexing patterns to connection pooling and query optimization.
Why Rust Changed How I Think About Backend Performance
After shipping a 50k RPS service in Rust, I returned to Node.js with a completely different mental model for performance. This is the story of memory models, threading, and why your async runtime is both better and worse than you think.
The Next.js Full-Stack Production Checklist
Launching a Next.js application to production is more than just running next build. After deploying six Next.js apps to production, here's the comprehensive checklist I wish I had from the start — covering performance, security, SEO, and operational readiness.