Tutorials, stack comparisons, tool reviews, and productivity tips — code that ships.
Every VM-deployed Node.js service eventually crashes and stays down until someone notices. Systemd gives you automatic restart, structured logging, resource limits, and zero-downtime deploys using a supervisor that ships with every Linux distro. Here is the exact service file and deployment workflow your app needs.
Strings, lists, sets, sorted sets, hashes, hyperloglogs, bitmaps, and streams each solve a different class of problem. Here is the decision tree, the memory cost of each type, and the production patterns that separate the "I learned Redis in a tutorial" tier from the "I run it in production" tier.
HTTP/2 server push was a well-intentioned failure. 103 Early Hints is the replacement that actually improves real-world performance. Here is how to implement it in Node.js, how to measure the difference, and why most CDNs already support it.
Prisma is beloved for DX, but its generated client, cold start overhead, and proxy layer cause real pain at scale. Drizzle takes the opposite approach: you write SQL and TypeScript validates it at compile time. Here is the migration, schema design, query patterns, and production gotchas from shipping Drizzle in a real Node.js service.
The big rewrite always fails. The Strangler Fig pattern lets you replace a legacy monolith piece by piece, routing traffic between old and new services, until nothing is left of the original. Here is the proxy layer, the migration workflow, and the data sync patterns that make it work.
Your API is slow, but you cannot explain why. Your APM shows request time, but you need to break it into DNS resolution, TCP connect, TLS handshake, and downstream call durations. The diagnostics_channel module gives you this data with zero application code changes and zero overhead when nobody is listening.
Your Node.js validation library catches 90% of bad data. The remaining 10% quietly corrupts your database and breaks downstream consumers. Here is how to push business rules into PostgreSQL constraints so bad data never reaches disk.
Your Postgres CPU is at 60%, users are complaining about slow pages, and EXPLAIN ANALYZE on the query in psql shows a fast index scan. The real problem is the other 99% of your queries. Here is how to use pg_stat_statements, auto_explain, and planner cost tuning to find the actual bottlenecks and fix them systematically.
A migration breaks production at 3 AM. The rollback script does not exist, the data is half-transformed, and every minute of downtime costs thousands. Here is the three-step plan: writing rollbacks alongside forward migrations, testing them in CI, and automating the detection that triggers them before customers notice.
Your API reads an entire file into memory on every download request, crashes the server when users download multiple large files simultaneously, and cannot resume interrupted transfers. Here is how to build a Node.js download endpoint that streams, supports Range headers for pause/resume, and throttles bandwidth per connection.