Technical articles. No filler.
Keep uploads outside your code and web root, start on local SSD up to about 200 GB, then move to S3 compatible storage on a Saudi server. Serve private files through signed URLs that expire in minutes, and back them up separately.
Run FastAPI under Gunicorn with Uvicorn workers behind Nginx, start at two workers per vCPU, and keep secrets in a locked env file. On a 4 vCPU / 8 GB server, eight workers serve about 2,300 requests per second using just 1.2 GB of RAM.
Running Node.js with a bare node command means your app dies on the first crash or reboot. PM2 restarts it automatically, spreads it across every core in cluster mode, recycles it past a memory ceiling, rotates logs and starts with the server through systemd.
You can change a table with millions of rows in production without downtime by picking the right path: ALGORITHM=INSTANT for new columns in MySQL 8, gh-ost or pt-online-schema-change for heavy rebuilds, and the expand, migrate, contract pattern instead of one breaking change.
Without SSR, an Inertia app hands search engines a nearly empty page, while SSR delivers full content in the first response. Run the SSR server as a systemd service next to Laravel using 100 to 200 MB, then confirm rendering with curl.
A safe PHP 8.4 upgrade starts with PHPStan and Rector checks before you touch the server, then runs PHP-FPM 8.4 next to your current version and switches one site at a time, with a one-minute rollback that changes a single Nginx line.
Laravel Reverb is the official WebSocket server you run yourself instead of Pusher, with no per-message billing and event data kept in Saudi Arabia. Put it behind Nginx with TLS as a systemd service, and a 2 vCPU server holds thousands of connections.
If all you want is a simple key-value cache, Memcached is enough and lighter. But if you need lists, queues, pub/sub, persistence across restarts, and richer data structures, Redis is the answer, and it is what most applications choose today.
If your data is under a few million vectors and you already run PostgreSQL, the pgvector extension is enough and keeps everything in one database. At large scale or when you need high-speed search under heavy concurrency, dedicated engines like Qdrant and Milvus pull ahead.
