Linux

Your AI app runs on a Linux server in production. You need the terminal to fix crashes, read logs, and restart services.

Linux is the backstage of a theater — users see the app on stage, engineers work behind the scenes.

Visual Workflows

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Overview

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Key Takeaways

1.Linux is the operating system behind most cloud servers and containers — you use its terminal to deploy, debug, and manage AI apps.
2.Key skills: navigate files (cd, ls), read logs (tail, grep), manage processes (ps, kill), and set permissions (chmod).

Real Example

Scenario

Your RAG API crashes in production and users see a 500 error.

What you would do

SSH into the server, run docker logs to find the ERROR, check disk space with df -h, and restart the service.

Practice Task

In your terminal: run pwd, ls, and cd into a project folder. Create a test.log file with a few lines, then grep a word in it. Run ps to list running processes.

Commands

Commands to Remember

ls -la # list files with permissions and hidden files
cd /path && pwd # navigate to a folder and show current path
tail -f app.log # follow live log output in real time
ps aux | grep name # find a running process by name
chmod 600 .env # restrict file access to owner only
df -h # check available disk space
grep -r "pattern" dir/ # search for text inside files

Cheat Sheet

Quick recap

quick ref

•Most cloud servers run Linux — access via SSH
•Navigate: ls, cd, pwd · Read logs: tail -f, grep
•Manage processes: ps, kill, systemctl
•chmod 600 .env — protect API keys on server
•df -h — check disk space (common crash cause)
•Never run production services as root

Common Mistakes

✕Running everything as root
✕Not checking disk space before large indexing jobs
✕Leaving API keys in shell history