Core Code
Core Code Modern Dev Handbook
LINUX-PRODUCTION Contents
Linux Fundamentals for Production
Filesystem Layout (FHS) in Practice Users, Groups, and Service Accounts Permissions & ACLs (chmod/chown/setuid) Sudoers Safe Defaults Packages: apt/dnf, Repos, and Pinning Shell & Environment Hygiene Editing Configs Safely Time, Timezones, and NTP System Introspection Toolkit
Processes & Signals
Linux Process Model (PID, PPID, Fork/Exec) ps/top/htop: Finding What Hurts Signals in Practice (TERM/KILL/HUP) nice/renice and Scheduling Basics ulimits and Resource Limits Background Jobs (nohup, tmux, systemd-run) /proc and What It Tells You cgroups Basics (CPU/Memory Isolation) Zombies, Orphans, and Stuck Processes
systemd & Services
systemd Unit Types Overview Service Unit Best Practices Dependencies & Ordering (After/Wants/Requires) Restart Policies and Backoff Environment Files and Secrets Handling journald Basics (Reading, Filtering, Retention) Logging Practices with systemd Timers vs Cron Debugging systemd Services
Networking Basics for Production
ip, routes, and interfaces DNS Debugging (dig, resolvectl, hosts) Ports and Sockets with ss curl for HTTP Debugging TCP Basics (Handshake, States, Retries) Firewall Overview (nftables/iptables/ufw) NAT and Port Forwarding Concepts TLS and Certificates Basics Network Troubleshooting Playbook
Storage & Filesystems
Disk Layout and Partitioning (lsblk/fdisk) Filesystems (ext4/xfs) Basics Mounts and /etc/fstab Safety Disk Usage: df vs du (and Why They Differ) Inodes and “Disk Full” Mysteries Swap Strategy in Production Log Rotation (logrotate) Basics Temporary and Runtime Storage Hygiene Backup Storage Considerations
Security Basics
SSH Hardening in Production Users and Least Privilege in Production Firewall Minimum Rules for Production Linux Patching Strategy in Production Managing Secrets on Linux Hosts Linux Audit and Basic Logging in Production Fail2ban and Rate Limiting in Production SELinux and AppArmor Overview in Production Linux Security Baseline Checklist for Production
Observability on Linux
Linux Log Sources Map in Production journalctl Power Usage in Production Log Structure and Correlation in Production Metrics Hooks Overview in Production Health Checks and Readiness in Production Tracing Mindset for Linux and Production Systems Core Dumps Basics in Production Debug Packages and Symbols in Production Linux Observability Checklist for Production
Performance & Debugging
Load Average Explained for Production Debugging CPU Profiling Basics in Linux Production Memory Pressure Basics in Linux Production IO Bottlenecks and iostat in Production lsof and Open Files in Production Debugging Practical strace Usage in Production Sockets Debugging Tools in Linux Production dmesg and Kernel Signals for Production Debugging Production Debugging Workflow for Linux Systems
Deployment Patterns
Environment and Configuration Management in Production Release Directory Pattern for Safe Linux Deployments Zero-Downtime Restarts in Production Running Migrations Safely in Production Secrets Deploy Patterns in Production Backups and Restore Drills in Production Rollback Strategies for Production Deployments Maintenance Windows in Production Operations Production Deployment Checklist for Linux Systems
Production Checklists
Writing Effective Runbooks for Production Systems Failure Modes Mapping for Linux Production Systems Incident Response Basics for Linux Production Break-Glass Access in Production Capacity Planning Basics for Linux Production Systems Monitoring and Alerting Baseline for Linux Production Production Readiness Review for Linux Systems Configuration Drift in Linux Production Systems Go-Live Checklist

Linux Log Sources Map in Production

Understand where logs originate on a Linux system: auth, kernel, systemd, application, audit, and service logs. Build a mental map for faster incident triage and correlation.
On this page

Why You Need a Log Source Map

During incidents, time is lost not in debugging — but in searching where logs are. A production engineer must know which subsystem logs where. Observability starts with log source awareness.

Symptom

  • Service failure but no obvious error in expected log
  • Authentication issues with no clear trace
  • Kernel-level crash with only partial application logs
  • Security incident with missing timeline

Root Cause

  • No mental model of log layers
  • Assuming application logs contain everything
  • Ignoring kernel and systemd logs
  • No audit visibility

Primary Log Sources

1) Authentication Logs

Debian/Ubuntu:

/var/log/auth.log

RHEL-based:

/var/log/secure

2) Systemd Journal

journalctl

Per service:

journalctl -u nginx

3) Kernel Logs

dmesg
journalctl -k

4) Application Logs

Typically located under:

/var/log/
/var/www/app/logs/
/opt/app/logs/

5) Audit Logs

/var/log/audit/audit.log

6) Cron Logs

journalctl -u cron

Investigation Flow

  • Start with service log
  • Check systemd journal for service failures
  • Check auth logs for access anomalies
  • Check kernel logs for resource or driver errors
  • Correlate timestamps across sources

Log Time Correlation

timedatectl

Ensure system clock is synchronized (NTP active). Incorrect time breaks forensic reconstruction.

Hardening Strategy

  • Standardize log locations across fleet
  • Centralize logs (ELK, SIEM, cloud logging)
  • Define log retention policy
  • Ensure logs are not world-writable
  • Enable audit logging for sensitive changes

Why This Matters in Real Infrastructure

Incidents unfold across layers: application → systemd → kernel → network. Without a clear map of log sources, engineers waste critical response time. Observability begins with knowing where the truth is recorded.

journalctl Power Usage in Production →