Resource Monitoring for Data Pipelines

When running data pipelines—especially in production—resource monitoring is critical to prevent slowdowns, crashes, or system-wide failures. Simple Linux command-line tools like top , htop , df -h , and free -h provide real-time visibility into system health and help you catch issues before they escalate. 1. Monitoring CPU & Processes: top and htop top (Built-in, lightweight) The top command gives a live view of system processes and CPU usage. Shows: CPU utilization (user, system, idle time) Running processes and their CPU/memory consumption Why it matters for pipelines: Identify CPU bottlenecks during heavy transformations (e.g., Spark jobs, ETL scripts) Detect runaway processes consuming excessive CPU Spot when multiple pipelines overload the system Tip: Press P inside top to sort by CPU usage. htop (Enhanced, user-friendly) htop is an improved version of top with a more intuitive interface. Features: Color-coded CPU, memory, and swap usage Easy process management (kill, renice) Tree