What metrics did you use to assess the system's state during monitoring?

The following metrics are typically used to assess the system's condition during monitoring:

• CPU usage — shows how loaded the processor is, helps identify overloads.
• Memory usage (RAM) — allows tracking whether there is enough RAM and if there are leaks.
• Disk usage (Disk I/O, free space) — important for performance assessment and preventing overflow.
• Network traffic (Network throughput, errors) — helps monitor network delays and packet loss.
• Application response time (Latency) — a key indicator of user experience.
• Error and warning logs — for identifying failures and issues.

In Python, monitoring can be performed using libraries such as psutil:

import psutil

cpu_percent = psutil.cpu_percent(interval=1)
memory = psutil.virtual_memory()
disk = psutil.disk_usage('/')

print(f"CPU: {cpu_percent}%")
print(f"Memory: {memory.percent}% used")
print(f"Disk: {disk.percent}% used")

These metrics help detect problems promptly and ensure system stability.