When troubleshootingperformance and latency issueson BIG-IP, especially under peak load conditions, it is critical to identify whichVirtual Servers are consuming the most resources. This is a coredata plane analysis task.
BIG-IP provides multiple views of configuration and status, but only certain areas exposereal-time and historical traffic statisticsthat correlate directly with CPU usage and throughput.
Why Option C Is Correct:
Statistics > Module Statistics > Local Traffic > Virtual Serversprovides:
Real-time and cumulative statistics per Virtual Server
Metrics such as:
Bits in / Bits out
Packets in / Packets out
Current connections
Connection rate
Total requests
The ability toidentify high-traffic or high-connection Virtual Servers, which are the most likely contributors to elevated CPU utilization
These statistics allow the administrator toobjectively determine which Virtual Servers are the top consumers of system resourcesand therefore good candidates for migration to a dedicated BIG-IP device.
Why the Other Options Are Incorrect:
A. Local Traffic > Virtual Servers > Virtual Server List
Primarily aconfiguration view
Does not provide sufficient performance or utilization statistics to identify CPU-heavy Virtual Servers
B. System > Platform
Displayshardware-level informationsuch as CPU cores, memory, disk, and platform type
Does not break down utilization by Virtual Server
D. Local Traffic > Network Map
Provides alogical topology viewof Virtual Servers, pools, and pool members
Useful for understanding relationships, but not for identifying high-utilization Virtual Servers
Key Data Plane Concept Reinforced:
To diagnose performance problems and plan traffic redistribution, BIG-IP administrators must rely onModule and object-level statistics, not configuration screens. TheVirtual Server statistics viewis the authoritative location for identifyingtraffic hotspotsthat directly impact CPU and latency during peak events such as Black Friday.
===========
