PROJECT NOTES / BACKEND & SYSTEMS
AppPowerMonitor
Measure the resource footprint of one application.
A Python monitoring tool that isolates application CPU and memory usage and estimates power consumption through TDP-based modeling.
BACKEND & SYSTEMS↗
01Application process
02Sample resources
03Estimate power
04Log
The problem
System-wide utilization can hide which application is responsible for a resource spike or an energy-intensive workload.
How it comes together
Process-level samples are collected over time, logged, and visualized. A TDP-based estimate adds a directional view of power consumption.
03 / UNDER THE HOOD
SIMPLIFIED ARCHITECTUREFollow the flow.
01Application process
02Sample resources
03Estimate power
04Log
05Visualize
Application-specific CPU and memory monitoring.
Real-time performance logging.
TDP-based power estimation.
Graphs for inspecting usage patterns.
Why this approach?
Keep the estimation method explicit: modeled power is a useful comparison signal, while direct energy measurement would require additional instrumentation.
Explore the project’s supporting sources.Project repository
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