Understanding the Application’s Footprint on Infrastructure with Code-Level Detail

The nature of an application defines its resource impact on infrastructure. An application that stores a lot of session data, will have big memory footprint. An application that processes data may have a larger CPU footprint.

Depending on the traffic or amount of data being processed, an application will be scaled out to multiple instances. That, in turn, scales its footprint.

Due to the time and space complexity of application code, the CPU and memory usage can get out of hand pretty quickly, requiring more and more instances. At that point, it is critical to know exactly how to prioritize optimization or troubleshooting efforts, whether for infrastructure cost reduction or response time improvement.

Analyzing the application footprint

It is therefore necessary to have continuous visibility into the total application footprint, including all of its instances, for every application.

When the StackImpact agent is used, information about the application CPU and memory footprint, as well as the execution hot spots, will be automatically available in the Dashboard.

First, the Footprint section lists all the applications and their total footprints over a selected time range.


Second, by selecting the application from the footprint chart’s breakdown, respective hot spot profiles will be opened, showing exactly where in the code the most resource consumption happens.


StackImpact is currently available for Go, Node.js and Python. See the respective GitHub repositories or the documentation for setup instructions.