What signals and metrics do you track to operate AWS CodeGuru well?
Quick Answer
For AWS CodeGuru, watch recommendations accepted vs dismissed on pull requests, and — for Profiler — CPU/latency hotspots and estimated cost of the most expensive methods. Trend them over time; a single scan is a snapshot, the trend tells you if you are getting more secure or just accumulating debt.
Detailed Answer
Operating a scanner is not "turn it on" — it needs the same observability as any production system. For AWS CodeGuru, the signals that matter are recommendations accepted vs dismissed on pull requests, and — for Profiler — CPU/latency hotspots and estimated cost of the most expensive methods.
Trend them. Rising Critical counts on a stable codebase usually means a base image or dependency has aged, not that developers got careless. A rising false-positive rate is an early warning that the gate is about to lose the team's trust. Scan duration matters because a slow gate is a gate people route around.
Feed these into a dashboard alongside remediation SLAs so security posture is visible to the people who own it, not buried in a tool nobody logs into.
Code Example
# Signals to track for AWS CodeGuru # recommendations accepted vs dismissed on pull requests, and — for Profiler — CPU/latency hotspots and estimated cost of the most expensive methods # rule: trend over time, don't react to a single scan # rule: watch false-positive rate as closely as finding count
Interview Tip
Name false-positive rate as a leading indicator — it shows you understand adoption, not just scanning.