What is AWS CodeGuru and where does it fit in a DevSecOps pipeline?
Quick Answer
AWS CodeGuru is used for AI-assisted code review and profiling, running at the code stage. Explain the class of problem it catches, why catching it there is cheaper than catching it in production, and how it reports findings back to developers.
Detailed Answer
Describe AWS CodeGuru by the failure it prevents, not by its feature list. It belongs to AI-assisted code review and profiling and runs at the code stage of delivery, which matters because the cost of fixing a defect rises sharply the later it is found — the core argument behind shifting security left.
Strong answers cover Reviewer for pull-request comments and security detectors vs Profiler for runtime CPU/heap hotspots, repository association, how it compares with dedicated SAST, and the migration toward Amazon Q Developer reviews. Interviewers also listen for the operational side: who owns the rules, how findings reach the developer who introduced them, how false positives get suppressed without silently disabling coverage, and what the break-glass path is when a fix genuinely cannot ship in time.
Tie it to the wider toolchain. Security scanning is only useful when its output is actionable, deduplicated across tools, and attached to a specific commit, image digest or resource — otherwise teams learn to ignore it.
Code Example
# Where AWS CodeGuru sits in the pipeline # stage: code # 1. run the scan against the artifact produced by this stage # 2. compare findings against the agreed severity threshold # 3. a pull-request review comment blocking merge on a detected security issue # 4. publish the report so developers see it on the commit or pull request
Interview Tip
Anchor AWS CodeGuru to a stage and a gate: what it scans, when it runs, and what makes the build stop.