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CodeGuru Overview

  • An ML-powered service for automated code reviews and application performance recommendations
  • Provides two functionalities
    • CodeGuru Reviewer: automated code reviews for static code analysis (development)
    • CodeGuru Profiler: visibility/recommendations about application performance during runtime (production)

CodeGuru Reviewer

  • Identify critical issues, security vulnerabilities, and hard-to-find bugs
  • Example: common coding best practices, resource leaks, security detection, input validation
  • Uses machine learning and automated reasoning
  • Hard-learned lessons accross millions of code reviews on 1000s of open-source and Amazon repositories
  • Supports Java and Python
  • Integrates with GitHub, BitBucke and AWS CodeCommit

CodeGuru Profiler

  • Helps understand the runtime behavior of your application
  • Example: identify if your application is consuming excessive CPU capacity on a logging routine
  • Features:
    • Identify and remove code inefficiencies
    • Improve application performance (e.g. reduce CPU utilization)
    • Decrese compute costs
    • Provides heap summary (identify which objects using up memory)
    • Anomaly Detection
  • Support applications running on AWS or on-premise
  • Minimal overhead on application