- ML-powered service for automated code reviews and application performance reccomendations
- Provides two functionalities:
- CodeGuru Reviewer: automated code reviews for static code analysys (development)
- CodeGuru Profiler: visibility/recommendations about application performance during runtime (production)
- 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 across millions of code reviews on 1000s of open-source and Amazon repositories
- Supports Java and Python
- Integrates with GitHub, BitBucket and AWS CodeCommit
- Help understand the runtime behaviour 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
- Supports applications running on AWS or on-premises
- Minimal overhead on application