Automatically Improve Code Quality with Amazon CodeGuru - Using Reviewer and Profiler
ML-based Reviewer automatically detects resource leaks and concurrency issues, while Profiler visualizes CPU bottlenecks with flame graphs. Learn about CI/CD integration patterns.
Automated Code Review with CodeGuru Reviewer
CodeGuru Reviewer is a service that uses ML models to automatically detect code issues. It integrates with GitHub, CodeCommit, and Bitbucket repositories, automatically running code reviews when pull requests are created. Detection targets include resource leaks (unclosed streams, connections), concurrency issues (race conditions, deadlocks), inefficient AWS API usage (missing pagination, unnecessary API calls), and security vulnerabilities (hardcoded credentials, SQL injection). Detection results are posted directly as pull request comments, allowing developers to address them within the normal code review workflow.
Performance Analysis with CodeGuru Profiler
CodeGuru Profiler is a service that continuously analyzes application runtime performance. It supports Java and Python applications, and by embedding an agent, it visualizes methods with high CPU usage, latency bottlenecks, and memory allocation hotspots. Flame graphs provide an at-a-glance view of CPU consumption across the entire call stack, helping identify code paths that need optimization. Profiler overhead is kept below 1% CPU usage, making it suitable for continuous operation in production environments. It also supports Lambda functions, enabling identification of cold start bottlenecks and inefficient processing.
CI/CD Pipeline Integration
Reviewer automatically runs reviews on all pull requests simply by configuring repository integration. Full repository scans can also be executed to detect issues across the entire existing codebase at once. Profiler recommendations are presented along with estimated cost savings. For example, specific metrics such as "optimizing this method can reduce monthly computing costs by $XX" are provided, making it useful for prioritizing optimizations. Detection results from both Reviewer and Profiler can be sent to Security Hub, enabling security teams to centrally monitor code quality across the organization. For a systematic study of CodeGuru from basics to advanced topics, books (Amazon) are available.
CodeGuru Pricing
CodeGuru Reviewer uses monthly billing based on the number of analyzed code lines in the repository, starting at approximately $10.00 per month for the first 100,000 lines. There is no limit on the number of pull request reviews, making costs predictable even for development teams that frequently create pull requests. CodeGuru Profiler costs approximately $0.005/hour per sampling group, with costs varying based on the number of profiled applications. A 90-day free trial is available for both Reviewer and Profiler, allowing you to verify cost savings before production deployment.
Summary
CodeGuru is a service that provides ML-based automated code review (Reviewer) and runtime performance analysis (Profiler). It automatically detects resource leaks and concurrency issues that human reviews often miss, and continuously visualizes performance bottlenecks in production environments. By incorporating it into the development process, you can achieve continuous improvement of code quality and application performance.