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CodeGuru

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Optimize application performance and reduce operational costs with ML-powered code analysis.

Free plan available
Freemium Security Developer Tools Code Review
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Reviews on SourceForge G2
68 reviews tracked

The Bottom Line

Price
Free plan available. Compare plans

Key facts

  • Uses machine learning to identify and fix code quality issues and security vulnerabilities.
  • Continuously monitors applications in production to optimize performance and reduce operational costs.
  • Provides actionable recommendations for improving code efficiency and security in Java and Python.

Pros

  • Automates code reviews and profiling, saving developer time.
  • Leverages machine learning for intelligent and actionable recommendations.
  • Helps reduce operational costs by optimizing inefficient code.
  • Enhances application security by detecting vulnerabilities and secrets.
  • Provides continuous monitoring for proactive performance management.

Cons

  • Primarily supports Java and Python, limiting use for other languages.
  • Pricing can become complex with multiple repositories and large codebases.
  • Requires integration with AWS ecosystem.

What is CodeGuru?

Amazon CodeGuru is a developer tool that leverages machine learning to improve code quality and identify performance bottlenecks in applications. It consists of two main components: CodeGuru Reviewer and CodeGuru Profiler. CodeGuru Reviewer automatically analyzes Java and Python code for common issues such as security vulnerabilities (including OWASP Top 10), resource leaks, concurrency problems, and deviations from AWS best practices. It integrates with popular code repositories like GitHub, Bitbucket, and AWS CodeCommit, providing recommendations directly within pull requests or through full repository scans. This helps development teams maintain high coding standards and enhance security. CodeGuru Profiler continuously monitors applications in production to identify the most expensive lines of code that consume excessive CPU and memory. It provides ML-based insights and recommendations to optimize application performance, reduce latency, and improve throughput. By visualizing application heap and using flame graphs, developers can pinpoint resource-intensive code paths, troubleshoot performance issues, and ultimately reduce operational costs.

Available on: Web

Data compiled by Toolradar How we evaluate
Source aws.amazon.com

Ratings Across the Web

4.4 (68 reviews)

CodeGuru holds an aggregate rating of 4.4 out of 5 from 68 reviews across SourceForge and G2, last checked September 25, 2026.

SourceForge 67 reviews
4.3/5
G2 1 reviews
5/5

Ratings aggregated from independent review platforms. Learn more

Key Features

  • ML-based code quality recommendations
  • Security vulnerability detection (OWASP Top 10, AWS API security)
  • Secrets detection in code repositories
  • Continuous application profiling in production
  • Identification of most expensive lines of code
  • CPU and memory usage optimization
  • Latency and throughput improvement
  • Application heap visualization

Pricing

Freemium

CodeGuru offers a generous free tier with optional paid upgrades for advanced features.

View pricing

CodeGuru by the numbers

CodeGuru compared with 84 Code Review tools on Toolradar, as of Oct 2026
Metric CodeGuru Peer median Position (1 is best)
Free plan Yes 90% have one n/a
User rating 4.4/5 (across the web, 68 ratings) 4.4/5 #10 of 22 (joint) tools with 20+ reviews

Each position is counted among the tools that have data for that row, as noted under it. All Code Review data · How we compute this. Advertising and placement fees are not inputs to any position.

Cite this: Toolradar, “CodeGuru by the numbers”, Oct 2026.

Reviews

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4.4/5

Across 68 verified user reviews on SourceForge, G2

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Still deciding?

Most buyers shortlist 2 or 3 tools before committing. Pull a side-by-side comparison or browse the full alternatives shortlist below.

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CodeGuru FAQ

How does CodeGuru assist in maintaining secure coding practices?

CodeGuru Reviewer automatically analyzes Java and Python code to identify security vulnerabilities, including those listed in the OWASP Top 10. It provides recommendations directly within pull requests, helping development teams enhance application security and maintain high coding standards.

Which teams benefit most from using CodeGuru?

Development teams working with Java and Python applications can significantly benefit from CodeGuru. It helps them automate code reviews, identify performance bottlenecks, and enhance application security, leading to improved code quality and reduced operational costs.

What kind of performance insights does CodeGuru Profiler offer?

CodeGuru Profiler continuously monitors live applications to pinpoint the most resource-intensive lines of code that consume excessive CPU and memory. It provides ML-based insights and recommendations to optimize performance, reduce latency, and improve throughput, often visualized through flame graphs.

How does CodeGuru compare to SonarQube for code analysis?

CodeGuru leverages machine learning for intelligent recommendations and integrates with the AWS ecosystem for continuous monitoring and profiling of live applications. SonarQube also offers static code analysis but may differ in its ML-driven insights and specific integration points for production profiling.

What are the primary language limitations of CodeGuru?

CodeGuru primarily supports Java and Python for its code analysis and profiling capabilities. This focus means that teams working with other programming languages will find its utility limited for their specific projects.

How is CodeGuru priced?

CodeGuru is available on a free tier, allowing users to get started without immediate cost. For more extensive usage and additional features, paid plans are available, with pricing that can become more complex for multiple repositories or large codebases.

Can CodeGuru integrate with existing development workflows?

Yes, CodeGuru Reviewer integrates with popular code repositories such as GitHub, Bitbucket, and AWS CodeCommit. This allows it to provide recommendations directly within pull requests or through full repository scans, fitting into established development workflows.

Source: aws.amazon.com

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