CodeGuru by Amazon - Detailed Review
Coding Tools
CodeGuru by Amazon - Product Overview
Amazon CodeGuru Overview
Amazon CodeGuru is a developer tool by Amazon Web Services (AWS) that leverages machine learning to improve code quality and optimize application performance. Here’s a brief overview of its primary function, target audience, and key features.
Primary Function
CodeGuru is designed to automate code reviews and application performance profiling. It helps developers identify and fix code issues, detect security vulnerabilities, and optimize the performance of their applications, ultimately reducing costs and improving overall software quality.
Target Audience
The primary target audience for CodeGuru includes software developers, DevOps engineers, and organizations involved in software development. It is particularly useful for teams looking to streamline their code review processes, enhance application performance, and ensure security across the development lifecycle.
Key Features
CodeGuru Reviewer
This component performs code analysis by examining the source code, application dependencies, and code repositories. It uses machine learning models trained on vast amounts of code to identify potential problems, defects, security vulnerabilities, and adherence to best practices.
CodeGuru Profiler
This component helps developers find an application’s most expensive lines of code by analyzing the runtime behavior of the application. It provides visualizations, such as interactive flame graphs, and recommendations to improve performance and reduce compute costs.
Security Features
CodeGuru Security is a static application security testing (SAST) tool that combines machine learning and automated reasoning to detect vulnerabilities at any stage of the development lifecycle. It reduces false positives and automatically tracks bug closure, ensuring up-to-date information on the organization’s security posture.
Integration and Scalability
CodeGuru can be easily integrated into the development workflow, including continuous integration and delivery (CI/CD) tooling. It does not require provisioning virtual machines and scales with the workload, making it easy to use and affordable.
By using Amazon CodeGuru, developers can speed up their work, reduce defects, and improve the functionality and performance of their applications, all while lowering cloud expenditures.
CodeGuru by Amazon - User Interface and Experience
User Interface of Amazon CodeGuru
The user interface of Amazon CodeGuru is designed to be intuitive and user-friendly, making it accessible for developers to improve code quality and application performance.Accessing CodeGuru
To start using CodeGuru, users log in to the AWS Console using their authorized credentials. Once logged in, they can search for “Amazon CodeGuru” in the search field to access the tool.CodeGuru Reviewer
The CodeGuru Reviewer component of the tool provides a straightforward interface for code reviews. Here, users can view code analysis and recommendations directly within the AWS Console. For example, when a code review is selected, CodeGuru displays the recommendations, and clicking on a recommendation takes the user to the specific line of code in their repository (such as GitHub) that needs attention. The interface also includes a pull request dashboard that lists the status of code reviews, the number of lines of code analyzed, and the number of recommendations provided.Providing Feedback
Users can provide feedback on the recommendations by using thumbs-up or thumbs-down icons, which helps improve the accuracy of future recommendations through machine learning model-tuning efforts. This feedback mechanism is accessible both in the console and directly within the repository source provider or via the CLI.CodeGuru Profiler
The CodeGuru Profiler interface focuses on application performance optimization. It allows users to configure and view profiling data for their applications. The profiler runs continuously with minimal CPU impact and provides visualizations and recommendations on how to improve code efficiency. Users can view detailed profiles that highlight areas of code causing bottlenecks, along with time-series graphs of detected anomalies. This information is presented in a clear and actionable format, making it easier for developers to identify and fix performance issues.Ease of Use
Setting up and using CodeGuru is relatively straightforward. The process involves configuring IAM permissions, installing or upgrading the AWS CLI, and creating a repository for the source code. Amazon provides complete documentation and step-by-step guides to help users through these setup steps. Once configured, CodeGuru integrates seamlessly into the normal development process, allowing developers to commit code as usual and receive automated reviews and profiling data without significant additional effort.Overall User Experience
The overall user experience with CodeGuru is streamlined and efficient. The tool is integrated well within the AWS ecosystem, making it easy for AWS users to adopt. The use of machine learning to provide intelligent recommendations and the ability to provide feedback on these recommendations enhance the tool’s effectiveness over time. Visualizations and clear recommendations help developers quickly identify and address code quality and performance issues, improving the overall quality and efficiency of their applications. CodeGuru by Amazon - Key Features and Functionality
Amazon CodeGuru Overview
Amazon CodeGuru is a suite of AI-driven developer tools offered by Amazon Web Services (AWS) that aims to improve code quality, performance, and security. Here are the main features and how they work:
CodeGuru Reviewer
Automated Code Reviews
CodeGuru Reviewer uses machine learning to analyze code repositories and provide intelligent recommendations. It scans for critical issues, identifies bugs, and suggests how to remediate them, thereby improving code quality and reducing the likelihood of introducing vulnerabilities.
Best Practices and Error Detection
This feature identifies code inefficiencies, common programming errors, and deviations from best practices, helping developers adhere to coding standards and improve overall code health.
CodeGuru Profiler
Performance Profiling
CodeGuru Profiler collects runtime performance data from live applications to help developers identify and optimize critical areas of their codebase. It analyzes application runtime behavior, focusing on latency bottlenecks, CPU utilization, and resource leaks.
Visualizations and Recommendations
The profiler provides various visualizations, such as interactive flame graphs, to help developers visualize the performance of their applications. It suggests ways to improve efficiency, reduce CPU utilization, and lower infrastructure costs.
Anomaly Detection
Using machine learning, CodeGuru Profiler continuously scans profiled data and compares it against performance engineering best practices. It proactively alerts developers to performance issues and anomalies in the application profile, highlighting the specific lines of code causing these issues.
Supported Languages
Currently, CodeGuru Profiler supports applications written in Java virtual machine (JVM) languages and Python 3.6 or later.
CodeGuru Security
Security Vulnerability Detection
CodeGuru Security is a machine learning and program analysis-based tool that identifies security vulnerabilities in application code. It also scans for hardcoded credentials, helping to secure the application.
Integration with Development Workflows
This feature integrates seamlessly with developers’ existing workflows, providing automated code recommendations directly within their preferred development environments.
Integration and Cost Model
Ease of Use
CodeGuru can be enabled with a few clicks in the AWS console, making it easy to integrate into existing development processes.
Pay-as-you-go Pricing
AWS CodeGuru operates on a pay-as-you-go pricing model, where customers only pay for the actual use of the service. This makes it a cost-effective solution for both small startups and large enterprises.
Continuous Improvement
Machine Learning Enhancements
As CodeGuru analyzes more code and learns from patterns across repositories, its machine learning models continuously improve. This results in more accurate issue detection and increasingly relevant recommendations over time.
By leveraging AI and machine learning, Amazon CodeGuru helps developers improve code quality, optimize performance, and enhance security, all while reducing operational costs and improving the overall efficiency of the development process.
CodeGuru by Amazon - Performance and Accuracy
Amazon CodeGuru
A developer tool offered by Amazon Web Services (AWS), is renowned for its ability to enhance code quality and optimize application performance, leveraging advanced machine learning and automated reasoning.
Performance
CodeGuru boasts impressive performance capabilities through its two primary components: CodeGuru Reviewer and CodeGuru Profiler.
CodeGuru Reviewer
This component automates code reviews by scanning code repositories for issues related to performance, security, and best practices. It identifies hard-to-find bugs and critical issues with high accuracy and provides intelligent suggestions for remediation, including example code and links to relevant documentation. This automation significantly reduces the workload on human reviewers and ensures consistent code quality without introducing bottlenecks in the development process.
CodeGuru Profiler
This tool analyzes the runtime behavior of applications to identify performance bottlenecks. It helps developers understand the most expensive lines of code in terms of CPU usage and latency, enabling them to optimize code and reduce operational costs. For instance, Amazon’s internal teams have used CodeGuru Profiler to achieve significant savings, with some applications realizing a 325% efficiency increase in CPU utilization and a 39% reduction in costs.
Accuracy
The accuracy of CodeGuru is a key aspect of its effectiveness. Here are some points highlighting its accuracy:
Machine Learning Models
CodeGuru is powered by machine learning models trained on extensive data from Amazon’s own coding practices. This training enables the tool to identify critical issues and provide accurate recommendations for improvement.
High Accuracy in Bug Detection
CodeGuru Reviewer is capable of identifying bugs and critical issues that might be missed during manual code reviews. It flags common issues that deviate from best practices, ensuring that the codebase remains secure and performant.
Detailed Performance Insights
CodeGuru Profiler provides detailed reports and insights on application performance, helping developers pinpoint and address performance bottlenecks accurately. This includes identifying the most resource-intensive lines of code and anomalous behaviors affecting latency and CPU usage.
Limitations or Areas for Improvement
While CodeGuru is highly effective, there are some limitations and areas where it could be improved:
Integration and Compatibility
Although CodeGuru integrates well with various development tools and environments, such as AWS CodeCommit, GitHub, and popular IDEs, there might be specific use cases or environments where integration could be more seamless or extensive.
Cost and Usage
While CodeGuru is pay-as-you-go, which makes it affordable, the cost can still be a consideration for smaller projects or organizations with limited budgets. However, the potential savings from optimized code and reduced operational costs often justify the expense.
Learning Curve
While the tool is generally easy to use, there may be a learning curve for developers who are new to machine learning-driven code analysis tools. However, the tool’s integration into existing development pipelines and the availability of tutorials and documentation help mitigate this issue.
Conclusion
In summary, Amazon CodeGuru demonstrates strong performance and accuracy in improving code quality and optimizing application performance. Its machine learning-driven approach ensures high accuracy in bug detection and performance analysis, making it a valuable tool for developers. However, as with any tool, there are areas where integration, cost, and user adoption could be further refined.
CodeGuru by Amazon - Pricing and Plans
Amazon CodeGuru
A suite of AI-driven coding tools, Amazon CodeGuru offers several services with distinct pricing structures. Here’s a breakdown of the pricing and plans for each service:
Amazon CodeGuru Reviewer
Free Tier:
- You can start using CodeGuru Reviewer at no cost for 90 days, covering up to 100,000 lines of code in onboarded repositories per AWS account.
Standard Pricing:
- After the 90-day free tier expires or if your repository size exceeds 100,000 lines of code, you will be charged based on the repository size.
- For the first 100,000 lines of code: $10 per month.
- For each additional 100,000 lines of code: $30 per month.
- You are charged for the largest code branch if your repository has multiple branches.
- Non-code lines (e.g., comments, empty lines) are not counted.
Features Included:
- Incremental code review analysis (e.g., pull, push, or merge requests).
- Up to two full repository scans per month for each onboarded repository. Additional full repository scans are charged at $10 per 100,000 lines of code.
- All security features available in CodeGuru Reviewer are included in both incremental and full repository scans.
Amazon CodeGuru Profiler
Free Tier:
- There is a 90-day free tier for CodeGuru Profiler, allowing you to get started at no cost.
Standard Pricing:
- After the free tier expires, you are charged $0.005 per sampling hour.
- The first 36,000 sampling hours per profiling group per month are charged at this rate. There is no additional charge beyond 36,000 sampling hours per profiling group per month.
Features Included:
- Profiling of applications to visualize performance from a centralized dashboard.
- Troubleshooting of application latency and CPU utilization issues.
- Identification of areas to reduce infrastructure costs for applications.
Amazon CodeGuru Security
Public Preview:
- Currently, CodeGuru Security is available for free in public preview. There is no additional cost during this period.
AWS BugBust
Free Tier:
- AWS BugBust offers a 30-day free tier per AWS account. During this period, all costs incurred by the underlying usage of CodeGuru Reviewer and CodeGuru Profiler are free of charge. You can create multiple BugBust events within this 30-day period.
Standard Pricing:
- After the 30-day free tier expires, charges are calculated based on the individual service pricing models of CodeGuru Reviewer and CodeGuru Profiler.
- For example, if you have a repository with 200,000 lines of code and 10 profiling groups, you would be charged according to the CodeGuru Reviewer and Profiler pricing tiers.
In summary, Amazon CodeGuru provides flexible pricing plans with free tiers to help you get started, and the costs are based on the specific services and the size of your code repositories or the number of sampling hours for profiling. This structure allows you to manage your costs effectively while leveraging the AI-driven features of CodeGuru.
CodeGuru by Amazon - Integration and Compatibility
Amazon CodeGuru Overview
Amazon CodeGuru, an AI-powered developer tool offered by Amazon Web Services (AWS), integrates seamlessly with a variety of development tools, platforms, and services to enhance code quality, performance, and security.
Integration with Development Environments and Tools
CodeGuru integrates with popular integrated development environments (IDEs) such as AWS Cloud9, IntelliJ IDEA, and Visual Studio Code. This integration allows developers to access CodeGuru’s features directly within their familiar development environments.
Version Control Systems and Git Hosting Services
CodeGuru Reviewer supports integration with several Git hosting services, including AWS CodeCommit, Bitbucket, GitHub, and even Amazon S3. However, it does not currently support GitLab, whether cloud or on-premise.
Continuous Integration and Continuous Deployment (CI/CD) Pipelines
CodeGuru can be integrated into CI/CD pipelines using tools like GitHub Actions, AWS CodeBuild, AWS CodeDeploy, and AWS CodePipeline. This integration enables automated code analysis and review as part of the development workflow, serving as a quality gate to identify and address issues early in the development process.
Security and Performance Tools
In addition to its core functionalities, CodeGuru Reviewer can integrate with other AWS services such as Amazon Inspector for enhanced security checks. It also works in conjunction with CodeGuru Profiler, which analyzes application runtime behavior to identify performance bottlenecks.
Language Support
CodeGuru Reviewer supports several programming languages, including Java, Python, and JavaScript. While the exact versions are not explicitly stated in the documentation, it is generally compatible with recent versions of these languages (e.g., Java 8, Python 3.8, JavaScript ECMAScript 2021).
Accessibility of Results
The results and recommendations from CodeGuru Reviewer can be accessed in various ways, including the CodeGuru AWS console, as comments in pull requests, and within the GitHub Security tab when integrated via CI/CD pipelines.
Conclusion
Overall, Amazon CodeGuru’s integration capabilities make it a versatile tool that can be easily incorporated into existing development workflows, enhancing the quality, performance, and security of applications across different platforms and tools.
CodeGuru by Amazon - Customer Support and Resources
Amazon CodeGuru Overview
Amazon CodeGuru, an AI-driven coding tool, offers a comprehensive set of customer support options and additional resources to help users effectively utilize its features.
Documentation and Guides
CodeGuru provides extensive documentation, including user guides for both Amazon CodeGuru Reviewer and Amazon CodeGuru Profiler. These guides offer step-by-step instructions on getting started, integrating the tools into continuous integration (CI) pipelines, and using various features such as graphs, filters, and recommendations.
Video Resources
There are several overview videos available that demonstrate how to use CodeGuru. These videos cover topics such as improving code quality with CodeGuru Reviewer, optimizing application performance with CodeGuru Profiler, and integrating CodeGuru into GitHub CI pipelines. Additionally, videos show how to analyze application performance, visualize profiling data, and receive automated recommendations for resolving inefficiencies.
Detector Library
The Amazon CodeGuru Reviewer Detector Library provides detailed information about security and code quality detectors. This includes descriptions of detectors, non-compliant and compliant code snippets, and severity levels. This resource helps users understand the types of issues CodeGuru can detect and how to address them.
Tutorials and Getting Started
CodeGuru offers tutorials and a straightforward process for getting started. Users can access the AWS Free Tier and begin building with CodeGuru directly from the AWS Management Console. The pricing pages for both CodeGuru Reviewer and Profiler are also available for those looking to understand the cost structure.
Integrations
CodeGuru supports integrations with various tools and platforms, including continuous integration and delivery (CI/CD) tools, repository scanning, and integrated development environments (IDEs). For example, CodeGuru Security is integrated with Amazon Inspector code scanning for Lambda, and additional integrations with repositories and CI/CD tools are planned.
FAQs
The Amazon CodeGuru FAQs section addresses common questions about the service, including how to get started, supported programming languages, and the types of issues detected by CodeGuru Security and Profiler. This section also provides information on the availability of CodeGuru in different AWS Regions.
Continuous Feedback
CodeGuru is designed to work within development pipelines, providing continuous feedback to developers. This helps in improving code quality and performance over time. Users can receive recommendations for code fixes and provide feedback to enhance the effectiveness of future code analyses.
Conclusion
By leveraging these resources, users can effectively use Amazon CodeGuru to improve their code quality, detect security vulnerabilities, and optimize application performance.
CodeGuru by Amazon - Pros and Cons
Advantages of Amazon CodeGuru
Amazon CodeGuru offers several significant advantages that can enhance the software development process:Automated Code Reviews
CodeGuru Reviewer automates the code review process, significantly reducing the time required for manual inspections. This tool scans pull requests in supported repositories like GitHub, AWS CodeCommit, and Bitbucket, and provides recommendations to identify complex issues such as thread safety, memory leaks, and unnecessary resource usage.Improved Code Quality
By leveraging machine learning trained on extensive Amazon data and coding practices, CodeGuru Reviewer helps maintain high code quality standards. It detects issues like inefficient algorithms, incorrect thread usage, and security vulnerabilities before they reach production, ensuring the final product is reliable and secure.Performance Optimization
CodeGuru Profiler collects runtime performance data from live applications and uses machine learning to identify performance bottlenecks. It provides visualizations and actionable recommendations to reduce CPU usage, cut down latency, and improve overall application performance. This tool supports various AWS services, including Amazon ECS, EC2, EKS, Lambda, and Fargate, as well as on-premises applications.Security Enhancements
CodeGuru Reviewer detects security vulnerabilities such as hard-coded credentials, incorrect handling of user input, and insecure data storage practices. It provides recommendations to mitigate these risks, ensuring that the code is secure before it goes into production.Scalability and Cost-Effectiveness
CodeGuru is scalable and suitable for projects of any size, from small startups to large enterprises. Its pay-as-you-go pricing model makes it accessible and cost-effective, allowing teams to budget and operationalize it easily based on their project needs.Integration with Existing Workflows
CodeGuru can be seamlessly integrated into existing development workflows, making it easy to adopt without disrupting current processes. This integration helps in streamlining the development cycle and improving overall efficiency.Disadvantages of Amazon CodeGuru
While Amazon CodeGuru offers numerous benefits, there are some potential drawbacks to consider:Learning Curve
For developers who are not familiar with automated code review tools or machine learning-driven recommendations, there may be a learning curve. Understanding and acting on the recommendations provided by CodeGuru can require some time and effort, especially for less experienced developers.Dependency on AWS Services
To fully leverage the capabilities of CodeGuru, especially the Profiler component, there is a dependency on AWS services. This might not be ideal for projects that are not already using AWS infrastructure.Initial Setup
Setting up CodeGuru requires linking your code to a supported repository and configuring the tool, which can be a bit time-consuming initially. However, this setup is generally straightforward and well-documented.Potential Overreliance on Automation
There is a risk of overrelying on automated tools like CodeGuru, which could lead to a lack of manual code review skills among developers. It’s important to strike a balance between automated and manual reviews to ensure comprehensive code quality. In summary, Amazon CodeGuru is a powerful tool that significantly enhances code quality, performance, and security through automated reviews and machine learning-driven recommendations. While it offers many advantages, it also requires some initial setup, may have a learning curve, and could lead to an overreliance on automation. CodeGuru by Amazon - Comparison with Competitors
Amazon CodeGuru
Amazon CodeGuru is a comprehensive tool that leverages machine learning to enhance code quality and performance. Here are its key features:
- CodeGuru Reviewer: This component conducts automated code reviews, detecting issues such as security vulnerabilities, performance problems, and hard-to-find errors. It provides inline recommendations to improve code quality.
- CodeGuru Profiler: This tool profiles and diagnoses application performance in production, identifying resource-intensive methods and suggesting optimizations. It operates continuously with minimal impact on application performance and provides insights such as heap summaries to show memory consumption.
- Security Features: CodeGuru Security uses machine learning to detect security vulnerabilities like injection flaws, data leaks, and weak cryptography, and provides detailed findings and remediation steps.
Alternatives and Comparisons
GitHub Copilot
GitHub Copilot is another prominent AI coding assistant that integrates well with the GitHub ecosystem and popular IDEs like Visual Studio Code and JetBrains.
- Key Features: Copilot offers advanced code autocompletion, context-aware suggestions, automated code documentation, and built-in test case generation. It also provides AI-driven code review suggestions and collaborative development support.
- Difference: Unlike CodeGuru, Copilot focuses more on real-time coding assistance and automation during the development phase rather than post-deployment performance profiling.
Graphite
Graphite is an AI-powered tool that streamlines Git commands and enhances the code review process.
- Key Features: Graphite provides immediate feedback and actionable suggestions on pull requests, helps eliminate merge conflicts, and offers real-time developer metrics. It also allows for visually editing and creating stacked pull requests.
- Difference: Graphite is more focused on the Git workflow and code review process, whereas CodeGuru covers a broader spectrum including performance profiling and security vulnerability detection.
Forge
Forge is a code review assistant currently in beta, integrated with GitHub.
- Key Features: Forge uses AI to explain subtle changes in code, generate suggestions, and ensure code quality based on organization-specific guidelines. It also enhances the review flow with features like AI-generated ASCII artwork.
- Difference: Forge is more specialized in the code review process and does not offer the performance profiling or security features that CodeGuru provides.
DeepCode
DeepCode is a cloud-based AI code analysis tool that automatically scans codebases for potential bugs and vulnerabilities.
- Key Features: DeepCode supports multiple languages and is known for its accurate bug detection. It identifies potential issues in the codebase, similar to CodeGuru Reviewer, but does not include performance profiling.
- Difference: DeepCode lacks the performance optimization and continuous profiling capabilities of CodeGuru Profiler.
Unique Features of Amazon CodeGuru
- Comprehensive Coverage: CodeGuru combines code reviews, performance profiling, and security vulnerability detection, making it a more holistic tool compared to its competitors.
- Continuous Profiling: The ability of CodeGuru Profiler to operate in production indefinitely with minimal impact on application performance is a unique feature that sets it apart from tools that focus solely on development-phase assistance.
- Machine Learning-Powered Recommendations: CodeGuru’s use of machine learning to provide actionable recommendations for performance and security improvements is a significant advantage.
In summary, while tools like GitHub Copilot, Graphite, Forge, and DeepCode offer valuable AI-driven coding assistance, Amazon CodeGuru stands out for its broad range of features that cover code quality, performance optimization, and security, making it a versatile choice for developers and organizations seeking a comprehensive solution.
CodeGuru by Amazon - Frequently Asked Questions
Frequently Asked Questions about Amazon CodeGuru
What is Amazon CodeGuru?
Amazon CodeGuru is a developer tool from AWS that consists of two main components: Amazon CodeGuru Security and Amazon CodeGuru Profiler. CodeGuru Security uses machine learning and program analysis to detect security vulnerabilities in application code, while CodeGuru Profiler optimizes performance for applications running in production and identifies the most expensive lines of code to reduce operational costs.What are the main features of Amazon CodeGuru Security?
CodeGuru Security offers several key features, including high precision vulnerability detection for issues like injection flaws, data leaks, weak cryptography, and missing encryption. It also provides automatic code fixes, vulnerability tracking, secrets detection, and integrations with various tools. Additionally, it includes a metrics dashboard to monitor security risks and how to remediate them.Which programming languages are supported by Amazon CodeGuru Security?
CodeGuru Security supports scanning code written in Java, Python, JavaScript, TypeScript, C#, CloudFormation, Terraform, Go, and Ruby.What type of issues are detected by Amazon CodeGuru Security?
CodeGuru Security detects issues such as OWASP Top Ten vulnerabilities, CWE Top 25 issues, log injection, secrets, and the secure use of AWS APIs and SDKs. It also scans for hardcoded credentials.How do I get started with Amazon CodeGuru?
To get started with Amazon CodeGuru, you can visit the CodeGuru console. You can integrate CodeGuru into your continuous integration and delivery (CI/CD) tools, repository scanning, and integrated development environments (IDEs).What is Amazon CodeGuru Profiler?
Amazon CodeGuru Profiler helps developers and IT operators understand the runtime behavior of their applications, improve performance, and decrease infrastructure costs. It analyzes application runtime profiles and provides intelligent recommendations and visualizations to guide performance improvements.What can I do with Amazon CodeGuru Profiler?
With CodeGuru Profiler, you can troubleshoot latency and CPU utilization issues, learn where to reduce infrastructure costs, identify application performance issues, and understand heap utilization over time. It provides various visualizations of profiling data to help in these tasks.Which programming languages are supported by Amazon CodeGuru Profiler?
CodeGuru Profiler currently supports applications written in all Java virtual machine (JVM) languages and Python 3.6 or later. It offers features such as CPU profiling, support for AWS Lambda, anomalies and recommendation reports, and more, with some features varying between Java and Python.How does Amazon CodeGuru Reviewer work?
Amazon CodeGuru Reviewer is an automated code review service that identifies critical defects and deviations from coding best practices for Java and Python code. It integrates with source control systems like GitHub, Bitbucket, and AWS CodeCommit, and provides recommendations based on standards learned from major open source projects and Amazon’s codebase.Is there a free tier available for Amazon CodeGuru?
Yes, Amazon CodeGuru is available at no cost for 90 days under the AWS Free Tier. During this period, you can review up to 100,000 lines of code with CodeGuru Reviewer.In which AWS Regions is Amazon CodeGuru available?
Amazon CodeGuru is available in all AWS Regions. For a detailed list of supported regions, you can visit the AWS Region Table for all AWS global infrastructure.