AI Agents for Developers

Feb 04, 2025. 5 min

Streamlining Code Reviews with CloudaEye: A Developer's Experience

Introduction

As developers, we know how crucial code reviews are for maintaining code quality, catching bugs early, and ensuring best practices. However, the process can often be time-consuming and tedious. That’s where CloudaEye comes in—a powerful tool designed to automate and simplify code reviews. In this blog, I’ll walk you through my experience using CloudAEye, from signing up to leveraging its features to improve my codebase.

Getting Started with CloudAEye

1. Signing Up

I followed the Getting Started with Code Review guide to do this.

The first step was to sign up on the CloudAEye platform. The process was straightforward— I just needed to provide my email address and create a password. Alternatively, you can sign up using your Google account.

2. Choosing a Plan

CloudAEye offers both free and paid plans. Since I was just starting out, I opted for the free plan, which provides access to basic features like code review automation, PR descriptions, and the ability to ask questions about your code. The free plan is perfect for individual developers or small teams looking to streamline their workflow without breaking the bank. CloudAEye allows 3 developers in a team to use the free plan. So, it is great for early-stage startup teams.

Integrating CloudAEye with GitHub

3. Connecting GitHub

Once signed up, I connected my GitHub account to CloudAEye. This was a seamless process— I simply clicked on the “Connect GitHub” button, authorized the integration, and installed the CloudAEye app on my GitHub account. The app ensures that CloudAEye can access the repositories and branches you specify.

4. Creating an App

After connecting GitHub, I created an app within CloudAEye. This involved selecting the repository and branch I wanted to monitor. I chose the main repository for my project and the main branch, as that’s where most of my development happens.

Automating Code Reviews with CloudaEye

5. Generating Code Reviews for PRs

One of the standout features of CloudAEye is its ability to automate code reviews. For every pull request (PR), I simply added the following command in the comments.

Refer to this example PR: https://github.com/CloudAEye/sklearn-pandas/pull/6

@cloudaeye review-code

CloudAEye would then analyze the code, highlight potential issues, and provide actionable feedback. This saved me a ton of time, especially when reviewing large PRs.

The first comment was about a potential security vulnerability.

The review found a few other issues including a risk that would be hard for human reviewers to find.

6. Describing PRs

Another handy feature is the ability to generate a summary of the PR. By using the command:

@cloudaeye describe-pr

CloudAEye provided a concise description of the changes, making it easier for my team to understand the purpose and scope of the PR.

I love the gentle reminders under the “Additional Info” section about writing unit tests.

7. Adding Commit Messages

CloudaEye also helps with writing meaningful commit messages. By using:

@cloudaeye add-commit-message

It suggested clear and descriptive commit messages based on the changes in the PR. This is a small but impactful feature that ensures better documentation of the codebase.

8. Asking Questions About Your Code

One of my favorite features is the “Ask Question” functionality. If I had any doubts or needed clarification about a specific piece of code, I could simply tag CloudAEye and ask:

@cloudaeye question

I asked to suggest code that would handle the errors in NeumericalTransformer class.

The generated code looks like the following:

I loved the summary at the end of the generated code. For example, it maintained compatibility with existing tests and maintained backward compatibility. Very nice!

Conclusion

Looking ahead, CloudAEye is poised to revolutionize the way developers approach code reviews. With advancements in AI and automation, the tool will continue to evolve, offering even more intelligent insights, predictive issue detection, and seamless integrations with modern development workflows. As software development becomes increasingly complex, having an AI-powered assistant like CloudaEye will be indispensable for ensuring high-quality, secure, and efficient code.

References

Use Code Review for free at www.cloudaeye.com

Docs: Getting Started with Code Review

Video: Overview of Code Review

About CloudAEye

CloudAEye offers two SaaS services, Test Failure Analysis in CI and Code Review, that can save developers up to 12 hours per week.

Speed and quality are crucial in software development. Manual test failure analysis is time-consuming and error-prone, delaying issue resolution. CloudAEye's automated test failure analysis within CI pipelines revolutionizes software testing and debugging with our AI-augmented approach to accelerate root cause analysis (RCA). The GenAI-based solution swiftly identifies the underlying software issues behind test failures by transforming intricate error logs and code analysis into succinct RCA summaries.

Code reviews are vital for quality assurance before deployment but often take over a week. CloudAEye tackles these challenges by ensuring AI code security and reliability, detecting vulnerabilities, and providing actionable fixes. The solution acts as an essential guardrail for your AI projects, enabling rapid and confident progress.

Enjoy complimentary access at www.CloudAEye.com.