We are pleased to announce the launch of Python support for Amazon CodeGuru, a service for automated code reviews and application performance recommendations. CodeGuru is powered by program analysis and machine learning, and trained on best practices and hard-learned lessons across millions of code reviews and thousands of applications profiled on open-source projects and internally at Amazon. The launch of Python support extends CodeGuru beyond its original Java support. Python is a widely used language for various use cases, including web app development and DevOps. Python's growth in data analysis and machine learning areas is driven by its rich frameworks and libraries.

This is a guest post co-written by Sergio Delgado from YoucanBook.me. In their own words, "YouCanBook.me is a small, independent and fully remote team, who love solving scheduling problems all over the world." At YoucanBook.me, we like to say that we're "a small company that does great things." Many aspects of our day-to-day culture are derived from such a simple motto, but especially a great emphasis on the efficiency of our operations. Although we're far from the first years in which our CTO programmed the entire first version of our SaaS tool, when I joined the company, we were only five developers, of which only three were in charge of backend services, and none were dedicated to it 100%.

Amazon Web Services (AWS) has made generally available a tool dubbed Amazon CodeGuru that employs machine learning algorithms to recommend ways to improve code quality and identify which lines of code are the most expensive to run on its cloud service. Peder Ulander, director of open source for AWS, said Amazon CodeGuru not only helps improve performance and resource utilization but also reduces the time and effort spent optimizing applications before and after they are deployed. Amazon CodeGuru is based on a set of AWS machine learning algorithms to identify best practices for deploying code. It creates a profile of the code deployed and then surfaces recommendations to improve performance and reduce costs by employing the most appropriate tier of the cloud service. That latter capability is critical because developers don't always factor costs into deciding which tier of a cloud service to employ.

Amazon Web Services Inc. said today its new Amazon CodeGuru service, which relies on machine learning to automatically check code for bugs and suggest fixes, is now generally available. Amazon announced the tool in preview at its AWS re:Invent event in December. "It's challenging to have enough experienced developers with enough free time to do code reviews, given the amount of code that gets written every day," the company said today. "And even the most experienced reviewers miss problems before they impact customer-facing applications, resulting in bugs and performance issues." AWS CodeGuru is actually made up of two separate tools, including a Reviewer and a Profiler, and they do pretty much what the names suggest.

Amazon CodeGuru is a recently launched chargeable machine learning service, currently still in preview mode. It was first announced in Andy Jassy's keynote at Amazon's AWS re:Invent 2019 conference that took place on December 2–6, 2019. The service is comprised of two parts: Amazon CodeGuru Reviewer executes automated code reviews and provides code issue detection, whereas Amazon CodeGuru Profiler searches for ways to improve the application's performance. Amazon CodeGuru was trained on internal Amazon projects as well as more than 10,000 open source GitHub projects. Amazon CodeGuru Reviewer is designed to find issues in code via automatic detection and provide recommendations on resolving them.

AWS introduced new services that use AI to allow more developers to apply machine learning to create better end user experiences, including new machine learning-powered enterprise search, code reviews and profiling, fraud detection, medical transcription, and human review of AI predictions. Machine learning continues to grow at a rapid clip, and today there are tens of thousands of customers doing machine learning on AWS (twice as many as the next largest cloud provider), including many customers that opt to use AWS's fully managed AI Services like Alfresco, Bayer Crop Science, Cerner, CJ Cox Automotive, C-SPAN, Deloitte, Domino's, Emirates NBD, Fred Hutchinson Cancer Research Center, FICO, FINRA, Gallup, Kelley Blue Book, Kia, Mainichi Newspapers Co, NASA, PricewaterhouseCoopers, White House Historical Association, and Zola. In the past year, AWS has introduced several new fully managed AI Services like Amazon Personalize and Amazon Forecast that allow customers to benefit from the same personalization and forecasting machine learning technology used by Amazon's consumer business to power its award-winning customer experiences. AWS customers are interested in learning from Amazon's vast experience using machine learning at scale to improve operations and deliver better customer experiences, without needing to train, tune, and deploy their own custom machine learning models. Today, AWS is announcing five new AI services that build upon Amazon's rich experience with machine learning, and allow organizations of all sizes across all industries to adopt machine learning in their enterprises – with no machine learning experience required. Despite many attempts over many years, internal search remains a vexing problem for today's enterprises, and most employees still frequently struggle to find the information they need. Organizations have vast amounts of unstructured text data, much of it incredibly useful if it can be discovered, stored in many formats and spread across different data sources (e.g.

It's like having a distinguished engineer on call, 24x7 Amazon CodeGuru is a machine learning service for automated code reviews and application performance recommendations. It helps you find the most expensive lines of code that hurt application performance and keep you up all night troubleshooting, then gives you specific recommendations to fix or improve your code. CodeGuru is powered by machine learning, best practices, and hard-learned lessons across millions of code reviews and thousands of applications profiled on open source projects and internally at Amazon. With CodeGuru, you can find and fix code issues such as resource leaks, potential concurrency race conditions, and wasted CPU cycles. And with low, on-demand pricing, it is inexpensive enough to use for every code review and application you run.