{"id":220,"date":"2020-09-12T16:01:52","date_gmt":"2020-09-12T16:01:52","guid":{"rendered":"https:\/\/machine-learning.webcloning.com\/2020\/09\/12\/how-devfactory-builds-better-applications-with-amazon-codeguru\/"},"modified":"2020-09-12T16:01:52","modified_gmt":"2020-09-12T16:01:52","slug":"how-devfactory-builds-better-applications-with-amazon-codeguru","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2020\/09\/12\/how-devfactory-builds-better-applications-with-amazon-codeguru\/","title":{"rendered":"How DevFactory builds better applications with Amazon CodeGuru"},"content":{"rendered":"
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This post is written in collaboration with DevFactory, an <\/em>AWS Select Technology Partner<\/em><\/a>.<\/em><\/p>\n

DevFactory<\/a> is an enterprise SaaS-focused company that is responsible for innovation, development, and operation of over 120 enterprise products. DevFactory also offers DevGraph, an integrated suite of software development tools built on AWS.<\/p>\n

Amazon CodeGuru<\/a> is an automated code review service that helps developers improve their quality of code by recommending actions in code review. CodeGuru consists of two services:<\/p>\n

In this post, we talk about how DevFactory uses CodeGuru Reviewer to improve their software as a service (SaaS) applications.<\/p>\n

What is CodeGuru Reviewer?<\/h2>\n

CodeGuru Reviewer is a code review service that uses a combination of machine learning (ML) and human curation techniques to analyze millions of lines of over 10,000 open-source projects and the Amazon internal code base to learn coding practices. It uses these models to find code issues such as concurrency race conditions, resources leaks, and wasted CPU cycles.<\/p>\n

DevFactory\u2019s challenge<\/h2>\n

DevFactory has more than 120 products and manages over 650 million lines of code. Most of these products were developed over the last two decades and therefore have custom code to implement widely available, off-the-shelf services. To adopt, upgrade, and maintain the code base with a global, fully remote workforce, DevFactory is constantly evolving and adding automation where necessary.<\/p>\n

One key part of the strategy is to identify and enhance the gems in each newly acquired product. These are the services, features, and applications that are both unique and valuable to the customers. ML-driven forecasts<\/a>? Business intelligence from social graphs<\/a>? Containerization and productivity enhancement at scale<\/a>? DevFactory wants their engineering teams to deliver these to customers, and leave the undifferentiated heavy lifting to AWS services and infrastructure.<\/p>\n

The following table shows DevFactory by the numbers.<\/p>\n\n\n\n\n
Verticals<\/strong><\/td>\nRepositories<\/strong><\/td>\nLines of Code<\/strong><\/td>\nNumber of Languages<\/strong><\/td>\n<\/tr>\n
20<\/td>\n6,000<\/td>\n~650 million<\/td>\n45<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

In addition to jettisoning undifferentiated code, monitoring and maintaining the existing code base requires effort. DevFactory\u2019s ideal code analysis solution is:<\/p>\n