How Big Data and AI Can Help the Developer Toolchain Posted on : Nov 14 - 2022

Developers today have a fantastic assortment of tools and technology available to them, which they use to construct the digital world around us. However, the sheer number of choices in the DevOps and CICD toolchains introduces a vast amount of complexity, which leads to multiple inefficiencies. Now a new discipline called developer productivity engineering (DPE) is emerging to tackle this problem, and advanced analytics and AI play big roles.

While the advent of DevOps and continuous integration, continuous deployment (CICD) methods has made developers lives simpler in many respects, they have also unleashed new forces that hinder developer productivity, according to Hans Dockter, the CEO of Gradle, the for-profit company behind the leading open source build tool of the same name.

For starters, testing is critical to ensure software is bug free and doesn’t pose a security risk. Thanks to build tools like Gradle, Apache Maven and Bazel, developers no longer need to manually execute the various convoluted steps required to push a new feature or bug fix into production. With more than 3,000 integrations maintained by its open source community, the Gradel build tool can eliminate much of that drudge work.

But for some large enterprise or Web applications, there may be 10,000 tests that need to be run before code can be promoted into production. That means that even for the smallest code changes, it may take 24 hours to run all the checks . Multiple that times a thousand developers or so, and you quickly run into a development quagmire. View More