What the ML is up with DevSecOps and AI?

Mar 16, 2023 · 6 min read
Taylor McCaslin GitLab profile

GitLab believes at our core that AI will revolutionize the power of DevSecOps platforms to bring to life a software development experience that feels straight out of science fiction. GitLab users already benefit from a step-function increase in productivity when they adopt our platform: streamlined collaboration, operational efficiencies, and massive acceleration in time to delivery. But by introducing machine learning (ML) and other artificial intelligence (AI) capabilities into the fabric of The DevSecOps Platform feature set, we aim to take those gains to a whole new level.

GitLab occupies a unique seat in relation to defining how AI and ML will impact DevSecOps into the future. As the creators of the DevSecOps platform category, we are the founders behind a successful philosophy for bringing DevSecOps principles into practice. By virtue of curating the entire software development lifecycle, our platform also has an unrivaled level of visibility into the code, configuration, testing, deployment, and operation of the applications it produces. It is in the rich data set underpinning that curated experience where unbounded opportunity lurks. These opportunities include the ability to deliver:

GitLab will focus on incorporating AI/ML capabilities that leverage our unique strengths to deliver unique value. In particular, we plan to:

AI/ML in GitLab today

Here are some of the ways we are using AI/ML in GitLab today.

AI/ML for automation

First, we are applying ML and AI to automate mundane tasks and reduce the cognitive load for our customers. We are currently developing AI Assisted capabilities to improve productivity and efficiency for everyone in the software delivery workflow. Here are some AI Assisted capabilities available in GitLab today:

Suggested Review Screenshot

Animated gif image of code suggestions

Protecting customer source code

We’ve heard from many of our enterprise DevSecOps customers that their organizations care deeply about the privacy of their source code. They understandably want control over who processes their data and if their code is used to train code generation AI models. That’s why we’ve built our code suggestions feature to work natively within GitLab. Customer source code does not leave the GitLab instance and it is not used to retrain generic multi-customer code generation models.

The road ahead for GitLab and AI

We plan to add many AI capabilities throughout our DevSecOps platform, including:

We also want to make it easier for customers to build and deploy amazing AI/ML-backed applications to their customers faster. We are working to integrate ModelOps features into the GitLab DevSecOps Platform to better support data science workloads and extend DevSecOps workflows to AI and ML workloads. This includes:

Follow along

This blog is the first in an ongoing series about GitLab’s journey to [build and integrate ML/AI into our DevSecOps platform. Throughout the series, we’ll feature blogs from our product, engineering, and UX teams that will showcase how we’re infusing AI/ML into GitLab.

We believe AI is going to dramatically change the way teams work and the way organizations develop, secure, and operate software. We’re using our core value of iteration and our experience building the most comprehensive DevSecOps platform to bring the power of AI/ML to bear on the software development lifecycle.

Want to continue reading about AI? Check out the next blog in this series:How AI-assisted code suggestions will advance DevSecOps!

Disclaimer: This blog contains information related to upcoming products, features, and functionality. It is important to note that the information in this blog post is for informational purposes only. Please do not rely on this information for purchasing or planning purposes. As with all projects, the items mentioned in this blog and linked pages are subject to change or delay. The development, release, and timing of any products, features, or functionality remain at the sole discretion of GitLab.

“AI will revolutionize DevSecOps platforms. Learn how @gitlab is integrating ML and AI” – Taylor McCaslin

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