Google Cloud-powered security feature previews AI’s role in cloud-to-edge application development
GitLab has incorporated an AI-based security feature that makes use of Google Cloud’s foundation models. The goal: help customers identify and address vulnerabilities quickly and securely. Using generative AI to speed up application development will eventually benefit the edge computing ecosystem by bringing new edge platform and application capabilities to a broader audience of developers.
Both GitLab and its Microsoft-owned competitor GitHub are web-based Git repositories that allow developers to store, manage and share their source code. Git is a version control system that enables developers to track changes in their codebase and collaborate with team members. Individual developers, small teams and large organizations use both platforms to manage their software projects and collaborate with their peers.
GitLab says it aims to enhance its customers’ DevSecOps process by implementing AI-assisted workflows for people that are involved in software delivery. The idea is that enterprises can speed up software development and quicken business transformation without compromising security or privacy. The company hopes to create a tenfold improvement in workflow efficiency for developers as it adds more AI-assisted features to its platform.
“Our partnership with Google Cloud enables GitLab to offer private and secure AI-powered features while maintaining customer data in our cloud infrastructure,” says David DeSanto, the chief product officer at GitLab.
By taking advantage of Google Cloud’s open generative AI infrastructure and customizable base models, GitLab customers can access AI-assisted features within the DevSecOps platform of the enterprise.
A new experimental feature called “Explain this Vulnerability” uses Google Cloud’s generative AI models to offer a natural-language explanation of any code vulnerabilities and suggestions for immediate fixes.
GitLab has added the feature to its list of AI-enabled features designed to increase developer productivity, joining “Explain this Code”, “Summarize Issue Comments” and “Summarize Merge Request Changes”.
“Organizations today are required to deliver software faster than ever before to remain competitive while requiring a stronger security posture in order to maintain customer, investor, and stakeholder trust,” says June Yang, the VP of Cloud AI and Industry Solutions at Google Cloud. “Together with GitLab, we’ll be able to deliver generative AI functionality that empowers our joint customers to increase delivery velocity without sacrificing security.”
The generative AI trend in DevSecOps
The 2023 DevSecOps Report: Security Without Sacrifices released by GitLab uncovered that developers are turning to AI more and more for testing and security; 62% of developers utilize AI/ML to examine their code, up from 51% in 2022. Furthermore, 36% of developers take advantage of AI/ML for code review, up from the preceding year’s 31%.
Interest in generative AI has been driven by OpenAI’s ChatGPT, which provides a conversational interface to large language models. For developers, this has resulted in new integrations and features such as GitHub Copilot, which is a cloud-based AI tool powered by OpenAI’s Codex model that provides real-time software code and functions suggestions.
In terms of edge computing, IoT is expected to be another beneficiary of generative AI for coding, while companies like Siemens are exploring its use for programming industrial control systems and robotics platforms.
Article Topics
application development | DevSecOps | generative AI | GitHub | GitLab | Google | Microsoft
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