DEVOPSdigest

GitLab announced new innovations across the platform to streamline how organizations build, test, secure, and deploy software.

GitLab Duo Enterprise, a new end-to-end AI add-on, combines the developer-focused AI capabilities of GitLab Duo Pro—organizational privacy controls, code suggestions, and chat—with enterprise-focused AI capabilities to help organizations proactively detect and fix security vulnerabilities, summarize issue discussions and merge requests, resolve CI/CD bottlenecks and failures, and enhance team collaboration.

A new AI impact dashboard and value stream forecasting capability will give an organization insight into its usage of AI features and their effect on software development lifecycle metrics such as cycle time and deployment frequency.

Organizations can customize GitLab Duo with context from their software projects for model personalization. Additionally, GitLab Duo Enterprise provides the option for self-hosted model deployments to support organizations that cannot connect their secure, air-gapped environments to internet-enabled services. GitLab Duo Enterprise will be generally available to Ultimate customers in the next few months.

GitLab also launched the general availability of a new CI/CD catalog to help organizations improve efficiency and standardize workflows with a centralized portal for customers to discover, reuse, and contribute pre-built CI/CD components. In addition to the public catalog, organizations can create a private catalog to distribute customized pipelines that automate workflows specific to their needs without compromising security.

Additional upcoming GitLab 17 capabilities include:

- Native Secrets Manager to allow customers to store sensitive credentials within GitLab.

- GitLab Dedicated on Google Cloud to assist organizations in meeting complex compliance requirements.

- Static Application Security Testing (SAST) integrations to help improve accuracy, reduce false positives, and quickly identify and resolve application-layer risks.

- Product analytics features to enable customers to understand user behavior patterns, measure product performance, and prioritize feature enhancements.

- Observability capabilities to allow development and operations teams to understand the application impact of a code or configuration change through error tracking, distributed tracing, metrics, and logs.

- Enterprise agile planning capabilities, including enhanced epics, custom fields in issues, Wikis, roadmaps, and objectives and key results (OKRs), to bring non-technical users into the same DevSecOps platform where engineers build, test, secure, and deploy code.

- A Model Registry to enable data scientists to develop AI/ML models on the same platform where engineers build, test, secure, and deploy code.

“GitLab continues to revolutionize the way organizations develop, build, secure, and deploy software faster leveraging a comprehensive DevSecOps platform,” said David DeSanto, chief product officer, GitLab. “GitLab 17 ushers in the future of AI-driven software innovation by removing silos across every team involved in delivering software value, automating tasks and complex workflows, and ensuring security and compliance is built-in from the beginning.”