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Recent posts
AI/ML
Inside look: How GitLab's Test Platform team validates AI features
Learn how we continuously analyze AI feature performance, including testing latency worldwide, and get to know our new AI continuous analysis tool.
AI/ML
Developing GitLab Duo: How we are dogfooding our AI features
As part of our blog series, we share real-world examples of how we integrate AI throughout our software development lifecycle and how we use metrics to gauge their success.
Security
GitLab native secrets manager to give software supply chain security a boost
GitLab is building a secrets manager that is key to providing an end-to-end, cloud-agnostic approach to the management of sensitive information.
AI/ML
Developing GitLab Duo: AI Impact analytics dashboard measures the ROI of AI
Our blog series continues spotlighting a new feature that provides detailed metrics, such as the Code Suggestions Usage Rate, to help understand the effectiveness of AI investments.
Security
Detect application vulnerabilities with GitLab’s browser-based DAST
Learn why you should include dynamic application security testing as part of a defense-in-depth strategy for software development, and how to migrate from proxy-based DAST.
AI/ML
Developing GitLab Duo: How we validate and test AI models at scale
Our blog series debuts with a behind-the-scenes look at how we evaluate LLMs, match them to use cases, and fine-tune them to produce better responses for users.
Product
CI/CD Catalog goes GA: No more building pipelines from scratch
The CI/CD Catalog becomes generally available in GitLab 17.0. Get to know the capabilities for discovering and sharing pipeline building blocks to help standardize and scale pipelines.
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