Browse articles that include the performance tag


Overcome AI sprawl with a Value Stream Management approach
From The Source: Learn how an AI strategy based on Value Stream Management can stop AI sprawl and supply chain constraints and drive ROI.

How we designed the GitLab Reference Architectures
Take a look back with us as we dive into our Reference Architectures design journey to help users easily deploy GitLab at scale. Learn our goals, process, and what's happened in the five years since.

Building GitLab with GitLab: A multi-region service to deliver AI features
Discover how we built our first multi-region deployment for teams at GitLab using the platform's many features, helping create a frictionless developer experience for GitLab Duo users.

Monitor application performance with Distributed Tracing
Learn how Distributed Tracing helps troubleshoot application performance issues by providing end-to-end visibility and seamless collaboration across your organization.

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.

A beginner's guide to the Git reftable format
In Git 2.45.0, GitLab upstreamed the reftable backend to Git, which completely changes how references are stored. Get an in-depth look at the inner workings of this new format.

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.
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