Value Stream Management

1 post · Sep 2016 – Feb 2025

What this trail covers

GitLab's Value Stream Management (VSM) is enhanced with Scheduled Reports Generation, a CI/CD Catalog component that automates the creation and distribution of value stream reports. These reports collect metrics via the GitLab GraphQL API and are delivered as issues containing markdown comparison tables. This complements existing VSM capabilities like the Value Streams Dashboard and AI Impact Analytics, aiming to provide consistent monitoring, data-driven decision-making, and time savings for software managers.

All GitLab trails

Feb 2025How we reduced MR review time with Value Stream ManagementThis post details the customization of GitLab Value Stream Analytics (VSA) to specifically track 'Review Time to Merge.' It describes setting up a new custom stage with 'MR first reviewer assigned' as the start event and 'MR merged' as the end event. The post highlights the use of the Total Time Chart and Stage Navigation Bar for analyzing this custom stage, identifying bottlenecks such as delays in reviewer assignment, slow review start times, multiple feedback loops, and idle time post-approval. It also announces the upcoming development of a 'Merge request last approved at' event for even more granular visibility into the review process.
Jun 2024New Scheduled Reports Generation tool simplifies value stream managementIntroduces a new CI/CD Catalog component for Scheduled Reports Generation within GitLab Value Stream Management. This component leverages the GitLab GraphQL API to collect metrics and generates markdown reports delivered as issues. It enhances existing VSM capabilities by automating report distribution and providing consistent monitoring.
Oct 2018GitLab's product vision for 2019 and beyondThis post introduces the concept of Value Stream Management within GitLab, outlining a vision for automating workflow tracking from issue creation to production deployment. It highlights the potential for analytics to identify and address bottlenecks in stages like code review and QA. Mock-ups demonstrate the intended user experience for tracking time spent across different workflow stages.
Sep 2016Feature Highlight: Cycle AnalyticsThis post introduces Cycle Analytics, a new feature in GitLab 8.12 that measures the median time taken for each stage of the software development lifecycle (Issue, Plan, Code, Test, Review, Staging, Production). It details the specific metrics tracked for each stage and the dependencies on GitLab Flow, such as issue closing patterns in commit messages and CI configuration for production environments. The post also announces a release webcast for Cycle Analytics and GitLab 8.12.
Sep 2016Feature Preview: Introducing Cycle AnalyticsThis post introduces Cycle Analytics, a new feature that measures the time from an idea to production for each project. It breaks down the total time into multiple stages of the development cycle to help teams identify and reduce bottlenecks. The vision is to monitor the entire process from idea to production in one place. The first iteration is scheduled for release on September 22.
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