'Custom Dashboard title'

Value Streams Dashboard

DETAILS: Tier: Ultimate Offering: GitLab.com, Self-managed, GitLab Dedicated

• Introduced in GitLab 15.8 as a closed beta feature with a flag named group_analytics_dashboards_page. Disabled by default.
• Released in GitLab 15.11 as an open beta feature with a flag named group_analytics_dashboards_page. Enabled by default.
• Generally available in GitLab 16.0. Feature flag group_analytics_dashboards_page removed.

To help us improve the Value Streams Dashboard, share feedback about your experience in this survey. For more information, see the Value Stream Management category direction page.

The Value Streams Dashboard is a customizable dashboard you can use to identify trends, patterns, and opportunities for digital transformation improvements. The centralized UI in the Value Streams Dashboard acts as the single source of truth (SSOT), where all stakeholders can access and view the same set of metrics that are relevant to the organization. The Value Streams Dashboard includes panels that visualize the following metrics:

• DORA metrics
• Value Stream Analytics (VSA) - flow metrics
• Vulnerabilities metrics
• GitLab Duo AI Code Suggestions

With the Value Streams Dashboard, you can:

• Track and compare the above metrics over a period of time.
• Identify downward trends early on.
• Understand security exposure.
• Drill down into individual projects or metrics to take actions for improvement.
• Understand the impact of adding AI to the software development life cycle (SDLC) and demonstrate the return on investment (ROI) of investments in GitLab Duo.

For a click-through demo, see the Value Stream Management product tour.

NOTE: Data displayed on the Value Streams Dashboard is continuously collected in the backend. If you upgrade to the Ultimate tier, you get access to historical data, and can view metrics about past GitLab usage and performance.

Value Streams Dashboard panels

The Value Streams Dashboard panels have a default configuration, but you can also customize the dashboard panels. The Value Streams Dashboard includes four panels:

• Overview
• DevSecOps metrics comparison
• DORA Performers score
• AI Impact analytics

Overview panel

• Introduced in GitLab 16.7 with a flag named group_analytics_dashboard_dynamic_vsd. Disabled by default.
• Generally available in GitLab 17.0.
• Feature flag group_analytics_dashboard_dynamic_vsd removed in GitLab 17.0.

The Overview panel provides a holistic view of the top-level namespace activity by visualizing key DevOps metrics. The panel displays metrics for:

• Subgroups
• Projects
• Users
• Issues
• Merge requests
• Pipelines

Data displayed in the Overview panel is collected by batch processing. GitLab stores record counts for each subgroup in the database, then aggregates the record counts to provide metrics for the top-level group. Data is aggregated monthly, around the end of the month, on a best-effort basis depending on the load on GitLab systems.

For more information, see epic 10417.

NOTE: To view metrics on the Overview panel, the background aggregation must be enabled.

DevSecOps metrics comparison panel

• Contributor count metric at the group level introduced to GitLab.com in GitLab 16.9.

The DevSecOps metrics comparison displays DORA4, vulnerability, and flow metrics for a group or project in the month-to-date, last month, the month before, and the past 180 days. This visualization helps you understand whether the key DevSecOps metrics improve month over month.

In the comparison panel, you can:

• Compare the performance between groups, projects, and teams at a glance.
• Identify the teams and projects that are the largest value contributors, overperforming, or underperforming.
• Drill down the metrics for further analysis.

When you hover over a metric, a tooltip displays an explanation of the metric and a link to the related documentation page.

The monthly values also indicate a percentage increase or decrease compared to the previous month.

The sparkline for the past six months represents value trends over this time period, not the percentage change rate. The sparkline color ranges from blue to green, where green indicates a positive trend, and blue indicates a negative trend. Sparklines help you identify patterns in metric trends (such as seasonal changes) over time.

Filter the DevSecOps metrics comparison panel by labels

Label filters are appended as query parameters to the URL of the drill-down report of each eligible metric and automatically applied. If the comparison panel from the configuration file is enabled with filters.labels, the drill-down links inherit the labels from the panel filter.

panels:
  - title: 'Group dora and issue metrics'
    visualization: dora_chart
    queryOverrides:
      namespace: my-dora-group
      filters:
        labels:
          - in_development
          - in_review

DORA Performers score panel

• Introduced in GitLab 16.3 with a flag named dora_performers_score_panel. Disabled by default.
• Enabled on GitLab.com in GitLab 16.9.
• Generally available in GitLab 16.11. Feature flag dora_performers_score_panel removed.

The DORA Performers score panel is a group-level bar chart that visualizes the status of the organization's DevOps performance levels across different projects for the last full calendar month.

The chart is a breakdown of your project's DORA scores, categorized as high, medium, or low. The chart aggregates all the child projects in the group.

The chart bars display the total number of projects per score category, calculated monthly. To exclude data from the chart (for example, Not included), in the legend select the series you want to exclude. Hovering over each bar reveals a dialog that explains the score's definition.

For example, if a project has a high score for deployment frequency (velocity), it means that the project has one or more deploys to production per day.

Filter the DORA Performers score by project topics

When you customize dashboards with a YAML configuration, you can filter the displayed projects by assigned topics.

panels:
  - title: 'My dora performers scores'
    visualization: dora_performers_score
    queryOverrides:
      namespace: group/my-custom-group
      filters:
        projectTopics:
          - JavaScript
          - Vue.js

If multiple topics are provided, all topics must match for the project to be included in the results.

AI Impact analytics

DETAILS: Tier: For a limited time, Ultimate. In the future, GitLab Duo Enterprise. Offering: GitLab.com, Self-managed

• Introduced in GitLab 16.11 with a flag named ai_impact_analytics_dashboard. Disabled by default.
• Generally available in GitLab 17.2. Feature flag ai_impact_analytics_dashboard removed.

AI Impact analytics displays SDLC metrics for a group or project in the month-to-date and the past six months. You can use this table to observe how changes in the AI usage metric correlate with changes in other metrics.

AI Impact analytics displays the following metrics for a group:

• GitLab Duo seats: Assigned and used: Percentage of assigned licensed seats that have used at least one AI feature in the last 30 days.

• Code Suggestions: Unique users: Percentage of users that engage with Code Suggestions every month. It is calculated as the number of monthly unique Code Suggestions users divided by total monthly unique contributors. Only unique code contributors, meaning users with pushed events, are included in the calculation.

• Code Suggestions: Acceptance rate: Percentage of code suggestions provided by GitLab Duo that have been accepted by code contributors in the last 30 days.

• Cycle time

• Lead time

• Deployment frequency

• Change failure rate

• Critical vulnerabilities over time

• Code Suggestions usage: Monthly user engagement with AI Code Suggestions.

  • The month-over-month comparison of the AI Usage unique users rate gives a more accurate indication of this metric, as it eliminates factors such as developer experience level and project type or complexity.
  • The baseline for the AI Usage trend is the total number of code contributors, not just users with GitLab Duo seats. This baseline gives a more accurate representation of AI usage by team members. To learn more about AI Impact analytics, see the blog post Developing GitLab Duo: AI Impact analytics dashboard measures the ROI of AI.
  • To analyze the performance of teams that use AI versus teams that don't, you can create a custom Value Streams Dashboard Scheduled Report based on the AI Impact view of projects and groups with and without GitLab Duo.

  NOTE: Usage rate for Code Suggestions is calculated with data starting from GitLab 16.11. For more information, see epic 12978.

Enable or disable overview background aggregation

DETAILS: Tier: Ultimate Offering: Self-managed, GitLab Dedicated

• Introduced in GitLab 16.1 with a flag named value_stream_dashboard_on_off_setting. Disabled by default.
• Enabled on self-managed in GitLab 16.4.
• Feature flag value_stream_dashboard_on_off_setting removed in GitLab 16.6.

To enable or disable the overview count aggregation for the Value Streams Dashboard:

1. On the left sidebar, select Search or go to and find your top-level group.
2. Select Settings > Analytics.
3. In Value Streams Dashboard, select or clear the Enable overview background aggregation for Value Streams Dashboard checkbox.

To retrieve aggregated usage counts in the group, use the GraphQL API.

View the Value Streams Dashboard

Prerequisites:

• You must have at least the Reporter role for the group.
• Overview background aggregation for Value Streams Dashboards must be enabled.
• To view AI Impact analytics, you must:
  • Enable Code Suggestions.
  • Configure ClickHouse for contribution analytics.
• To view the contributor count metric in the comparison panel, you must set up ClickHouse.

To view the Value Streams Dashboard:

• From Analytics Dashboards:

  1. On the group left sidebar, select Search or go to and find your group.
  2. Select Analyze > Analytics Dashboards.

• From Value Stream Analytics:

  1. On the left sidebar, select Search or go to and find your project or group.
  2. Select Analyze > Value stream analytics.
  3. Below the Filter results text box, in the Lifecycle metrics row, select Value Streams Dashboard / DORA.
  4. Optional. To open the new page, append this path /analytics/dashboards/value_streams_dashboard to the group URL (for example, https://gitlab.com/groups/gitlab-org/-/analytics/dashboards/value_streams_dashboard).

View the Value Streams Dashboard for a project

• Introduced in GitLab 16.7 with a flag named project_analytics_dashboard_dynamic_vsd. Disabled by default.

Prerequisites:

• You must have at least the Reporter role for the project.
• Overview background aggregation for Value Streams Dashboards must be enabled.

To view the Value Streams Dashboard as an analytics dashboard for a project:

1. On the left sidebar, select Search or go to and find your project.
2. Select Analyze > Analytics dashboards.
3. From the list of available dashboards, select Value Streams Dashboard.

Schedule Value Streams Dashboard reports

You can schedule reports using the CI/CD component Value Streams Dashboard Scheduled Reports tool. This tool saves time and effort by eliminating the need to manually search for the right dashboard with the relevant data, so that you can focus on analyzing insights. By scheduling reports, you can ensure that the decision-makers in your organization receive proactive, timely, and relevant information.

The Scheduled Reports tool collects metrics from projects or groups through the public GitLab GraphQL API, then builds a report using GitLab Flavored Markdown, and opens an issue in a specified project. The issue includes a comparison metrics table in Markdown format.

See an example scheduled report. To learn more, see the blog post New Scheduled Reports Generation tool simplifies value stream management.

Customize the dashboard panels

You can customize the Value Streams Dashboard and configure what subgroups and projects to include in the page.

To customize the default content of the page, you need to create a YAML configuration file in a project of your choice. In this file, you can define various settings and parameters, such as title, description, and number of panels and labels filters. The file is schema-driven and managed with version control systems like Git. This enables tracking and maintaining a history of configuration changes, reverting to previous versions if necessary, and collaborating effectively with team members. Query parameters can still be used to override the YAML configuration.

Before you customize the dashboard panels, you must select a project to store your YAML configuration file.

Prerequisites:

• You must have at least the Maintainer role for the group.

1. On the left sidebar, select Search or go to and find your group.
2. Select Settings > Analytics.
3. Select the project where you would like to store your YAML configuration file.
4. Select Save changes.

After you have set up the project, set up the configuration file:

1. On the left sidebar, select Search or go to and find the project you selected in the previous step.
2. In the default branch, create the configuration file: .gitlab/analytics/dashboards/value_streams/value_streams.yaml.
3. In the value_streams.yaml configuration file, fill in the configuration options:

# version - The latest version of the analytics dashboard schema
version: '2'

# title - Change the title of the Value Streams Dashboard.
title: 'Custom Dashboard title'

# description - Change the description of the Value Streams Dashboard. [optional]
description: 'Custom description'

# panels - List of panels that contain panel settings.
#   title - Change the title of the panel.
#   visualization - The type of visualization to be rendered
#   gridAttributes - The size and positioning of the panel
#   queryOverrides.namespace - The Group or Project path to use for the chart panel
#   queryOverrides.filters.excludeMetrics - Hide rows by metric ID from the chart panel.
#   queryOverrides.filters.labels -
#     Only show results for data that matches the queried label(s). If multiple labels are provided,
#     only a single label needs to match for the data to be included in the results.
#     Compatible metrics (other metrics will be automatically excluded):
#       * lead_time
#       * cycle_time
#       * issues
#       * issues_completed
#       * merge_request_throughput
panels:
  - title: 'Group usage overview'
    visualization: usage_overview
    queryOverrides:
      namespace: group
      filters:
        include:
          - groups
          - projects
    gridAttributes:
      yPos: 1
      xPos: 1
      height: 1
      width: 12
  - title: 'Group dora and issue metrics'
    visualization: dora_chart
    queryOverrides:
      namespace: group
      filters:
        excludeMetrics:
          - deployment_frequency
          - deploys
        labels:
          - in_development
          - in_review
    gridAttributes:
      yPos: 2
      xPos: 1
      height: 12
      width: 12
  - title: 'My dora performers scores'
    visualization: dora_performers_score
    queryOverrides:
      namespace: group/my-project
      filters:
        projectTopics:
          - ruby
          - javasript
    gridAttributes:
      yPos: 26
      xPos: 1
      height: 12
      width: 12

Supported visualization filters

The filters subfield on the queryOverrides field can be used to customize the data displayed in a panel.

DevSecOps metrics comparison panel filters

Filters for the dora_chart visualization.

DORA Performers score panel filters

Filters for the dora_performers_score visualization.

Usage overview panel filters

Filters for the usage_overview visualization.

Group and subgroup namespaces

Project namespaces

Dashboard metrics and drill-down reports

Value Streams Dashboard metrics with Jira

The following metrics do not depend on using Jira:

• DORA Deployment frequency
• DORA Lead time for changes
• Number of deploys
• Merge request throughput
• Median time to merge
• Vulnerabilities