Development Analytics Group

Development Analytics Group under Developer Experience Stage
Category Handle
GitLab Group Handle @gl-dx/development-analytics
Slack Channel #g_development_analytics
Slack Handle @dx-development-analytics
Team Boards Team Issues Board, Team Epics Board, Support Requests
Issue Tracker tracker
Team Repositories development-analytics

Mission

Our mission is to enhance developer efficiency by delivering actionable insights, optimizing pipeline performance, and building scalable productivity tools that measurably improve the software development lifecycle.

Vision

We envision a future where GitLab’s development workflows are seamless, insightful, and empowered by data. The Development Analytics team will:

  • Establish GitLab as the industry benchmark for measurable developer productivity
  • Improve cycle time to industry-leading standards through tooling and practices
  • Create intuitive, powerful analytics dashboards that drive informed development decisions
  • Deploy AI-powered systems that optimize pipeline performance and resource utilization

Team members

Name Role
Paul John PhillipsPaul John Phillips Engineering Manager, Development Analytics / Feature Readiness
Andrejs CunskisAndrejs Cunskis Senior Software Engineer in Test, Development Analytics
David DieulivolDavid Dieulivol Senior Backend Engineer, Development Analytics
Ievgen ChernikovIevgen Chernikov Senior Software Engineer in Test, Development Analytics
Pranshu SharmaPranshu Sharma Intermediate Backend Engineer, Development Analytics
Lohit PeesapatiLohit Peesapati Intermediate Backend Engineer, Development Analytics

Core Responsibilities

flowchart LR
    DA[Development Analytics Team]

    DA --> MRCT[MR Cycle Time Improvement]
    DA --> Tools[Tooling Maintenance]

    MRCT --> Analytics[Analytics & Observability]
    MRCT --> ExecTime[Pipeline Execution Time Optimization]
    MRCT --> ReviewEng[Review Engagement Enhancement]
    MRCT --> PipeStab[Pipeline Stability Assurance]

    Tools --> Triage[Triage Ops]
    Tools --> Roulette[GitLab Roulette]
    Tools --> Danger[Dangerfiles]
    Tools --> EPInfra[Engineering Productivity Infrastructure]
    Tools --> CNG[CLI for Cloud Native GitLab deployment]

    click Triage "https://gitlab.com/gitlab-org/quality/triage-ops"
    click Roulette "https://gitlab.com/gitlab-org/gitlab-roulette"
    click Danger "https://gitlab.com/gitlab-org/ruby/gems/gitlab-dangerfiles"
    click EPInfra "https://gitlab.com/gitlab-org/quality/engineering-productivity-infrastructure"
    click Analytics "https://gitlab.com/groups/gitlab-org/-/epics/16185"
    click ExecTime "https://gitlab.com/groups/gitlab-org/-/epics/15989"
    click ReviewEng "https://gitlab.com/groups/gitlab-org/-/epics/16028"
    click PipeStab "https://gitlab.com/groups/gitlab-org/-/epics/16186"
    click MRCT "https://gitlab.com/groups/gitlab-org/-/epics/16026"
    click CNG "https://gitlab.com/gitlab-org/gitlab/-/tree/master/qa/gems/gitlab-cng"

Roadmap

As part of our commitment to aligning with GitLab’s company goals, our team conducts a thorough review of company-level Roadmap and Objectives and Key Results (OKRs) at the beginning of each quarter. This process ensures that our efforts are strategically focused on delivering high-impact results that contribute to the broader organizational objectives. View the Development Analytics Roadmap for FY26 for detailed insights and upcoming priorities

Custom Tooling and Dogfooding

GitLab dogfoods extensively. The Development Analytics team builds custom tooling to address GitLab functionality gaps, creating a valuable feedback loop between internal needs and product development.

The Custom Data ↔ Custom Tooling Loop

Over the years, we’ve built custom tooling for missing GitLab features (triage-ops, test health management, CI observability, in-job metrics). This custom tooling generates custom data that’s not part of GitLab’s production database.

By integrating custom tooling as product features, we achieve:

  • Features that benefit customers (if it helps us as customer zero, it likely helps others)
  • Custom data becomes product data, available by default in visualizations
  • Reduced technical debt from maintaining custom solutions
  • Every improvement benefits both customers and internal teams

Current Custom Tooling

CI/CD Pipeline Observability

Tool Purpose Repository Status Product Potential
CI Alerts Real-time alerting for pipeline failures and performance issues ci-alerts Active High - Could become native pipeline alerting
CI/CD Pipelines Observability Pipeline visualizer, failure categorization, CI log scraping for custom metrics, and comprehensive analytics requiring tests as first-class citizens and runner improvements Epic #22, Pipeline Visualizer, Failure Categories Active High - Requires runner epic and native test concept in product
Snowflake Observability Custom dashboards and analytics for GitLab.com operations and performance snowflake-dashboard-sql Active High - Could be integrated directly in product

Triage and Issue Management Automation

Tool Purpose Repository Status Product Potential
Triage Ops (Reactive) Real-time automated issue and MR triage using custom policies and reactive engine triage-ops Active High - Advanced real-time triage automation
Triage Ops (Scheduled) Scheduled triage operations including weekly team reports and batch processing triage-ops Active High - Could benefit many customers (for example, weekly team reports)

Review and Code Quality Tools

Tool Purpose Repository Status Product Potential
GitLab Roulette Intelligent reviewer assignment system that considers domain expertise, availability, and workload gitlab-roulette Active High - Core developer workflow improvement
GitLab Danger Files Standardized CI-based code review automation and policy enforcement gitlab-dangerfiles Active High - Demonstrates advanced merge request automation
Renovate Bot Automated dependency management across GitLab projects renovate-gitlab-bot Active High - Multiple teams built similar solutions, clear product need

Test Health and Quality Management

Tool Purpose Repository Status Product Potential
Flaky Tests Management RSpec report parsing from job artifacts, automated test behavior analysis, GitLab issue creation for test health tracking, and data pipeline to GCS/Snowflake gitlab_quality-test_tooling Active High - Native test results concept missing from product
Slow Tests Management RSpec profiling and analysis with custom frontend/backend for test performance insights RSpec profiling stats, gitlab_quality-test_tooling Active Medium - Built but limited team adoption/reaction

Incident and Process Management

Tool Purpose Repository Status Product Potential
Main Branch Broken Process Automated identification, incident management, response, and revert MR handling broken main branch workflow Active High - Critical workflow for maintaining stable main branches

Data and Analytics Infrastructure

Tool Purpose Repository Status Product Potential
Data Pipelines Custom data processing pipelines feeding Snowflake dashboards and analytics test_tooling project, various GCS buckets, internal events, Snowflake SQL queries, alerting Active Medium - Could be integrated directly in product

Dashboards

Pipeline Duration Analytics

Pipeline Stability Analytics

Note: Access to these dashboards requires appropriate permissions. Contact team leads for access requests.

How we work

Philosophy

  • We prioritize asynchronous communication and a handbook-first approach, in line with GitLab’s all-remote, timezone-distributed structure.
  • We emphasize the Maker’s Schedule, focusing on productive, uninterrupted work.
  • Most critical recurring meetings are scheduled on Tuesdays and Thursdays.
  • We dedicate 3–4 hours weekly for focused learning and innovation. This protected time enables the team to explore emerging technologies, conduct proof-of-concepts, and stay current with industry trends. Meeting requests during these blocks require advance notice.
  • All meeting agendas can be found in the Team Shared Drive as well as in the meeting invite.

Meetings/Events

Event Cadence Agenda
End-of-Week progress update Once a week (Wednesday) Summarize status, progress, ETA, and areas needing support in the weekly update in issues and Epics. We leverage epic-issue-summaries bot for automated status checks
Team meeting Twice a month on Tuesday 4:00 pm UTC Agenda
Monthly Social Time Monthly on last Thursday 4:00 pm UTC No agenda, fun gathering. Choose one of the slots based on your timezone alignment. Read Virtual team building
Quarterly Business Report Quarterly Contribute to team’s success, learnings, innovations and improvement opportunities for each business quarter
1:1 with Engineering Manager Weekly Discuss development goals (see the 1:1 guidelines)
Team member’s coffee chats Once/twice a month Optional meetings for team members to regularly connect

Yearly Roadmap Planning

  • Each financial year, we create a roadmap to ensure visibility and alignment.
  • We conduct an intensive month-long exercise (usually in Q4) to gather input from stakeholders.
  • DRIs take the lead drafting the roadmap using the roadmap prep-work template).
  • Once the roadmap is approved, during our bi‑weekly team meetings, we review progress, address blockers, and gather feedback on the planned roadmap work.

Iterations

Once the yearly roadmap is defined, we structure our work using GitLab Iterations within a twice-a-month iteration model. This approach ensures consistent progress tracking, clear priorities, and iterative improvements. Here are our current iteration board and previous iterations for reference. As a team, we make sure:

  1. Each issue is assigned to a Development Analytics Iteration.
  2. Issues that are not worked on within the iteration automatically roll over to the next iteration.
  3. In every twice-a-month team meeting, we review the iteration boards and track velocity using burndown charts.

Internal Rotation & Support Requests

Internal Rotation

We use an internal rotation for support requests and other team maintenance tasks. This frees up time for other Engineers in the team to work on planned work.

Support Requests

  • If one finds a bug, needs assistance, or identifies an improvement opportunity then raise support requests using the ~"group::Development Analytics" and ~"development-analytics::support-request" labels. If the issue is urgent, escalate to the designated Slack channel - #g_development_analytics.
  • If a request first comes through Slack, either the requester or a group::Development Analytics member should open an issue with the correct labels to ensure proper tracking and triage.
  • The team reviews the support request board and prioritizes accordingly. Generally, the team reserves ~20% of weekly time for support tasks, though this may vary based on current priorities.

Tools/Repository Maintenance

  • Team does not automatically watch every new issue created in each group-owned repository—use the group labels or escalate in Slack to ensure visibility.
  • We highly promote self-served Merge Requests. If one already identified a fix or improvement, we request opening an MR for faster turnaround. The ~group::development analytics maintainers will review and merge as appropriate.
  • Feature work and bug fixes follow the team’s current priorities.
  • Find the version management rituals for ~group::development analytics owned repositories:
Repository Release Process
gitlab-roulette Version updates are not scheduled on a set cadence. A release can be cut whenever a version-update MR is submitted.
gitlab-dangerfiles Same as above—no regular cadence; release triggered by a version-update MR.
triage-ops A new release is initiated after merging a new commit into the default branch.
engineering-productivity-infrastructure Dependency update MRs are generated by Renovate bot.

Automated Label Migration

For details on label migration, see the Handbook entry for creating label migration triage policy with GitLab Duo Workflow.

Last modified October 7, 2025: Remove 'Our Data Needs' section from Development Analytics (a7f6817a)
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