Development Analytics Group
Development Analytics Group under Developer Experience Stage
Common Links
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 GitLabโs 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
Core Responsibilities
| Core Responsibilities |
Goals |
| Improve developer experience and productivity |
- โก Create intuitive dashboards, predictive analytics, and benchmarks to enable data-driven decisions.
- ๐ Track developer engagement and satisfaction and use the data to drive process and tooling improvements.
- ๐ Optimize workflows and reduce MR cycle times. |
| Enhance developer tools and processes |
- ๐ค Deploy self-served AI evalution tooling to effectively utilize data for enhancing the performance of GitLab Duo
- ๐ ๏ธ Automate repetitive and manual tasks, such as issue tracking and pipeline failure triage, to enhance operational efficiency.
- ๐ง Develop robust self-healing systems to ensure resilience and reliability across workflows. |
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 detailed insights and upcoming priorities
Dashboards
Pipeline Duration Analytics
Pipeline Stability Analytics
AI Latency Analytics
Note: Access to these dashboards requires appropriate permissions. Contact team leads for access requests.
How we work
- 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.
Work management
Planning
- Each financial year, we develop a clear roadmap for the team to enhance visibility and alignment.
- Our roadmap preparation is an intensive month-long exercise (usually in Q4), led by a DRI. During this phase, DRIs take the lead in drafting the roadmap using the roadmap prep-work template for necessary project tracks. This involves gathering inputs from the team, various stakeholders, assessing past performance, and aligning with the strategic goals of the Development Analytics group.
- We utilize and plan OKRs to prioritize the roadmap items.
- Adhering to our team’s work rituals, we conduct reviews to assess progress, address challenges, and recalibrate goals if necessary every two weeks.
- We maintain a Team Board to visualise the current state of the feature work.
Working with us through support requests
We estimate ~20% of weekly time for support tasks, and balancing our roadmap work with emerging support needs. Please note this estimate varies depending upon ongoing priorities.
Automated label migration
Please read our handbook entry for creating label migration triage policy with GitLab Duo Workflow
Summary
This guide provides comprehensive instructions for writing triage automation policies in triage-ops using GitLab Duo Workflow. You will be able to self service label migrations after a department re-org by following this page.
Todo: include instructions for writing policies to perform other types of automated tasks.
Purpose
Triage policies are used when team members migrate labels across existing issues, merge requests, and epics using gitlab-triage. This tool automates triaging through policies defined in YAML. To optimize operational efficiency and ensure seamless implementation, we recommend self-servicing the label migration MRs using GitLab Duo Workflow.
Abhinaba Ghosh
Andrejs Cunskis
Chloe Liu
Dan Davison
David Dieulivol
Ievgen Chernikov
Jennifer Li