Oobeya Quick Onboarding Guide
Welcome to Oobeya! We're excited to have you on board. This step-by-step guide will help you quickly get started.
Quick Onboarding Guide
Use this guide to connect your engineering tools, configure your organization, and create your first actionable engineering view in Oobeya.
This guide is primarily intended for Oobeya Workspace Administrators responsible for the initial configuration of Oobeya.
Before You Begin
Make sure that:
Your Oobeya workspace is available.
You have administrator access to Oobeya.
You have the required credentials or tokens for the tools you plan to connect.
The service account used to generate tokens has access to the required repositories, projects, pipelines, and boards.
Your organization has identified the first teams and repositories to onboard.
Start with a small, representative scope. Configure one or two teams first, validate the results, and then expand the setup across the organization.
Onboarding Overview
The recommended onboarding sequence is:
Define the initial scope
Connect your source code management platform
Initialize Development Analytics
Connect additional engineering tools
Add users and map identities
Create teams
Configure Team Scorecards
Initialize Project Analytics
Validate data and automate updates
Expand your Oobeya setup
Step 1: Define Your Initial Scope
Before connecting tools, define what you want to onboard first.
For the initial setup, identify:
One or two engineering teams
The repositories owned by those teams
The primary development branches
The related project management boards
The CI/CD pipelines used for production deployments
The users who will access Oobeya
The contributors who will be analyzed by Oobeya
Also decide which outcomes you want to review first:
Development activity and productivity metrics
Pull request and code review performance
DORA metrics
Project delivery and flow
Code quality
Team health and engineering risks
AI coding assistant adoption and impact
A clearly defined scope makes it easier to validate data, repository ownership, team mapping, and metric accuracy.
Step 2: Connect Your Source Code Management Platform
Oobeya uses source code management data as the foundation for Development Analytics.
Commonly supported SCM platforms include:
GitHub, GitLab, Azure DevOps, Bitbucket, Gitea, Gerrit.
2.1 Install the Add-on
Open Integrations in Oobeya.
Find your SCM platform.
Select the add-on.
Click Install.
See Installing an Add-on.
2.2 Add a Data Source
After installing the add-on:
Navigate to Data Sources.
Select the installed SCM platform.
Click New Data Source.
Enter the required URL, credentials, token, or connection details.
Save the data source.
Validate that Oobeya can access the expected organizations, projects, and repositories.
For provider-specific requirements and permission details, review the Integration Catalog.
The connected service account must be able to access every repository and project that you want to analyze.
Step 3: Initialize Development Analytics
After connecting your SCM platform, create your first Development Analytics analysis.
Development Analytics can analyze:
Commits
Contributors
Branches
Pull requests
Code review activity
Development patterns
Deployment activity
DORA metrics
To start an analysis:
Open Development Analytics.
Click New Analysis.
Select your SCM platform and data source.
Select the project, repository, and branch.
Choose the CI/CD strategy used by the repository.
Configure deployment and incident detection options when applicable.
Select the related team and historical analysis period.
Review the configuration and click Finish.
See Setting Up Development Analytics and DORA Metrics.
Configuration Notes
Select the correct primary or development branch.
Choose the CI/CD strategy that reflects the actual delivery workflow.
Configure the production deployment pipeline when you want to calculate deployment metrics.
Select the correct development model, such as pull request-based or trunk-based development.
Configure an incident source to calculate Change Failure Rate and Time to Restore Service accurately.
Avoid starting with every repository before validating the configuration on a smaller scope.
The initial historical analysis may take some time depending on the selected date range, repository size, and number of activities.
Step 4: Connect Additional Engineering Tools
While the initial repository analysis is running, connect the other tools used across your software delivery lifecycle.
Depending on your reporting goals, you can connect:
Project management
Jira, Azure Boards, ServiceNow
Work items, flow, predictability, lead time, cycle time
CI/CD
ArgoCD, Jenkins, GitHub Actions, GitLab CI, Azure Pipelines
Build, pipeline, and deployment activity
Code quality and security
SonarQube, SonarCloud, Fortify
Quality, security, maintainability, and technical debt signals
Monitoring and APM
New Relic, Dynatrace, Datadog, Elastic
Production incidents and operational signals
Test management
Xray, Testinium and supported testing tools
Test execution, automation, and efficiency signals
AI coding assistants
GitHub Copilot and supported AI tools
Adoption, usage, cost, and engineering impact signals
Identity providers
Microsoft Entra ID, LDAP, Active Directory
Authentication, provisioning, and user onboarding
Browse all available tools in the Integration Catalog.
Connect only the tools required for your initial use case. Additional integrations can be introduced after the first teams and metrics are validated.
Step 5: Add Users and Map Identities
Users must be configured correctly so that Oobeya can associate engineering activity with the correct profiles and teams.
You can add users through:
Microsoft Entra ID
Configure authentication and user access through Microsoft Entra ID.
See Microsoft Entra ID Integration.
LDAP or Active Directory
Connect your corporate directory to authenticate and import users.
See LDAP / Active Directory Integration.
Manual User Creation
Create individual users directly in Oobeya.
See Adding a New User.
Verify Contributor Accounts
A single developer may appear under different usernames or email addresses across Git, project management, code quality, and identity systems.
Review contributor identities and merge duplicate accounts where necessary. Correct identity mapping is especially important for:
Developer Profiles
Team Scorecards
Resource Allocation
AI Impact
Individual-level metrics
Cross-platform reporting
Step 6: Create Your Teams
Teams connect people, repositories, projects, and engineering metrics within Oobeya.
To create a team:
Open the team management area.
Click Add Team.
Enter the team name and description.
Add team members.
Assign the relevant team roles.
Save the team.
See Adding a Team.
Team Configuration Checklist
Before continuing, verify that:
All current team members are included.
Former team members are removed or marked correctly.
Contributor identities are mapped to the correct users.
The correct repositories are associated with the team.
The correct project boards are associated with the team.
Team ownership reflects the selected reporting period.
Team configuration affects scorecards, Symptoms, resource allocation, benchmarks, and team-level reporting. Review team membership regularly.
Step 7: Configure the Team Scorecard
Team Scorecards provide a unified view of engineering health by combining metrics from multiple data sources.
To configure the first scorecard:
Open the team.
Navigate to Team Scorecard.
Add the relevant scorecard widgets.
Select the required repositories, projects, and data sources.
Configure targets and benchmarks where applicable.
Save the scorecard.
Validate the results with the team or engineering manager.
See Team Scorecard.
A first scorecard can include signals from:
Development Analytics
Pull Request Analytics
DORA metrics
Project Analytics
Code Quality
Test Analytics
Bug Analytics
AI Impact
Engineering Symptoms
Start with a small number of meaningful metrics rather than displaying every available metric.
Step 8: Initialize Project Analytics
Connect a project management platform when you want to analyze delivery flow, work item progress, planning effectiveness, and predictability.
Project Analytics can provide visibility into:
Lead Time
Cycle Time
Velocity
Throughput
Predictability
Productivity
Work in Progress
Backlog Health
Innovation Rate
Project Contribution
To start an analysis:
Connect Jira, Azure Boards, or another supported project management platform.
Open Project Analytics.
Click New Analysis.
Select the data source, project, and board.
Configure work item types, workflow statuses, and analysis settings.
Associate the analysis with the relevant team.
Select the historical analysis period.
Review the configuration and start the analysis.
See Starting a Project Analytics Analysis.
Review status mappings and excluded work item types carefully. Incorrect workflow configuration can affect flow and delivery metrics.
Step 9: Validate Your Data
Before expanding Oobeya across the organization, validate the first results with the relevant engineering teams.
Development Analytics
Confirm that:
DORA Metrics
Confirm that:
Project Analytics
Confirm that:
Teams and Users
Confirm that:
Data validation should involve both the Oobeya administrator and the engineering teams that understand the actual workflows.
Step 10: Configure Automatic Updates
After validating the first analyses, configure automatic reanalysis so that Oobeya keeps engineering data up to date.
See Setting Automated Reanalyze for Development Analytics.
When selecting an update frequency, consider:
The size of the organization
The number of repositories and boards
The frequency of engineering activity
Available infrastructure resources
Reporting and operating review schedules
For on-premise environments, monitor resource consumption as the number of integrations and analyses increases.
Step 11: Expand Your Oobeya Setup
After the initial teams and data sources are validated, you can gradually enable additional Oobeya capabilities.
Engineering Insights and Symptoms
Automatically identify recurring bottlenecks, risks, and engineering anti-patterns.
AI Coding Assistant Impact
Understand AI coding assistant adoption and its relationship with engineering outcomes.
Resource Allocation
Understand how engineering capacity is distributed across projects and work categories.
Recommended Rollout Approach
For enterprise onboarding, use an incremental rollout:
Phase 1: Pilot
Phase 2: Standardize
Phase 3: Scale
Phase 4: Improve
Onboarding Completion Checklist
Use this checklist before completing the initial onboarding:
Next Steps
After completing the onboarding process:
Review the Metrics List.
Review the Symptoms Catalog.
Establish a recurring review process for team health, delivery, quality, and AI impact.
Need Help?
The Oobeya team is dedicated to ensuring a smooth onboarding experience. If you have any questions or feedback, reach out to us on our website or via your dedicated support channels.
Last updated