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Digital.ai Agility – Azure DevOps Server (TFS) Integration

The integration of Digital.ai Agility (Formerly VersionOne) and Azure DevOps Server (Also known as TFS) brings seamless coordination between the product management and development team, which in turn paves the way for a highly productive, agile delivery chain. With the integration of these two systems, enterprises can have cross-functional transparency and enriched collaboration across the business and technical verticals.

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Digital.ai Agility – Azure DevOps Server Integration Overview

In an Application Lifecycle Management (ALM) ecosystem, the choice of systems and the collaboration between the cross-functional teams play a great role. While the choice of systems impacts the productivity of a team, cross-functional collaboration helps the teams get complete context of the business requirements.

Integrating Digital.ai Agility (Formerly VersionOne) with Azure DevOps Server (Also known as TFS) helps the project & portfolio management teams have real-time visibility into the complete delivery ecosystem. It also helps in creating traceability for all work items in Digital.ai Agility to the source code repository and vice versa. On the other hand, it gives Azure DevOps Server users clarity on business requirements and expectations.

How Digital.ai Agility – Azure DevOps Server integration is beneficial for an enterprise

  • Trace the requirement breakdown and associated test cases
  • Get complete context of the business requirement and receive real-time updates when there is a change in the plan
  • Coordinate on the delivery timelines seamlessly with concurrent updates on changes
  • Full traceability into the Quality Assurance (QA) reports

With Digital.ai Agility + Azure DevOps Server integration, enterprises can:

Digital.ai Agility Azure DevOps Server (TFS) Integration

How OpsHub Integration Manager integrates Digital.ai Agility and Azure DevOps Server

OpsHub Integration Manager integrates Digital.ai Agility (Formerly VersionOne)and Azure DevOps Server (Also known as TFS) in a bidirectional manner. It ensures that all historical and current data is available to each user, in that user’s preferred system, with full context, in real-time. Digital.ai Agility users have traceability for each workitem at each stage of development. On the other hand, Azure DevOps Server (Also known as TFS) users are always up-to-date on iterations schedules and changes/enhancements made to customer requests.

Popularly synchronized entities

Digital.ai Agility Azure DevOps Server (TFS) Entities Mapping

Use Case: Digital.ai Agility integration with Azure DevOps Server

Problem statement: The project management team is using Digital.ai Agility (Formerly VersionOne) and the development team is using Azure DevOps Server (Also known as TFS). If these two systems are not integrated, the Project Manager doesn’t have clear visibility into efforts taken to complete a task, status of a task, and similar details to plan work.

Solution: When Digital.ai Agility (Formerly VersionOne) and Azure DevOps Server (Also known as TFS) are integrated, the Project Manager will have real-time visibility into the progress of a customer requirement, which in turn will improve the overall planning and estimation process.

  1. The Project Manager logs a ‘user story’ in Digital.ai Agility.
  2. The ‘user story’ synchronizes to Azure DevOps Server.
  3. The development team breaks the ‘user stories’ into ‘tasks’ in Azure DevOps Server and log their effort hours.
  4. The ‘tasks’ in Azure DevOps Server are synchronized to ‘Actuals’ in Digital.ai Agility, which is the effort tracking entity.
  5. The Project Manager, therefore, has clear and real-time visibility into how the development work is progressing.
Digital.ai Agility Integration with Azure DevOps Server (TFS)

Benefits of integration for Digital.ai Agility and Azure DevOps Server users

Digital.ai Agility users

  • Access to the business requirements and associated updates from within Digital.ai Agility (Formerly VersionOne)
  • Complete context of the customer requirements and priorities
  • No manual efforts needed to keep product management teams updated on the development status

Azure DevOps Server users

  • Traceability for business requirements throughout the ALM tool chain
  • Visibility into the progress of development work & the QA cycle
  • No dependency on manual communication for making business decisions