Azure DevOps Server (Also known as TFS)
- 2010, 2012, 2013, 2015 (up to Update 3), 2017, 2017 (Update 2), 2018, 2019, 2020
Azure DevOps Services (Also known as VSTS)
- 10.x to 20.x
Azure DevOps – Digital.ai Agility 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, the cross-functional collaboration helps the teams get complete context of the business requirements.
Integrating Digital.ai Agility (Formerly VersionOne) with Azure DevOps (Both Azure DevOps Server and Services, also known as TFS and VSTS) 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 users clarity on business requirements and expectations.
How Azure DevOps – Digital.ai Agility 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
- Track the estimated and actual development efforts
With Azure DevOps + Digital.ai Agility integration, enterprises can:
How OpsHub Integration Manager integrates Azure DevOps and Digital.ai Agility
OpsHub Integration Manager integrates Digital.ai Agility (Formerly VersionOne) and Azure DevOps (both Azure DevOps Server and Services, also known as TFS and VSTS) in a bi-directional 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 work item at each stage of development. On the other hand, Azure DevOps users are always up-to-date on iterations’ schedules and changes/enhancements made to a customer request.
Popularly synchronized entities
Use Case: Digital.ai Agility integration with Azure DevOps
Problem statement: The Project Management Team is using Digital.ai Agility (Formerly VersionOne) and the Development team is using Azure DevOps. 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 Azure DevOps and Digital.ai Agility(Formerly VersionOne) 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.
- The Project Manager logs a ‘user story’ in Digital.ai Agility.
- The ‘user story’ synchronizes to Azure DevOps .
- The development team breaks the ‘user stories’ into ‘tasks’ in Azure DevOps and log their effort hours.
- The ‘tasks’ in Azure DevOps are synchronized to ‘Actuals’ in Digital.ai Agility, which is the effort tracking entity.
- The Project Manager, therefore, has clear and real-time visibility into how the development work is progressing.
Benefits of integration for Digital.ai Agility and Azure DevOps users
Digital.ai Agility 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
Azure DevOps users
- Access to the business requirements and associated updates from within Digital.ai Agility
- Complete context of the customer requirements and priorities
- No manual efforts needed to keep product management teams updated on the development status