Azure Pipelines and fully integrated workflows
May 18, 2022

Azure Pipelines and fully integrated workflows

Matthew Budram | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Azure Pipelines

Azure Pipelines are used for any deployment of our apps, backend services and test automation. This is the backbone of our deployment process allows us to deliver within our release cycle. Our current deployment cycle is monthly - but at times we may have smaller more controlled deployments within a release cycle. Azure Pipelines are fully integrated with our workflows as we also use Azure DevOps and implementation was more effective and efficient for us than other tools that might exist.
  • Integration with SonarQube
  • Integration with Azure DevOps
  • Integration with GitHub
  • Error messaging when team members don't have permissions
  • deployment
  • building
  • test coverage monitoring
  • we have had outages from Azure in the past
The tools are very similar - but Azure Pipelines work best for Azure-based products are better suited for the stack. For our engineers, we could switch between all the various continuous integration/deployment tools without much issues, but it makes sense to use the stack recommended by Azure. Our team has the relevant support licences to get support from Microsoft for all our products.

Do you think Azure Pipelines delivers good value for the price?

Yes

Are you happy with Azure Pipelines's feature set?

Yes

Did Azure Pipelines live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Azure Pipelines go as expected?

I wasn't involved with the implementation phase

Would you buy Azure Pipelines again?

Yes

With a fully Microsoft Azure based workflow - Azure Pipelines makes absolute sense. Azure Pipelines are robust and work very well with SonarQube for test coverage and are shared with our developers. This prevents the developers for pushing code without unit tests across our backend and frontend platforms. We have reduced our instances of manual regression tests especially when there are multiple teams working across the same repositories.