Connect Azure DevOps and Google Vertex AI to power AI-driven automation
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How Zapier works
Zapier makes it easy to integrate Azure DevOps with Google Vertex AI - no code necessary. See how you can get setup in minutes.
Choose a trigger
A trigger is the event that starts your Zap—like a "Completed Build" from Azure DevOps.
Add your action
An action happens after the trigger—such as "Analyze Document" in Google Vertex AI.
You’re connected!
Zapier seamlessly connects Azure DevOps and Google Vertex AI, automating your workflow.
Supported triggers and actions
Zapier helps you create workflows that connect your apps to automate repetitive tasks. A trigger is an event that starts a workflow, and an action is an event a Zap performs.
- Build DefinitionRequired
- Build Status
- ProjectRequired
Try ItTriggerInstant- ProjectRequired
- Repository
- Branch
Try ItTriggerInstant- ProjectRequired
- Area Path
- Work Item Type
Try ItTriggerInstant- ProjectRequired
- Build DefinitionRequired
ActionWrite
- ProjectRequired
- PathRequired
Try ItTriggerInstant- ProjectRequired
- Area Path
- Work Item Type
- Contains StringRequired
Try ItTriggerInstant- ProjectRequired
- Area Path
- Work Item Type
- Changed Field
Try ItTriggerInstant- ProjectRequired
- TypeRequired
- TitleRequired
- Area
- Iteration
- Assigned To
- Description
ActionWrite
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Frequently Asked Questions about Azure DevOps + Google Vertex AI integrations
New to automation with Zapier? You're not alone. Here are some answers to common questions about how Zapier works with Azure DevOps and Google Vertex AI
What is needed to start integrating Azure DevOps with Google Vertex AI?
To integrate Azure DevOps with Google Vertex AI, you'll need valid credentials for both services. You'll also need to set up triggers in Azure DevOps, such as a code push or a completed build pipeline, which can initiate actions within Google Vertex AI.
How can I automate model training in Google Vertex AI from Azure DevOps?
You can automate model training by setting a trigger in Azure DevOps that, upon successful code commit or build completion, calls an action in Google Vertex AI to start a model training job.
Can we deploy models in Google Vertex AI directly from Azure DevOps?
Yes, it's possible to deploy models in Google Vertex AI directly from Azure DevOps. After a CI/CD pipeline completes in Azure DevOps, an action can be configured to deploy the latest model build into the production environment of Google Vertex AI.
Is it possible to monitor model performance on Google Vertex AI using data from Azure DevOps?
Yes, by configuring continuous monitoring triggers in Azure DevOps that collect relevant data after each deployment or integration cycle and send it to Google Vertex AI, the performance metrics can be reviewed and analyzed comprehensively.
What type of triggers are supported when integrating these two platforms?
Triggers like code commit, branch merge, pull request completion, build success or failure events are supported. Each of these triggers can be used to initiate subsequent actions within Google Vertex AI.
How do we handle authentication between Azure DevOps and Google Vertex AI?
Authentication is managed via OAuth tokens or service accounts depending on your organizational policies. We'll ensure secure connection by verifying permissions and managing credentials carefully during the integration setup.
Do we need any specific tools or plugins for this integration?
You'll typically require connectors that facilitate communication between Azure DevOps and Google Vertex AI. Our team constantly updates resources and documentation outlining any additional tools or plugins needed for seamless integration.



