Trigger
Azure DevOps and Databricks integration
Automate Azure DevOps + Databricks workflows
Connect Azure DevOps and Databricks to automate your development and analytics workflows, syncing work items with data pipelines and streamlining CI/CD processes with real-time insights.
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Technical overview
What this integration can actually do
This is not a rigid connector between Azure DevOps and Databricks. Use native nodes where they already exist, then cover edge cases with webhook, polling, HTTP Request, or JavaScript in the same scenario.
3 triggers and 13 actions across Azure DevOps and Databricks
Gets data from
Code Events (Instant) and Git Events (Instant), plus 1 more trigger
Can do
Create Work Item and Get Work Item, plus 11 more actions
Works via
Native nodes, Webhooks, Polling, HTTP Request, JavaScript
Customizable with
field mapping, filters, branching, retries, dedupe logic, and custom API or JavaScript steps.
Capabilities
Triggers & Actions
Every event and operation available when connecting Azure DevOps and Databricks — from both apps.
Trigger
Git Events (Instant)
Trigger
Work Item Events (Instant)
Production readiness
Production workflow controls
Use these controls when a workflow needs to stay stable after launch, not just pass a happy-path test.
01
Retry failed API calls
Automatically retry temporary failures before a run is marked as failed.
02
Handle 429 / rate-limit responses
Pause, back off, and continue the workflow safely when an upstream API throttles requests.
03
Add fallback branches for missing fields
Route incomplete payloads into a safe branch instead of letting the main scenario break.
04
Prevent duplicates with lookup-before-create logic
Check whether a record already exists before creating a new one in the destination system.
05
Use JavaScript to normalize dates, phone numbers, tags, and statuses
Clean and standardize values before mapping them into downstream fields.
06
Store execution logs for debugging
Keep a trace of what happened in every run so production issues are easier to inspect.
07
Route failed runs to email or a database
Notify the team or save failures for follow-up when a run cannot complete successfully.
08
Manually rerun failed executions
Replay a failed run after the issue is fixed without rebuilding the scenario from scratch.
Example payload
See what the workflow receives and returns
Show one real event and one real result so technical users can understand the payload shape before they connect accounts or customize the scenario.
Source event
JSON{"event": "client_added","client": {"id": "client_123","firstName": "Alex","lastName": "Smith","status": "active","tags": ["online-coaching"]}}Scenario result
JSON{"target": "wix_contact","operation": "upsert","dedupeBy": "email","status": "created"}Setup
Connect both apps in 3 steps
No developer needed. From credentials to live workflow in under 10 minutes.
01
Connect Azure DevOps
Authenticate Azure DevOps in Latenode's Credentials panel. You'll need access to your Azure DevOps account and permissions to create connections.
02
Connect Databricks
Add Databricks credentials (OAuth or API key, depending on the app). Latenode stores credentials securely and never saves your passwords.
03
Build and go live
Pick a trigger and an action, test with real data, then toggle your workflow to Live — done.
Build your Azure DevOps + Databricks automation
Choose a trigger and an action to build your workflow.
When this happens in Azure DevOps...
...do this in Databricks
Or
Describe your automation — press Build to open it in the editor.
Yes! Latenode provides a native integration between Azure DevOps and Databricks. You can connect them in minutes using our visual workflow builder — no coding required.
Use cases
Explore each app
Start from either hub, then mix triggers and actions with the rest of your stack.
About Azure DevOps
Azure DevOps is a comprehensive development platform that offers integrated tools for planning, developing, testing, and delivering high-quality software. With features like Azure Boards for agile project management, Azure Repos for version control, Azure Pipelines for CI/CD automation, and Azure Test Plans for manual and exploratory testing, Azure DevOps streamlines workflows and enhances collaboration across teams. Its cloud-based services ensure scalability and flexibility, enabling organizations to efficiently manage their software development lifecycle from ideation to deployment.
Learn moreAbout Databricks
Databricks is a unified data analytics platform that combines data engineering, data science, and machine learning into a single collaborative workspace, enabling teams to easily process large volumes of data and build data-driven applications. With its powerful Apache Spark engine, it supports real-time data processing and advanced analytics at scale, facilitating seamless integration with various data sources. Databricks empowers organizations to accelerate their analytical workflows, optimize resources, and derive actionable insights through its interactive notebooks and automated machine learning capabilities.
Learn moreStart automating Azure DevOps + Databricks today
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