Confluence and Databricks Integration

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Sync Databricks analysis results to Confluence for collaborative documentation. Latenode's visual editor simplifies connecting these tools, adding custom JavaScript logic and scaling the automation affordably based on execution time.

Confluence + Databricks integration

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Automate your workflow

Swap Apps

Confluence

Databricks

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Confluence and Databricks

Create a New Scenario to Connect Confluence and Databricks

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Confluence, triggered by another scenario, or executed manually (for testing purposes). In most cases, Confluence or Databricks will be your first step. To do this, click "Choose an app," find Confluence or Databricks, and select the appropriate trigger to start the scenario.

Add the Confluence Node

Select the Confluence node from the app selection panel on the right.

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Configure the Confluence

Click on the Confluence node to configure it. You can modify the Confluence URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Connect Confluence

Sign In

Run node once

Add the Databricks Node

Next, click the plus (+) icon on the Confluence node, select Databricks from the list of available apps, and choose the action you need from the list of nodes within Databricks.

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Authenticate Databricks

Now, click the Databricks node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Databricks settings. Authentication allows you to use Databricks through Latenode.

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Connect Databricks

Sign In

Run node once

Configure the Confluence and Databricks Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Select an action *

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The action ID

Run node once

Set Up the Confluence and Databricks Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Confluence, Databricks, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Confluence and Databricks integration works as expected. Depending on your setup, data should flow between Confluence and Databricks (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Confluence and Databricks

Databricks + Confluence + Slack: When a Databricks job run is triggered, this automation monitors its status. Upon completion, it retrieves related documentation from Confluence using a search query and sends a message to a designated Slack channel with links to the documentation.

Databricks + Confluence + Jira: If a Databricks job fails, the automation searches Confluence for related documentation. It then creates a Jira issue, linking to the relevant documentation to facilitate debugging and resolution.

Confluence and Databricks integration alternatives

About Confluence

Automate Confluence tasks in Latenode: create pages, update content, or trigger workflows when pages change. Connect Confluence to other apps (like Jira or Slack) for streamlined project updates and notifications. Use Latenode’s visual editor and JS node for custom logic and efficient information sharing across teams.

About Databricks

Use Databricks inside Latenode to automate data processing pipelines. Trigger Databricks jobs based on events, then route insights directly into your workflows for reporting or actions. Streamline big data tasks with visual flows, custom JavaScript, and Latenode's scalable execution engine.

See how Latenode works

FAQ Confluence and Databricks

How can I connect my Confluence account to Databricks using Latenode?

To connect your Confluence account to Databricks on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Confluence and click on "Connect".
  • Authenticate your Confluence and Databricks accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically update Confluence pages with Databricks analysis?

Yes, you can! Latenode enables automated updates, ensuring your Confluence documentation reflects the latest Databricks data insights. Enjoy real-time reporting and eliminate manual updates.

What types of tasks can I perform by integrating Confluence with Databricks?

Integrating Confluence with Databricks allows you to perform various tasks, including:

  • Automatically generating Confluence reports from Databricks query results.
  • Creating Confluence pages with insights derived from Databricks notebooks.
  • Updating Confluence tables with processed data from Databricks clusters.
  • Triggering Databricks jobs when Confluence pages are updated.
  • Archiving Confluence content to Databricks for long-term analysis.

Can I trigger Databricks workflows from Confluence page updates?

Yes! Latenode allows triggering Databricks jobs from Confluence edits, making data workflows reactive and efficient. Integrate no-code blocks, JavaScript, and AI for advanced behavior.

Are there any limitations to the Confluence and Databricks integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Large data transfers may be subject to API rate limits of both platforms.
  • Complex Databricks notebook outputs might require custom parsing logic.
  • Real-time synchronization depends on the polling frequency set within Latenode.

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