How to Access Live Splunk Data in Power Automate Desktop via ODBC



The CData ODBC Driver for Splunk enables you to integrate Splunk data into workflows built using Microsoft Power Automate Desktop.

The CData ODBC Driver for Splunk enables you to access live Splunk data in workflow automation tools like Power Automate. This article shows how to integrate Splunk data into a simple workflow, moving Splunk data into a CSV file.

Through optimized data processing, CData ODBC Drivers offer unmatched performance for interacting with live Splunk data in Microsoft Power Automate. When you issue complex SQL queries from Power Automate to Splunk, the driver pushes supported SQL operations, like filters and aggregations, directly to Splunk and utilizes the embedded SQL engine to process unsupported operations client-side (e.g. SQL functions and JOIN operations).

Connect to Splunk as an ODBC Data Source

If you have not already, first specify connection properties in an ODBC DSN (data source name). This is the last step of the driver installation. You can use the Microsoft ODBC Data Source Administrator to create and configure ODBC DSNs.

To authenticate requests, set the User, Password, and URL properties to valid Splunk credentials. The port on which the requests are made to Splunk is port 8089.

The data provider uses plain-text authentication by default, since the data provider attempts to negotiate TLS/SSL with the server.

If you need to manually configure TLS/SSL, see Getting Started -> Advanced Settings in the data provider help documentation.

When you configure the DSN, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing workflows.

Integrate Splunk Data into Power Automate Workflows

After configuring the DSN for Splunk, you are ready to integrate Splunk data into your Power Automate workflows. Open Microsoft Power Automate, add a new flow, and name the flow.

In the flow editor, you can add the actions to connect to Splunk, query Splunk using SQL, and write the query results to a CSV document.

Add an Open SQL Connection Action

Add an "Open SQL connection" action (Actions -> Database) and configure the properties.

  • Connection string: DSN=CData Splunk Source

After configuring the action, click Save.

Add an Execute SQL Statement Action

Add an "Execute SQL statement" action (Actions -> Database) and configure the properties.

  • Get connection by: SQL connection variable
  • SQL connection: %SQLConnection% (the variable from the "Open SQL connection" action above)
  • SQL statement: SELECT * FROM DataModels

After configuring the action, click Save.

Add a Write to CSV File Action

Add a "Write to CSV file" action (Actions -> File) and configure the properties.

  • Variable to write to: %QueryResult% (the variable from the "Execute SQL statement" action above)
  • File path: set to a file on disk
  • Configure Advanced settings as needed.

After configuring the action, click Save.

Add a Close SQL Connection Action

Add a "Close SQL connection" action (Actions -> Database) and configure the properties.

  • SQL Connection: %SQLConnection% (the variable from the "Open SQL connection" action above)

After configuring the action, click Save.

Save & Run the Flow

Once you have configured all the actions for the flow, click the disk icon to save the flow. Click the play icon to run the flow.

Now you have a workflow to move Splunk data into a CSV file.

With the CData ODBC Driver for Splunk, you get live connectivity to Splunk data within your Microsoft Power Automate workflows.

Related Power Automate Articles

This article walks through using the CData ODBC Driver for Splunk with Power Automate Desktop. Check out our other articles for more ways to work with Power Automate (Desktop & Online):

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Splunk Icon Splunk ODBC Driver

The Splunk ODBC Driver is a powerful tool that allows you to connect with live Splunk, directly from any applications that support ODBC connectivity.

Access Splunk like you would a database - read, write, and update Datamodels, Datasets, SearchJobs, etc. through a standard ODBC Driver interface.