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Connect to Google Vertex AI

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Connect to Google Vertex AI

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This page provides step-by-step instructions for setting up a Google Vertex AI connector for the first time. This connector type enables you to leverage Vertex AI’s large language models (LLMs) within Elastic Security. You’ll first need to enable Vertex AI, then generate an API key, and finally configure the connector in your Elastic Security project.

Before continuing, you should have an active project in one of Google Vertex AI’s supported regions.

Enable the Vertex AI API
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  1. Log in to the GCP console and navigate to Vertex AI → Vertex AI Studio → Overview.
  2. If you’re new to Vertex AI, the Get started with Vertex AI Studio popup appears. Click Vertex AI API, then click ENABLE.

The following video demonstrates these steps.

For more information about enabling the Vertex AI API, refer to Google’s documentation.

Create a Vertex AI service account
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  1. In the GCP console, navigate to APIs & Services → Library.
  2. Search for Vertex AI API, select it, and click MANAGE.
  3. In the left menu, navigate to Credentials then click + CREATE CREDENTIALS and select Service account.
  4. Name the new service account, then click CREATE AND CONTINUE.
  5. Under Select a role, select Vertex AI User, then click CONTINUE.
  6. Click Done.

The following video demonstrates these steps.

Generate an API key
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  1. Return to Vertex AI’s Credentials menu and click Manage service accounts.
  2. Search for the service account you just created, select it, then click the link that appears under Email.
  3. Go to the KEYS tab, click ADD KEY, then select Create new key.
  4. Select JSON, then click CREATE to download the key. Keep it somewhere secure.

The following video demonstrates these steps.

Configure the Google Gemini connector
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Finally, configure the connector in Kibana:

  1. Log in to Kibana.
  2. Find Connectors in the navigation menu or use the global search field. Then click Create Connector, and select Google Gemini.
  3. Name your connector to help keep track of the model version you are using.
  4. Under URL, enter the URL for your region.
  5. Enter your GCP Region and GCP Project ID.
  6. Under Default model, specify either gemini-1.5.pro or gemini-1.5-flash. Learn more about the models.
  7. Under Authentication, enter your API key.
  8. Click Save.

The following video demonstrates these steps.

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