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integrationGoogle Vertex AI node
HTTP Request
integrationRedis node

Google Vertex AI and Redis integration

Save yourself the work of writing custom integrations for Google Vertex AI and Redis and use n8n instead. Build adaptable and scalable AI, Development, and Data & Storage workflows that work with your technology stack. All within a building experience you will love.

How to connect Google Vertex AI and Redis

  • Step 1: Create a new workflow
  • Step 2: Add and configure nodes
  • Step 3: Connect
  • Step 4: Customize and extend your integration
  • Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Google Vertex AI and Redis integration: Create a new workflow and add the first step

Step 2: Add and configure Redis and Google Vertex AI nodes (using the HTTP Request node)

You can find the Redis node in the nodes panel and drag it onto your workflow canvas. To add the Google Vertex AI app to the workflow select the HTTP Request node and use the generic authentication method to make custom API calls to Google Vertex AI. Configure Google Vertex AI and Redis one by one: input data on the left, parameters in the middle, and output data on the right.

Redis and Google Vertex AI integration: Add and configure Redis and Google Vertex AI nodes

Step 3: Connect Redis and Google Vertex AI

A connection establishes a link between Redis and Google Vertex AI (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

Redis and Google Vertex AI integration: Connect Redis and Google Vertex AI

Step 4: Customize and extend your Redis and Google Vertex AI integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Redis and Google Vertex AI with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Redis and Google Vertex AI integration: Customize and extend your Redis and Google Vertex AI integration

Step 5: Test and activate your Google Vertex AI and Redis workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Google Vertex AI to Redis or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

Redis and Google Vertex AI integration: Test and activate your Redis and Google Vertex AI workflow

Build your own Google Vertex AI and Redis integration

Create custom Google Vertex AI and Redis workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Supported methods for Google Vertex AI

Delete
Get
Head
Options
Patch
Post
Put

Requires additional credentials set up

Use n8n’s HTTP Request node with a predefined or generic credential type to make custom API calls.

Redis supported actions

Delete
Delete a key from Redis
Get
Get the value of a key from Redis
Increment
Atomically increments a key by 1. Creates the key if it does not exist.
Info
Returns generic information about the Redis instance
Keys
Returns all the keys matching a pattern
Pop
Pop data from a redis list
Publish
Publish message to redis channel
Push
Push data to a redis list
Set
Set the value of a key in redis

Google Vertex AI and Redis integration details

integrationGoogle Vertex AI node
HTTP Request
Google Vertex AI

Google Vertex AI is a unified machine learning platform that enables developers to build, deploy, and manage models efficiently. It provides a wide range of tools and services, such as AutoML and datasets, to accelerate the deployment of AI solutions.

Use case

Save engineering resources

Reduce time spent on customer integrations, engineer faster POCs, keep your customer-specific functionality separate from product all without having to code.

Learn more

FAQs

  • Can Google Vertex AI connect with Redis?

  • Can I use Google Vertex AI’s API with n8n?

  • Can I use Redis’s API with n8n?

  • Is n8n secure for integrating Google Vertex AI and Redis?

  • How to get started with Google Vertex AI and Redis integration in n8n.io?

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Why use n8n to integrate Google Vertex AI with Redis

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Pause your workflow to wait for external events.

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Simple debugging

Your data is displayed alongside your settings, making edge cases easy to track down.

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