Google AI Platform

Connect your Google AI Platform-powered application to Latitude Telemetry for feature-level observability and evaluations.

Overview

This guide shows you how to integrate Latitude Telemetry into an existing application that uses the official Google AI Platform SDK.

After completing these steps:

• Every Google AI Platform call (e.g. predict) can be captured as a log in Latitude.
• Logs are grouped under a prompt, identified by a path, inside a Latitude project.
• You can inspect inputs/outputs, measure latency, and debug Google AI Platform-powered features from the Latitude dashboard.

You’ll keep calling Google AI Platform exactly as you do today — Telemetry simply observes and enriches those calls.

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Requirements

Before you start, make sure you have:

• A Latitude account and API key
• A Latitude project ID
• A Node.js-based project that uses the Google AI Platform SDK

That’s it — prompts do not need to be created ahead of time.

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Steps

1. Install requirements

   Add the Latitude Telemetry package to your project:

   npm

   npm add @latitude-data/telemetry
   
2. Initialize Latitude Telemetry

   Create a single LatitudeTelemetry instance when your app starts

   You must pass the Google AI Platform SDK so Telemetry can instrument it.

   telemetry.ts

   import { LatitudeTelemetry } from '@latitude-data/telemetry'
   import * as AIPlatform from '@google-cloud/aiplatform'
   
   export const telemetry = new LatitudeTelemetry(
     process.env.LATITUDE_API_KEY,
     {
       instrumentations: {
         aiplatform: AIPlatform, // This enables automatic tracing for the Google AI Platform SDK
       },
     }
   )
   

   The Telemetry instance should only be created once. Any Google AI Platform client instantiated after this will be automatically traced.

3. Wrap your Google AI Platform-powered feature

   Wrap the code that calls Google AI Platform using telemetry.capture.

   import { telemetry } from './telemetry'
   import { PredictionServiceClient } from '@google-cloud/aiplatform'
   
   export async function generateSupportReply(input: string) {
     return telemetry.capture(
       {
         projectId: 123, // The ID of your project in Latitude
         path: 'generate-support-reply', // Add a path to identify this prompt in Latitude
       },
       async () => {
   
         // Your regular LLM-powered feature code here
         const client = new PredictionServiceClient({ ... });
         const response = await client.predict({ ... })
   
         // You can return anything you want — the value is passed through unchanged
         return response;
       }
     )
   }
   

   The path:

   • Identifies the prompt in Latitude
   • Can be new or existing
   • Should not contain spaces or special characters (use letters, numbers, - _ / .)

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Seeing your logs in Latitude

Once your feature is wrapped, logs will appear automatically.

1. Open the prompt in your Latitude dashboard (identified by path)
2. Go to the Traces section
3. Each execution will show:
   • Input and output messages
   • Model and token usage
   • Latency and errors
   • One trace per feature invocation

Each Google AI Platform call appears as a child span under the captured prompt execution, giving you a full, end-to-end view of what happened.

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That’s it

No changes to your Google AI Platform calls, no special return values, and no extra plumbing — just wrap the feature you want to observe.