Google Vertex AI Integration for LLM Cost Tracker

Overview

Binadox LLM Cost Tracker provides comprehensive monitoring and cost analysis for your Google Vertex AI resources. This integration allows you to track usage patterns, monitor costs, analyze performance metrics, and optimize your AI spending across all Vertex AI models and deployments.

The LLM Cost Tracker automatically discovers your Vertex AI resources and provides detailed insights into:

Model predictions and API call volumes
Cost breakdown by model, endpoint, and region
Usage trends and performance patterns
Resource utilization metrics
Detailed billing analysis with cost allocation

Prerequisites

Before setting up the integration, ensure you have:

Google Cloud Project with Vertex AI enabled and active deployments
Project Owner or appropriate IAM roles to create service accounts
Google Cloud CLI installed (optional but recommended for setup)
Billing enabled on your Google Cloud project
Binadox account
Active Vertex AI usage for meaningful metrics and cost data

Authentication Method

This guide uses Service Account authentication, which is the recommended approach for production integrations. Service Account authentication provides:

Secure, JSON key-based authentication
Fine-grained permission control through IAM roles
Full access to Cloud Monitoring, Billing, and Vertex AI APIs
Cross-project monitoring capabilities
Automated credential management

Step 1: Create Google Cloud Service Account

Set Up Your Project Environment

First, configure your Google Cloud environment and set the target project. Open your terminal or Google Cloud Shell and set your project ID as an environment variable for easier management:

export PROJECT_ID="your-project-id"
gcloud config set project $PROJECT_ID

Create the Service Account

Create a dedicated service account for Binadox LLM Cost Tracker monitoring. This service account will be used exclusively for accessing Vertex AI metrics, billing data, and logs:

gcloud iam service-accounts create binadox-vertex-monitoring \
    --display-name="Binadox LLM Cost Tracker" \
    --description="Service account for monitoring Vertex AI usage and costs"

export SA_EMAIL="binadox-vertex-monitoring@${PROJECT_ID}.iam.gserviceaccount.com"

Step 2: Grant Required IAM Roles

The service account needs specific IAM roles to access Vertex AI monitoring data. Grant the following roles to enable comprehensive monitoring:

Core Monitoring Permissions

Grant the Monitoring Viewer role to read metrics and performance data from Cloud Monitoring:

gcloud projects add-iam-policy-binding $PROJECT_ID \
    --member="serviceAccount:${SA_EMAIL}" \
    --role="roles/monitoring.viewer"

Billing Access Permissions

Grant billing viewer access to retrieve cost and usage information:

gcloud projects add-iam-policy-binding $PROJECT_ID \
    --member="serviceAccount:${SA_EMAIL}" \
    --role="roles/billing.viewer"

Logging Access Permissions

Grant logging access to read detailed Vertex AI request logs and audit trails:

gcloud projects add-iam-policy-binding $PROJECT_ID \
    --member="serviceAccount:${SA_EMAIL}" \
    --role="roles/logging.viewer"

Vertex AI Access Permissions

Grant Vertex AI user permissions to access model and endpoint information:

gcloud projects add-iam-policy-binding $PROJECT_ID \
    --member="serviceAccount:${SA_EMAIL}" \
    --role="roles/aiplatform.user"

Service Usage Permissions

Grant service usage permissions for API access and quotas:

gcloud projects add-iam-policy-binding $PROJECT_ID \
    --member="serviceAccount:${SA_EMAIL}" \
    --role="roles/serviceusage.serviceUsageConsumer"

Step 3: Create and Secure Service Account Key

Generate the JSON Key File

Create a JSON key file for the service account. This file contains the credentials that Binadox will use to authenticate with Google Cloud APIs:

gcloud iam service-accounts keys create binadox-vertex-key.json \
    --iam-account=$SA_EMAIL

Secure the Key File

Set appropriate file permissions to protect the service account key:

chmod 600 binadox-vertex-key.json

Verify Key Structure

Verify that the key file was created correctly and contains the required fields:

cat binadox-vertex-key.json | jq .type
# Should output: "service_account"

The JSON key file should contain essential fields including type, project_id, private_key, client_email, and authentication URIs. Store this file securely as it provides access to your Google Cloud resources.

Step 4: Enable Required Google Cloud APIs

Enable APIs via Console

Navigate to the Google Cloud Console and enable the required APIs. Go to APIs & Services → Library and enable the following APIs:

Vertex AI API
Cloud Monitoring API
Cloud Billing API
Cloud Logging API
Cloud Resource Manager API

Enable APIs via CLI

Alternatively, enable all required APIs using the command line:

gcloud services enable \
    aiplatform.googleapis.com \
    monitoring.googleapis.com \
    cloudbilling.googleapis.com \
    logging.googleapis.com \
    cloudresourcemanager.googleapis.com \
    compute.googleapis.com

Verify that the APIs are enabled correctly:

gcloud services list --enabled | grep -E "(aiplatform|monitoring|billing|logging)"

Step 5: Configure LLM Cost Tracker in Binadox

1. Access LLM Cost Tracker:

Log into your Binadox dashboard
Navigate to LLM Cost Tracker section
Click Add New Integration

2. Select Google Vertex AI from the available providers.

3. Enter Connection Details.

Field	Value	Description
Connection Name	Vertex AI Production	Descriptive name for this integration
Project ID	your-project-id	Google Cloud project ID containing Vertex AI resources
Service Account JSON	Upload or paste JSON	Contents of the binadox-vertex-key.json file
Default Location	us-central1	Primary region for Vertex AI resources

Troubleshooting

Common Issues and Solutions

Issue	Symptoms	Solutions
Permission Denied	Connection test fails with 403 Forbidden or permission denied errors	Verify that all required IAM roles are properly assigned to the service account; Wait 5-10 minutes for IAM role changes to propagate across Google Cloud services; Check that the service account email address is correct and matches your project; Ensure that all required APIs are enabled in your Google Cloud project.
API Not Enabled	Integration fails with messages about disabled APIs	Enable the Vertex AI API: `gcloud services enable aiplatform.googleapis.com` ; Enable other required APIs using the CLI commands provided in Step 4; Verify API enablement in the Google Cloud Console under APIs & Services; Check that your project has billing enabled as some APIs require active billing.
No Vertex AI Resources Found	Integration succeeds but no models or endpoints are discovered	Verify that you have active Vertex AI deployments in your project; Check that resources exist in the specified location/region; Ensure the service account has `aiplatform.user` role permissions; Confirm that Vertex AI resources are in the same project as the service account.
Missing Cost Data	Usage metrics appear but billing information is unavailable	Verify that the service account has the `billing.viewer` role; Ensure billing is enabled on your Google Cloud project; Cost data may take 24-48 hours to appear for new usage; Check that Vertex AI usage has generated actual billable activity.
Incomplete Metrics Data	Some performance metrics are missing or inconsistent	Verify the `monitoring.viewer` role is assigned to the service account; Ensure Vertex AI models have active prediction traffic; Metrics may take 5-15 minutes to appear after model usage; Check that audit logging is enabled for detailed request metrics.

Validating Service Account Access

Test your service account configuration using the Google Cloud CLI:

# Authenticate with the service account
gcloud auth activate-service-account --key-file=binadox-vertex-key.json

# Test Vertex AI API access
gcloud ai endpoints list --region=us-central1

# Test monitoring API access
gcloud logging read "resource.type=aiplatform.googleapis.com/endpoint" --limit=5

# Test billing API access (if billing account permissions are available)
gcloud billing accounts list

Debug Service Account Permissions

Verify the assigned roles for your service account:

# List all IAM bindings for the service account
gcloud projects get-iam-policy $PROJECT_ID \
    --flatten="bindings[].members" \
    --filter="bindings.members:serviceAccount:${SA_EMAIL}"

# Test specific API permissions
curl -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    "https://aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/us-central1/endpoints"

Support and Resources

Binadox Support: Contact support through your Binadox dashboard for integration assistance
Google Vertex AI Documentation: Vertex AI User Guide
Cloud Monitoring: Cloud Monitoring API Documentation
Cloud Billing API: Billing API Reference

For additional assistance or feature requests related to LLM Cost Tracker, please reach out to the Binadox support team.