How do I trigger the validation process?

You can trigger the skill by asking Claude to 'validate deployment', 'check production readiness', or perform a 'security audit vertex ai'.

What specifically does this skill validate in Vertex AI?

It validates security configurations (IAM, VPC), monitoring (dashboards, alerting), performance (scaling, limits), and compliance (logs, data residency).

How is the production readiness score calculated?

The skill generates a weighted score from 0-100% based on the criticality of passed checks across security, performance, and compliance categories.

Does this skill require administrative write access to my GCP project?

No, the skill uses read-only tools like Read, Grep, Glob, and Bash to analyze configurations and provide recommendations without altering your infrastructure.

Vertex AI Production Validator

Name: Vertex AI Production Validator
Author: BbgnsurfTech

byBbgnsurfTech

•

Security & Testing

Validates Vertex AI Agent Engine deployments for production readiness by auditing security, monitoring, performance, and compliance standards.

About

The Vertex AI Production Validator is a specialized skill designed to ensure Google Cloud AI deployments meet enterprise-grade requirements before going live. It automates the complex task of auditing Agent Engine configurations, checking for least-privilege IAM roles, VPC Service Controls, and robust monitoring setups. By generating a weighted readiness score (0-100%) and providing specific actionable recommendations, it helps developers mitigate security risks, optimize resource performance, and maintain strict compliance with data residency and privacy policies.

Key Features

Monitoring and observability verification for Cloud Monitoring and SLOs
Comprehensive security auditing including IAM roles and VPC Service Controls
Compliance validation for data residency and audit logging
Performance optimization checks for auto-scaling and resource limits
Automated production readiness scoring with weighted evaluation
1 GitHub stars

Use Cases

Pre-deployment security and compliance audits for Vertex AI Agents
Optimizing performance and resource allocation in GCP AI environments
Generating readiness reports for stakeholder approval before production launch

About

Key Features

Monitoring and observability verification for Cloud Monitoring and SLOs
Comprehensive security auditing including IAM roles and VPC Service Controls
Compliance validation for data residency and audit logging
Performance optimization checks for auto-scaling and resource limits
Automated production readiness scoring with weighted evaluation
1 GitHub stars

Use Cases

Pre-deployment security and compliance audits for Vertex AI Agents
Optimizing performance and resource allocation in GCP AI environments
Generating readiness reports for stakeholder approval before production launch