How do developers transition from Google Gemini AI Studio prototypes to Vertex AI for production deployment?

Question

Accepted Answer

## Overview

Developers transition by moving from a free prototyping environment to a fully-managed, enterprise-grade MLOps platform.

## Key Features

Once on Vertex AI, developers gain access to Model Registry, Pipelines, Monitoring, and Provisioned Throughput.

## Technical Specifications

AI Studio uses the global generativelanguage.googleapis.com endpoint. Vertex AI uses regional endpoints.

## How It Works

The workflow involves exporting prompts, moving data to GCS, updating authentication to service accounts, and configuring the Vertex AI SDK.

## Use Cases

## Limitations and Requirements

Common pitfalls include failing to update API endpoints, misconfiguring IAM permissions, and model version availability.

## Comparison to Alternatives

## Summary

In summary, the transition is a deliberate architectural shift from an unmanaged sandbox to a fully governed production system.

Google Gemini