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# 10 questions for your startup developers

**[Google Cloud](https://daily.dev/sources/gcp)** · 21 min read · 0 upvotes · 0 comments

## Summary

A practical guide for AI startups covers ten decisions that determine whether a prototype survives the move to production on Google Cloud. Topics include choosing between Google AI Studio and Gemini Enterprise Agent Platform (formerly Vertex AI), setting up IAM and service accounts without becoming a cloud admin, authenticating safely with Application Default Credentials instead of raw API keys, and knowing when to migrate off an API key model. It also covers handling HTTP 429 errors via regional endpoints, retry/backoff, and monitoring; choosing between Standard PayGo, Priority PayGo, and Provisioned Throughput; shifting eligible workloads to batch prediction; enforcing spend caps and billing kill switches; storing secrets in Secret Manager; and securing autonomous agents with identity, sandboxing, prompt filtering, and behavioral monitoring.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cloud.google.com/blog/topics/developers-practitioners/10-questions-for-your-startup-developers>

## Questions this post answers

### How can I stop Vertex AI billing budgets from just sending alert emails and actually enforce a hard spend cap?

Cloud Billing budgets can now enforce spending limits instead of only notifying, through a spend cap budget feature that entered Preview in July. When usage costs cross 100% of the budget on an eligible project and service, such as Vertex AI (Gemini Enterprise Agent Platform), Cloud Run, or Cloud Run functions, Google Cloud pauses the service until it is manually lifted; alerts still fire at 50% and 80% first.

_Startups budgeting for AI usage can track billing and cost-control changes like this one on daily.dev._

### Why am I getting HTTP 429 Too Many Requests errors on Vertex AI even though I'm not near any quota I set myself?

429 errors under Standard PayGo usually mean you hit the Dynamic Shared Quota ceiling for your project's tier, or you're calling the global endpoint during a worldwide demand spike. Pinning requests to a specific regional endpoint like us-central1 instead of the default global routing, and adding exponential backoff with jitter via the google-genai SDK's built-in retry options, typically resolves it faster than filing a quota-increase request.

_Developers debugging rate-limit errors in production can follow Vertex AI capacity issues like this on daily.dev._

### What's the difference between Standard PayGo, Priority PayGo, and Provisioned Throughput on Vertex AI, and which should I use?

Standard PayGo charges per token from a shared pool with no guarantees and is cheapest; Priority PayGo charges a premium per token to jump the queue during contention; Provisioned Throughput requires prepaying for reserved capacity that you pay for whether used or not. The recommended sequence is running on Standard PayGo for several weeks to measure real request shape, enabling Priority PayGo only when facing 429 storms, then buying Provisioned Throughput once baseline traffic is predictable, letting overflow spill to PayGo.

_Teams comparing AI inference pricing tiers can weigh Vertex AI consumption models like these on daily.dev._

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---

Tags: [#gcp](https://daily.dev/tags/gcp), [#iam](https://daily.dev/tags/iam), [#vertex-ai](https://daily.dev/tags/vertex-ai)

[View this post on daily.dev](https://daily.dev/posts/10-questions-for-your-startup-developers-skgdx36bf)

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