Skip to main content

Buyer guide

Agent Platform Production Playbook

A checklist for taking a Gemini or Claude workload on Google Cloud from prototype to live traffic: models and endpoints, throughput, data settings and spend controls.

Reading time
2 min read
Sources
12 cited
In this piece
Gemini Enterprise Agent Platform−27 Negative

Evaluate models through the endpoint you will use in production, confirm the throughput tier or reserve capacity before launch, and label every request before the first production job. Each step cites Google Cloud documentation and public accounts from teams running Agent Platform.

When you need this

  • A feature or agent built on Gemini or Claude is moving from an AI Studio key or a prototype project to production traffic on Google Cloud.
  • The team is choosing between Gemini, Claude and open models in Model Garden for the same workload.
  • A launch date is fixed, and nobody has checked which throughput tier the organization's spend has reached.

Evaluation criteria

  1. Model choice: evaluations on your task

    Which Model Garden model passes your own test set at the lowest cost per completed task?

    Look forRun the same prompts on two or three models through the production endpoint. Slack matches models to features across clouds and reports about 10% better quality on complex reasoning and about 67% lower latency on low-token work. Track malformed function calls on Gemini: developers on Google's forum reported MALFORMED_FUNCTION_CALL far more often on Vertex than on the Developer API in 2025.

  2. Endpoint: global, multi-region or regional

    Does the workload have to stay in the US or the EU?

    Look forUse the global endpoint when residency allows: it carries the list price and serves from any region with capacity. The us and eu multi-region endpoints and named regional endpoints cost 10% more for Gemini 3 and later models.

  3. Capacity: throughput tier or Provisioned Throughput

    Will 30-day spend put the organization in a tier that covers launch traffic?

    Look forTier 1 covers 500,000 tokens per minute for Gemini Pro and Argon models. A new organization moving from AI Studio can hit persistent 429 errors, as one agent app operator did in March 2026. Reserve GSUs for steady traffic, and add retries with backoff for the rest.

  4. Cost control: labels and grounding

    Can every dollar on the bill be traced to a service and a feature?

    Look forAttach labels to requests and set budgets per project. Count grounding requests separately, because they bill per request on top of tokens. A startup's overnight job produced a C$71K bill after credits ran out, with charges arriving for days.

  5. Governance: data settings

    Is zero data retention set where the workload needs it?

    Look forOpt out of abuse-monitoring prompt logging and turn off caching for zero data retention, and check the security controls matrix for the features you use.

Questions to ask vendors

  1. Which throughput tier has our organization reached, and what traffic does it cover per model family?
  2. Which Claude features on our roadmap does Google-managed Claude lack?
  3. Who owns each project's budget alert, and which labels does each service attach?
  4. Which promotional prices end before our first full quarter in production?

Red flags

  • A launch plan that assumes AI Studio's capacity carries over to a new Google Cloud organization.
  • Many services sharing one project with no request labels.
  • Grounding left on by default with no per-request budget.
  • Budgets set on the promotional Gemini 4 Argon price.

Products in this piece

Sources

Official documentation
6
Public source
6
  1. Google Cloud: Agent Platform generative AI pricingOfficial documentationcloud.google.com
  2. Agent Platform documentation: Standard PayGoOfficial documentationdocs.cloud.google.com
  3. Agent Platform documentation: Provisioned ThroughputOfficial documentationdocs.cloud.google.com
  4. Agent Platform documentation: Deployment and endpoint locationsOfficial documentationdocs.cloud.google.com
  5. Agent Platform documentation: Agent Platform and zero data retentionOfficial documentationdocs.cloud.google.com
  6. Agent Platform documentation: Security controlsOfficial documentationdocs.cloud.google.com
  7. Engineering at Slack: Slack AI, the path to multi-cloud (May 28, 2026)Public sourceslack.engineering
  8. Google AI Developers Forum: MALFORMED_FUNCTION_CALL happens too frequently with Vertex AI (Jul 12, 2025)Public sourcediscuss.ai.google.dev
  9. Google AI Developers Forum: Persistent 429 RESOURCE_EXHAUSTED on Vertex AI after migrating from AI Studio (Mar 17, 2026)Public sourcediscuss.ai.google.dev
  10. r/googlecloud: Got a C$71K Google Cloud bill overnight (Oct 18, 2026)Public sourcereddit.com
  11. junhee916 on DEV: Vertex AI grounding cost gap on a solo VM (Jun 7, 2026)Public sourcedev.to
  12. karthidec on DEV: Postmortem, the Tuesday our AI bill had no owner (Oct 25, 2026)Public sourcedev.to

Keep reading

  1. Buyer guideChoosing Between an AI Studio Key and Google Cloud's Agent PlatformGemini Developer API and Enterprise Agent Platform compared on setup, billing, limits, regions, and data terms.
  2. Buyer guideAgent Platform Data, Endpoints & Residency ChecklistWhich endpoint keeps processing in the US or EU, what zero data retention requires, and which controls cover which models.
  3. ResearchAgent Platform After Vertex AI: What Changed for Buyers in 2026What the April 2026 rename moved, how throughput tiers and promotions set the bill, and what public accounts report about quotas, reliability and billing.
Read the research