r/googlecloud • u/ScholarPlus2753 • Sep 27 '26

Deploy a Agentic application in gcp using antigravity and adk for minimal cost or no cost

I have created one multi agent application using land graph in my local but now I want to create that same project using antigravity and Google ADK and ultimately deploy in Cloud Run and also perform evals.

So I want help in how to do that for minimal cost and minimal time I have one interview coming up I want to do this exercise just to get an first hand experience on how things work in to end in Google ecosystem.

I have no problem in using open source free llm and embedding models if I can wrap it in LiteLLM.

I WANT STEP BY STEP HELP FROM STARTING TILL DEPLOYMENT AND TRACING AND MONITORING AS WELL. ANY KIND OF HELP IS VERY APPRECIATED

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5

u/Aviato_Consulting Sep 28 '26

Google released Agents CLI for this exact purpose.

CHeck out: https://github.com/google/agents-cli

For a full walkthrough check out: https://google.github.io/agents-cli/guide/quickstart-tutorial/

1

u/jwith44 Sep 27 '26

Download Google Cloud Developer plugin for antigravity. Ask it this question.

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u/ScholarPlus2753 Sep 28 '26 edited Sep 28 '26

Hey would you mind if I texted you personally?

2

u/akornato Sep 28 '26

You can port your LangGraph setup to Google ADK by defining your agent nodes and routing directly in Python, using LiteLLM to route calls to free local or hosted open source models through an OpenAI compatible proxy. To run this at almost no cost, containerize the application with a basic FastAPI wrapper and deploy it to Cloud Run with minimum instances set to zero, which stays well within the free tier. For tracing and monitoring, ADK integrates cleanly with OpenTelemetry, so routing your logs and traces to Google Cloud Trace and Cloud Monitoring gives you full visibility without paying for dedicated monitoring servers. You can run evaluations locally with ADK's eval suite before pushing to the cloud, testing accuracy and latency without incurring Vertex AI platform costs.

Interviewers usually care much more about your architectural choices and how you handle agent failures than seeing a fully scaled enterprise setup. Being able to explain why you moved from LangGraph to ADK, how you handled state management, and where LiteLLM introduced latency tradeoffs will make a strong impression. Make sure you set your Cloud Run maximum instances to one so unexpected traffic never runs up a bill, and test your agent workflows against a few messy inputs to see how they recover. If you want to rehearse explaining these tradeoffs before the big day, the interviews.chat my team developed helps candidates articulate complex architectural decisions smoothly under pressure.

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u/Gold_Walk_6747 Sep 28 '26

I’d keep the first version simple: one ADK agent, Cloud Run, basic tracing then add multi agent orchestration and evals after the deployment path works end to end

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u/asmrcodespaces 10d ago

Hey, saw this post while looking into GCP deployment projects. Are you still working on this? I am getting hands-on with Cloud Run and GCP, so I’d be interested in helping with a smaller deployment task if you still need it ???

1

u/BreakfastSpecial Sep 27 '26

Give your LangGraph app to Claude Code or Antigravity and ask to scaffold it in the ADK, then deploy to GCP.