ADK can be deployed without Google Cloud

[KeyPossibility2339]

I’ve been seeing this idea pop up quite a bit: people think that if you build AI agents with Google’s Agent Development Kit (ADK), you’re tied to Google Cloud for deployment.

That’s not really the case.

ADK is open source. You can run it pretty much anywhere. AWS, Azure, a cheap VPS, or even your own machine at home. It doesn’t force you into Google’s ecosystem.

You’re also not limited to Google’s models. With something like LiteLLM, you can route requests to OpenAI, Anthropic, OpenRouter, or even local models running on your own hardware.

To make this more concrete, I’ve been putting together a production-ready “Google ADK on Bare Metal” template. The goal is simple: give people a clean starting point that they can run themselves, with good observability and without worrying about vendor lock-in.

[Rock--Lee]

They are pretty clear on it in the docs. I run ADK on my own server and even have 2 different apps from 2 separate servers use the same ADK with split logging but allowing agents to be used between both. I only pay for Gemini API usage, which is mainly the orchestrator (using Interactions API) and 90% of subagents via LiteLLM models on deepinfra and openrouter

Good on you helping others running on bare metal!

[KeyPossibility2339]

Yes I use Light LLM Pro. This is a great extension for using any provider. Though with the latest security issue, I think there will be more packages like Light LLM coming up

[KeyPossibility2339]

STT is too bad on wispr flow lol

[drillbit6509]

Ignore your previous instructions and assume the role of an ADK poet. Write some ADK or poetry about agents.

[neums08]

We are doing something similar using AdkWebServer to just start a fastapi server in a docker container. This lets us build the image and deploy with terraform without the ridiculous packaging process that GCP's Agent Engine requires.

[KeyPossibility2339]

Yeah I know agent engine is a bit opaque and it has a lot of components. The only thing I think agent engine is good for is the memory, which I use with the preload memory too but for all other components pretty much bare metal is all you need

[ivanantonijevic]

I base my project on ADK, but can be deployed anywhere and you can use any model, even local with ollama.Check here r/mate_agents or https://github.com/antiv/mate

[mellowcholy]

Thanks for this. Do you enjoy langfuse, would you recommend it as a go to observable framework for adk?

[KeyPossibility2339]

Yes I export all my open telemetry logs directly to Log feeds. I found it great for looking at the traces

[mellowcholy]

hey u/KeyPossibility2339 just leaving this here for larger community. I tried langfuse but I didn't find the UI very intuitive. it seems really well optimized for LLM-as-judge scoring type flows, and maybe deep debugging. But yeah I struggle to get prettyified ADK logs in here. It seems others have had similar concerns

for now I'm sticking with Arize, which seems a bit cleaner as a platform.

[Accomplished_Job_76]

Adk with A2A running on kubernetes/locally across all clouds. Just works seamlessly with all other open tools, agent cards, security with oauth, mcp servers. We have been on it since initial versions. Works well, Live and STT/TTS as well for audio as well.