Agent Substrate can run stateful Google ADK agents across a shared pool of GKE worker Pods. After an agent responds, the harness can suspend its whole process—including its conversation, in-memory working state, and files—and Substrate can restore it on whichever compatible … Continue reading Running stateful ADK agents on Substrate and GKE
In The Agent Platform API contract I walked through the two routes a bring-your-own-container agent has to serve — /api/reasoning_engine and /api/stream_reasoning_engine — and the FastAPI wrapper I wrote to dispatch them onto an AdkApp. It worked, but it was 117 lines of plumbing … Continue reading Agent Platform BYOC without the wrapper: new in ADK 2.2
Agent Runtime can host a container with arbitrary HTTP endpoints. To use it through the Agent Platform Python SDK or the Google Cloud console playground — or through Gemini Enterprise’s native ADK integration — the container must also implement the operations those integrations … Continue reading The Agent Platform API contract: what your agent must expose, and why
With Agent Platform’s bring your own container (BYOC) deployment option, you need to serve the standard API contract yourself. In The Agent Platform API contract: what your agent must expose, and why, I covered why the contract exists and walked through the thirteen methods that … Continue reading Serving the Agent Platform API contract
So far we’ve run the trading agent two ways: locally with adk run, and deployed to Agent Platform runtime with a little Python script that packages the code and hosts it for us. Both are handy, but in each case something else is deciding how your agent gets hosted. Sometimes you … Continue reading Containerizing an ADK agent
The Trading agent we deployed earlier will automatically have session persistence when deployed on Agent Platform. You can test this by asking it a day later “What trades did you execute” from the same session that you executed the trades from. The full conversation history is … Continue reading Deterministic memories
To use Agent Platform services like Memory Bank, and Sessions from other environments, you need to first create a resource that is currently known as an “agent engine”. Note: if you are familiar with the Python ADK libraries, you can follow these instructions instead, to create … Continue reading Creating an Agent Platform resource identifier
Did you know that Agent Platform offers a leading memory bank service, that can be used even if you’re deploying your agentic workload to GKE or Cloud Run? Memory Bank is a fully managed service that in addition to being able to save specific memories you give it, can review the … Continue reading Other Services
ADK Agents will automatically have session persistence when deployed on Agent Platform. You can test this by asking follow up questions in the running sessions like “What trades did you execute?”. The full conversation history is preserved, even while the agent is suspended … Continue reading Agent memories with ADK
In my previous post, we created an agent with ADK and ran it locally. The next step is to deploy it to Agent Platform runtime. You can deploy to the runtime using a Python script that imports your agent, and configures the remote resource, and performs the deployment. This … Continue reading Deploy an ADK agent to Agent Platform Runtime
The Agent Development Kit (ADK) is Google’s open-source Python framework for building AI agents. You write the agent’s logic and the tools it can call, and ADK handles orchestrating everything — with evaluation and deployment built in too. I wanted a slightly more interesting app … Continue reading Building a stock-trading agent with ADK