So far we’ve let other tools decide how the agent gets hosted — adk run locally, or the little deploy script that packages everything up for Agent Platform runtime. Both are handy, but sometimes you just want a plain container: one image you can run on your laptop today, and on Cloud Run, GKE, or Agent Platform runtime (in bring-your-own-container mode) tomorrow. In this part we’ll build that image, set up the Agent Platform resource the managed services need, and deploy the same artifact to each of those targets. Let’s build it.
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
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
More parts coming soon.