# Deploying Your Agent

Once you've built and tested your agent using ADK,
the next step is to deploy it so it can be accessed, queried, and used in
production or integrated with other applications. Deployment moves your agent
from your local development machine to a scalable and reliable environment.

<img src="../assets/deploy-agent.png" alt="Deploying your agent">

## Deployment Options

Your ADK agent can be deployed to a range of different environments based
on your needs for production readiness or custom flexibility:

### Agent Runtime on Agent Platform

[Agent Runtime](agent-runtime/index.md) is a fully managed auto-scaling service on Google Cloud
specifically designed for deploying, managing, and scaling AI agents built with
frameworks such as ADK.

Learn more about [deploying your agent to Agent Runtime](agent-runtime/index.md).

### Cloud Run

[Cloud Run](https://cloud.google.com/run) is a managed auto-scaling compute platform on
Google Cloud that enables you to run your agent as a container-based
application.

Learn more about [deploying your agent to Cloud Run](cloud-run.md).

### Google Kubernetes Engine (GKE)

[Google Kubernetes Engine (GKE)](https://cloud.google.com/kubernetes-engine) is a managed
Kubernetes service of Google Cloud that allows you to run your agent in a containerized
environment. GKE is a good option if you need more control over the deployment as well as
for running Open Models.

Learn more about [deploying your agent to GKE](gke.md).

### Other Container-friendly Infrastructure

You can manually package your Agent into a container image and then run it in
any environment that supports container images.  For example you can run it
locally in Docker or Podman. This is a good option if you prefer to run offline
or disconnected, or otherwise in a system that has no connection to Google
Cloud.

Follow the instructions for [deploying your agent to Cloud Run](cloud-run.md#deployment-commands).
In the "Deployment Commands" section for gcloud CLI, you will find an example FastAPI entry point and 
Dockerfile.
