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Mofi Rahman
39 lines
1.4 KiB
Markdown
39 lines
1.4 KiB
Markdown
# Deploying Your Agent
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Once you've built and tested your agent using ADK,
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the next step is to deploy it so it can be accessed, queried, and used in
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production or integrated with other applications. Deployment moves your agent
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from your local development machine to a scalable and reliable environment.
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<img src="../assets/deploy-agent.png" alt="Deploying your agent">
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## Deployment Options
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Your ADK agent can be deployed to a range of different environments based
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on your needs for production readiness or custom flexibility:
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### Agent Engine in Vertex AI
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[Agent Engine](agent-engine.md) is a fully managed auto-scaling service on Google Cloud
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specifically designed for deploying, managing, and scaling AI agents built with
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frameworks such as ADK.
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Learn more about [deploying your agent to Vertex AI Agent Engine](agent-engine.md).
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### Cloud Run
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[Cloud Run](https://cloud.google.com/run) is a managed auto-scaling compute platform on
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Google Cloud that enables you to run your agent as a container-based
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application.
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Learn more about [deploying your agent to Cloud Run](cloud-run.md).
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### Google Kubernetes Engine (GKE)
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[Google Kubernetes Engine (GKE)](https://cloud.google.com/kubernetes-engine) is a managed
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Kubernetes service of Google Cloud that allows you to run your agent in a containerized
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environment. GKE is a good option if you need more control over the deployment as well as
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for running Open Models.
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Learn more about [deploying your agent to GKE](gke.md).
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