Deploying an AI Agent

AI agents are intelligent software programs that can perform tasks, answer questions, or make decisions based on the data and instructions they are given. After building an AI agent, the next crucial step is deployment. Deployment allows your AI agent to be used by others—whether inside a company, on a website, or integrated into other systems.

How to Deploy an AI Agent?

• Build and test your AI agent using tools like the Agent Development Kit (ADK).
• Prepare your deployment environment by choosing a hosting solution.
• Package your agent and ensure it meets the technical requirements of your chosen platform.
• Deploy the agent so it can respond to user requests reliably and at scale.
• Monitor and maintain the deployed agent to ensure performance and uptime.

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.

Different Deployment Options

Some of the options are as follows:

Agent Engine in Vertex AI

This is a managed service by Google Cloud that makes it easy to deploy, host, and scale AI agents. It’s fully integrated with other Google AI tools and is suitable for production-ready AI deployments.

Cloud Run

Cloud Run is a serverless platform that allows you to deploy containerized AI agents. It automatically scales depending on traffic and only charges when your code is running. It is a fully managed platform that enables you to run your code directly on top of Google’s infrastructure.

Google Kubernetes Engine (GKE)

GKE is a powerful container orchestration platform that allows you to run your AI agents in Kubernetes clusters. It offers flexibility and control, ideal for complex or enterprise-grade deployments.