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joshyfruit
joshyfruit

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Host your first AI Agent on Agentcore

#ai #agents #aws

Exploring AgentCore: Effortless AI Agent Deployment with AWS Strands SDK

I had a good time exploring AgentCore and I see what AWS is trying to do: eliminate the second guessing on how to deploy your AI Agent. With the release of the Strands SDK, AWS has introduced a truly streamlined way to get agents running quickly. In this post, I’ll walk you through how I hosted my own agent on AgentCore, with everything from setup to cloud deployment.

Why AgentCore and Strands SDK?

AWS AgentCore Runtime solves a major pain-point for developers: secure, reliable, and scalable deployment of AI agents without wrangling cloud infrastructure details. The new Strands SDK tightly integrates with AgentCore, letting you focus on your agent logic while AWS handles scaling, session isolation, and production readiness.

Step-by-Step: Deploying Your Agent

Prerequisites:

  • AWS account and CLI configured (aws configure)
  • Python 3.10+, pip, Docker
  • Install the AgentCore toolkit and Strands SDK: 
pip install bedrock-agentcore bedrock-agentcore-starter-toolkit strands-agents
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Sample Agent (my_agent.py):

from bedrock_agentcore import BedrockAgentCoreApp
from strands import Agent

app = BedrockAgentCoreApp()
agent = Agent()

@app.entrypoint
def invoke(payload):
    user_message = payload.get("prompt", "Hello! How can I help you today?")
    result = agent(user_message)
    return {"result": result.message}

if __name__ == "__main__":
    app.run()
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Local Test (optional):

python my_agent.py
# In another terminal:
curl -X POST http://localhost:8080/invocations \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Hello!"}'
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Configure for Cloud Deployment:

agentcore configure --entrypoint my_agent.py
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Follow prompts for runtime options.

Deploy to AgentCore Runtime:

agentcore launch
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You’ll get an Agent ARN for your deployed agent.

Invoke the Deployed Agent:

agentcore invoke '{"prompt": "Tell me a joke"}'
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Architecture Diagram

Here’s a quick summary of the workflow:

Note: Local testing uses HTTP. Deployment and cloud invocation use AWS endpoints over HTTPS for secure communication.

My Takeaways

AgentCore Runtime and the Strands SDK make deploying AI agents on AWS simple and production-ready. From local prototyping to scalable cloud hosting, you skip the usual cloud headaches and focus on building features.

Let me know if you want a deeper dive into custom agent logic, more advanced deployment options, or troubleshooting advice!

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