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This guide walks you through hosting a Swarms agent on Google Cloud Run — a fully managed container platform that auto-scales from zero. The setup uses a slim Docker image, an api/api.py Flask endpoint, and gcloud for deployment.

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Project structure

.
├── Dockerfile
├── requirements.txt
└── api/
    └── api.py

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Step 1: Prerequisites

  1. Google Cloud account — sign in at console.cloud.google.com and enable billing on a project.
  2. gcloud SDK — install via the official guide.
  3. Docker — install via the Docker docs.
  4. Project — create a new Google Cloud project and note the Project ID.
  5. APIs — enable the following in the API Library:
    • Cloud Run API
    • Cloud Build API
    • Artifact Registry API

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Step 2: Build the agent

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api/api.py

from flask import Flask, request, jsonify
from swarms import Agent

app = Flask(__name__)

agent = Agent(
    agent_name="Stock-Analysis-Agent",
    model_name="gpt-5.4",
    max_loops="auto",
    interactive=True,
    streaming_on=True,
)


@app.route("/run-agent", methods=["POST"])
def run_agent():
    data = request.json
    task = data.get("task", "")
    result = agent.run(task)
    return jsonify({"result": result})


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=8080)

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requirements.txt

flask
swarms

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Dockerfile

FROM python:3.10-slim
WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY api/ ./api/

EXPOSE 8080
CMD ["python", "api/api.py"]
Cloud Run sends traffic to port 8080 by default — keep that as the listening port.

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Step 3: Authenticate

gcloud auth login
gcloud config set project [PROJECT_ID]

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Step 4: Push the image to Artifact Registry

# 1. Create the registry
gcloud artifacts repositories create my-repo \
    --repository-format=Docker \
    --location=us-central1

# 2. Authenticate Docker against the registry
gcloud auth configure-docker us-central1-docker.pkg.dev

# 3. Build and tag the image
docker build -t us-central1-docker.pkg.dev/[PROJECT_ID]/my-repo/my-image .

# 4. Push it
docker push us-central1-docker.pkg.dev/[PROJECT_ID]/my-repo/my-image

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Step 5: Deploy to Cloud Run

gcloud run deploy my-agent-service \
    --image us-central1-docker.pkg.dev/[PROJECT_ID]/my-repo/my-image \
    --platform managed \
    --region us-central1 \
    --allow-unauthenticated
--allow-unauthenticated makes the service publicly reachable. Drop it to require IAM-authenticated calls.

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Step 6: Test the deployment

Cloud Run prints a URL after deploy. Hit the endpoint: 
curl -X POST [CLOUD_RUN_URL]/run-agent \
    -H "Content-Type: application/json" \
    -d '{"task": "Summarise the latest performance of AAPL"}'

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Step 7: Update the service

Iterating is just rebuild → push → redeploy: 
docker build -t us-central1-docker.pkg.dev/[PROJECT_ID]/my-repo/my-image .
docker push us-central1-docker.pkg.dev/[PROJECT_ID]/my-repo/my-image
gcloud run deploy my-agent-service \
    --image us-central1-docker.pkg.dev/[PROJECT_ID]/my-repo/my-image

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Troubleshooting

  • Permission errors — your account needs the Cloud Run Admin and Artifact Registry Reader roles.
  • Port issues — Cloud Run expects port 8080. Make sure your Flask app binds to it.
  • Logs: 
    gcloud logs read --project [PROJECT_ID]
Source: docs/swarms_cloud/cloud_run.md

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See also