> ## Documentation Index
> Fetch the complete documentation index at: https://docs.swarms.world/llms.txt
> Use this file to discover all available pages before exploring further.

# Google Cloud Run

> Deploy a Swarms agent as a containerized REST API on Google Cloud Run with automatic scaling and managed infrastructure.

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.

## Project structure

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

## Step 1: Prerequisites

1. **Google Cloud account** — sign in at [console.cloud.google.com](https://console.cloud.google.com/) and enable billing on a project.
2. **gcloud SDK** — install via the [official guide](https://cloud.google.com/sdk/docs/install).
3. **Docker** — install via the [Docker docs](https://docs.docker.com/get-docker/).
4. **Project** — create a new Google Cloud project and note the **Project ID**.
5. **APIs** — enable the following in the [API Library](https://console.cloud.google.com/apis/library):
   * Cloud Run API
   * Cloud Build API
   * Artifact Registry API

## Step 2: Build the agent

### `api/api.py`

```python theme={null}
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)
```

### `requirements.txt`

```
flask
swarms
```

### `Dockerfile`

```dockerfile theme={null}
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"]
```

<Note>
  Cloud Run sends traffic to port `8080` by default — keep that as the listening port.
</Note>

## Step 3: Authenticate

```bash theme={null}
gcloud auth login
gcloud config set project [PROJECT_ID]
```

## Step 4: Push the image to Artifact Registry

```bash theme={null}
# 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
```

## Step 5: Deploy to Cloud Run

```bash theme={null}
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.

## Step 6: Test the deployment

Cloud Run prints a URL after deploy. Hit the endpoint:

```bash theme={null}
curl -X POST [CLOUD_RUN_URL]/run-agent \
    -H "Content-Type: application/json" \
    -d '{"task": "Summarise the latest performance of AAPL"}'
```

## Step 7: Update the service

Iterating is just rebuild → push → redeploy:

```bash theme={null}
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
```

## 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**:

  ```bash theme={null}
  gcloud logs read --project [PROJECT_ID]
  ```

<Note>
  Source: [docs/swarms\_cloud/cloud\_run.md](https://github.com/kyegomez/swarms/blob/master/docs/swarms_cloud/cloud_run.md)
</Note>

## See also

* [Deployment Solutions Overview](/examples/deployment-overview) — when to pick Cloud Run vs cron jobs vs Kubernetes.
* [FastAPI Agent API](/examples/fastapi-agent-api) — alternative API stack using FastAPI + Uvicorn.
* [Cloudflare Workers](/examples/cloudflare-workers) — edge deployment pattern for cron-driven agents.