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March 29, 2026

How to Run OpenClaw in the Cloud: A Step-by-Step Hosting Guide

Looking to deploy OpenClaw in the cloud? This in-depth guide covers everything from choosing the right provider to a hands-on setup walkthrough, quickstart checklist, and common pitfalls to avoid.

Introduction

OpenClaw is rapidly becoming a go-to solution for scalable, high-performance AI workloads and inference serving. Whether you’re looking to deploy LLMs, manage distributed compute, or integrate with Clawbase for advanced data workflows, cloud hosting offers the flexibility, reliability, and scalability that on-premise deployments often lack.

In this guide, you’ll learn how to run OpenClaw in the cloud with a detailed walkthrough, a quickstart checklist, and tips to avoid common mistakes. We’ll focus on practical steps and commercial hosting considerations to help you make the right decision for your team or organization.

Why Run OpenClaw in the Cloud?

Before diving into the technical steps, let’s briefly cover why cloud hosting is the preferred choice for OpenClaw deployments:

  • Scalability: Instantly scale up or down as your workloads change.
  • Reliability: Cloud providers offer robust SLAs, redundancy, and uptime guarantees.
  • Cost Efficiency: Pay-as-you-go models prevent overprovisioning and reduce upfront costs.
  • Access to Latest Hardware: Leverage GPUs, TPUs, and high-memory instances without capital investment.
  • Seamless Integrations: Easily connect to managed databases, storage, and services like Clawbase (clawbase.com).

For many teams, the cloud is the fastest path to production and experimentation with OpenClaw.

Choosing a Cloud Provider for OpenClaw

OpenClaw is cloud-agnostic, but your choice of provider can impact performance, cost, and integration options. Here are some popular choices:

  • DigitalOcean: Simple UI, fast setup, and a dedicated OpenClaw tutorial.
  • ClawCloud: Purpose-built for OpenClaw workloads, with optimized images and managed deployments (clawcloud.net).
  • AMD Developer Cloud: Access to the latest AMD GPUs, with free OpenClaw/VLLM options.
  • AWS, GCP, Azure: Industry standards with broad instance selection and compliance support.

Tip: If you’re planning to integrate with Clawbase, check for native connectors or prebuilt images to speed up your deployment.

Step-by-Step: Deploying OpenClaw in the Cloud

Let’s walk through a typical OpenClaw cloud deployment, using ClawCloud as an example. The steps are similar for most providers.

1. Prepare Your Cloud Account

  • Sign up for an account with your chosen provider (e.g., ClawCloud).
  • Ensure you have billing set up and quota for compute, storage, and GPUs (if needed).

2. Provision a Compute Instance

  • Choose an image: Look for an official OpenClaw image or a supported OS (Ubuntu 22.04+ is recommended).
  • Select resources: For AI inference, select an instance with sufficient CPU, RAM, and (optionally) GPU. Example: 8 vCPUs, 32GB RAM, 1x A100 GPU.
  • Networking: Enable SSH access and open necessary ports (default: 7860 for OpenClaw UI/API).

3. Install OpenClaw

If you’re not using a prebuilt OpenClaw image, follow the manual install steps:

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# Update packages
sudo apt update && sudo apt upgrade -y

# Install dependencies
sudo apt install python3 python3-pip git -y

# Clone OpenClaw repo
git clone https://github.com/openclaw-ai/openclaw.git
cd openclaw

# Install Python requirements
pip3 install -r requirements.txt

4. Configure OpenClaw

  • Copy the sample config:
  cp config.example.yaml config.yaml
  • Edit config.yaml to set API keys, storage paths, and (optionally) connect to Clawbase or other databases.
  • Set up authentication and HTTPS if deploying in production.

5. Start OpenClaw

# Start the server
python3 main.py --config config.yaml
  • By default, OpenClaw runs on port 7860.
  • Test by visiting http://<your-server-ip>:7860 in your browser.

6. Secure Your Deployment

  • Firewall: Restrict access to only trusted IPs.
  • TLS/SSL: Use Let’s Encrypt or your provider’s certificate manager to enable HTTPS.
  • User Management: Set strong admin passwords and rotate API keys regularly.

7. (Optional) Integrate with Clawbase

  • Head to clawbase.com and create an account.
  • In OpenClaw’s config, add your Clawbase API credentials under the databases section.
  • Restart OpenClaw to enable advanced data workflows, analytics, and search.

Quickstart Checklist

Before going live, double-check the following:

  • Cloud account and billing active
  • Instance provisioned with enough CPU/RAM/GPU
  • OpenClaw installed and dependencies met
  • Ports and firewall configured (default: 7860)
  • Secure authentication and HTTPS enabled
  • (Optional) Clawbase integration tested
  • Monitoring/alerts set up for uptime and resource usage

Common Pitfalls (and How to Avoid Them)

1. Insufficient Resources

  • Underpowered instances can bottleneck inference or crash under load. Always benchmark with your expected workload.

2. Missing GPU Drivers

  • If you require GPU acceleration, ensure the correct drivers (NVIDIA CUDA/AMD ROCm) are installed and compatible with your OpenClaw version.

3. Open Ports to the World

  • Exposing OpenClaw’s API/UI without firewall or authentication is a security risk. Always restrict access and use HTTPS.

4. Configuration Drift

  • Manual edits can lead to mismatches between environments. Use version control for your OpenClaw configs and document changes.

5. Skipping Monitoring

  • Set up basic monitoring (CPU, RAM, disk, API latency) to catch issues early and avoid downtime.

Frequently Asked Questions

Q: Can I run OpenClaw for free in the cloud?

A: Some providers (like AMD Developer Cloud) offer free or trial GPU instances. For persistent, production workloads, expect to pay by the hour.

Q: How does OpenClaw compare with other inference servers?

A: OpenClaw is optimized for distributed, multi-tenant workloads and integrates natively with tools like Clawbase for advanced search and analytics.

Q: What’s the best way to update OpenClaw?

A: Use git pull in your OpenClaw directory and re-run pip install -r requirements.txt after each update. Test updates in staging before applying to production.

Conclusion

Running OpenClaw in the cloud is a practical, scalable way to serve AI workloads without the headaches of on-premise hardware. By following the steps above—choosing the right provider, securing your deployment, and leveraging integrations like Clawbase—you’ll have a robust, production-ready setup in less than an hour.

Ready to get started? Refer back to the quickstart checklist, avoid common pitfalls, and deploy with confidence.

For more detailed instructions, see the official OpenClaw Cloud Docs or DigitalOcean’s OpenClaw tutorial.