EasyDeploy
Deploy pre-configured AI environments on Krutrim Cloud with one-click templates like OpenClaw and Jupyter Notebook.
Krutrim EasyDeploy lets you launch pre-configured AI environments on Krutrim Cloud with one-click templates. It provisions a Virtual Machine with the required software stack, dependencies, runtimes, and application code already installed.
EasyDeploy currently supports two templates:
OpenClaw: A pre-configured environment for deploying autonomous AI agents.
Jupyter Notebook: A ready-to-use workspace for data science and model experimentation.
OpenClaw
Autonomous Agents
443 (HTTPS)
openclaw_
Jupyter Notebook
Data Science / ML
8888 (HTTP)
jupyter_
2. Deployment Workflows
2.1 Deploying OpenClaw
OpenClaw is an autonomous agent ecosystem tailored for Indian developers. The EasyDeploy flow automates the provisioning of the orchestrator and reasoning engine.
Steps for Deployment:
Infrastructure Setup: Before launching, ensure you have created the required networking dependencies:
VPC & Subnet: Select your preferred Virtual Private Cloud and specific subnet.
Network & Security Group (SG): Ensure your Security Group allows inbound traffic on port 443 for web access.
API Integration: You must provide or create a Model API Key (e.g., from Krutrim AI Studio) to serve as the agent's reasoning "brain".
Provisioning: Navigate to the EasyDeploy tab in the Krutrim Console, select "OpenClaw," and click Deploy.
Verification: Once the status changes from "Provisioning" to "Running," the VM will appear in your "My Instances" list with the prefix openclaw_ (e.g., openclaw_assistant_01).
Access: You can access the OpenClaw Web UI directly via the public IP:
URL Format: https://<VM_IP>/
Pricing: Pricing for this feature is the same as standard VM pricing for the selected flavor, with no additional charges.
Disclaimer: The data you expose using OpenClaw is strictly your responsibility. Krutrim is not responsible for any data exposure, as OpenClaw is an open-source software. Please refer to the OpenClaw GitHub repository for the source code and official documentation.
2.2 Deploying Jupyter Notebook
The Jupyter Notebook template provides a sandboxed environment with pre-installed Python libraries and ML tools.
Steps for Deployment:
Infrastructure Setup: Configure the foundational networking components:
VPC & Subnet: Identify the region and network for deployment.
Security Group: Open port 8888 in your Security Group configuration to allow browser access to the Jupyter server.
Provisioning: Select the Jupyter Notebook template from the EasyDeploy menu.
Verification: Monitor the deployment progress in the dashboard. The VM will be created with the prefix jupyter_ (e.g., jupyter_research_env).
Access: Access your notebook environment using the following URL:
URL Format: http://<VM_IP>:8888
3. Post-Deployment Management
All instances created via EasyDeploy will appear in the "My Instances" page with their respective prefixes. From there, you can perform the following lifecycle operations through the Krutrim Console:
View: Track status and resource utilization.
Start/Stop: Manage costs by pausing instances when not in use.
Delete: Remove instances and associated block storage when no longer required.
4. Troubleshooting & Best Practices
Networking: If the VM is "Running" but the URL is inaccessible, verify that your Security Group explicitly allows ingress on the required ports (443 for OpenClaw, 8888 for Jupyter).
API Keys: For OpenClaw, ensure your API key has sufficient token limits to avoid inference failures.
Identification: Always check for the openclaw_ or jupyter_ prefix in the instance list to distinguish EasyDeploy VMs from standard compute instances.
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