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Configuring Deployment

Cluster Deployment is the process of integrating a trained model into the cluster's environment for inference or other applications. Once the model is trained, deployment involves configuring it to make predictions or provide results by utilizing the computational resources within the cluster.

Deployment Types

There are several deployment types you can choose from based on your use case and technology stack. Below are the supported deployment types:

Create Deployment

  • To create a new Deployment, click the Create Deployment button.

First Time Deployment Create

Select the desired Framework by choosing the appropriate Cluster with the required CPU, GPU, and an available plan. Click on Next.

Select Deployment Type

Select the desired Image according to your requirement.

Select Image Type

Select the appropriate SSH Keys or create new one. Click on Next.

Select Ssh Keys

Select the Shared File-System and Dataset according to your requirement or create new one. Click on Finish.

Select Sfs Keys

Review the details you have selected and make any necessary changes by clicking on Edit. Click on Create.

Check Summary

Manage Deployment

Overview

You can view the details of the selected Deployment, including the Deployment Name, Number of Workers, SSH Keys, and the Deployment Image. By clicking Overview.

Deployment Overview

Worker Management

You can view the details of Workers created for your Deployment and view logs and connect to Master Node.

View Worker

Connect

You can view connect details by clicking connect icon.

Click Connect

View Connect

Logs

You can view Logs in details by clicking Logs. And select the worker you want view logs.

View Logs

Volume

You can view Volume in details by clicking volume.

View Volume

Volume

You can view added ssh keys in details by clicking User Management.

View ssh keys

Monitoring

You can view the Memory Usage for the Workers within the Deployment. Additionally, the following metrics are also available: GPU Utilization, GPU Temperature, CPU Utilization, Memory Utilization.

View Events