> ## Documentation Index
> Fetch the complete documentation index at: https://docs.shaktistudio.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Deploying a Docker Container
This guide walks you through the complete process of deploying Docker containers to Shakti Studio platform, from credential setup to deployment.
## Prerequisites
* Docker images uploaded to your **Docker Hub repository.**
* **Docker Hub** account with appropriate access permissions:
> **Important**: Ensure your Docker Hub credentials have ***read access*** to your repositories.
## Part 1: Setting Up Docker Hub Credentials
### Creating a Secret:
1. Navigate to the **Integrations** section in your Shakti Studio dashboard
2. Select [**Secrets**](https://shaktistudio.ai/integrations/secrets) from the menu
3. Click **Create Secret** and configure:
* **Secret Name**: Enter a name for your secret.
* **Secret Type**: Select **Docker Hub** from the dropdown.
* **Credentials**: Enter your Docker Hub ***username*** and ***access token***.
## Part 2: Adding Your Docker Image
### Model Configuration
1. Go to the **My Models** page
2. Click **Add Model** and provide:
* **Model Name**: Descriptive name for your application
* **Source**: Select the model source as **DockerHub** from the dropdown
* **Registry Path**: Your **Docker Hub** registry path
* **Image Tag**: Specify the image *version/ tag*
* **GPU Per Container**: Default is set to `1`. You can allocate maximum 8 GPUs.
* **Credentials**: Select the **Docker Hub** secret created earlier
3. The system will verify your image path and add it to your models list
## Part 3: Deployment Configuration
### Basic Setup
1. From the **My Models** section, select the previously added **model** and click on **Deploy Model**
2. Configure basic details:
* **Deployment Name**: Enter a unique name for this deployment.
* **Cluster**: Select **Shakti Cloud** as the cluster.
* **Node Group**: Choose the required **node group** (H100/L40S).
### Container Configuration
#### Service Configuration
Configure how external traffic reaches your container:
* **HTTP Service** (Required):
* For example: 8000 (or your application's port) (The port on which your server will be running).
* This exposes your service within the cluster.
* **Optional Services**:
* **gRPC Service**: Enable if your application uses gRPC. (This port can't be the same as **http** service port)
* **Monitoring Service**: Add for enhanced monitoring capabilities.
#### Health Check Settings
Essential for monitoring container health:
* **Health Check Path**: /health (endpoint your app responds to)
* **Port**: 8000 (same as your HTTP service port)
* **Initial Delay**: 30 seconds (startup time allowance)
* **Check Interval**: 10 seconds (frequency of health checks)
* **Timeout**: 5 seconds (maximum response wait time)
#### Environment Variables (Optional)
Set runtime environment variables as needed:
* Add key-value pairs for configuration
* Use the + button to add multiple variables
#### Command Override (Optional)
Override the default container startup command:
* Specify the command to run in the container to **override** the **default command**. Add each part of the command as a separate entry and then press enter or click on the add button.
### Scaling Parameters
* **Range**: Set minimum and maximum instances (1-8)
* **Scaling Metric**: Choose **CPU usage / memory usage** as the scaling trigger
* **Threshold**: Define the percentage that triggers scaling \
*(e.g CPU Utilisation 80%)*
#### Node Distribution (Node Anti-Affinity)
Control how your containers are distributed across nodes:
* **No Affinity**: Containers deployed anywhere resources are available
* **Preferred**: System attempts to distribute across different nodes when possible
* **Required**: Strict enforcement of separate node placement
#### Advanced Options
* **Rapid Auto-scaling**: Enable for faster scaling response when needed
## Part 4: Deployment
1. Review all configuration settings
2. Click **Add Deployment** to initiate the deployment process
3. Monitor the deployment status
## Part 5: Monitoring and Access
### Health Status
Once deployed successfully, you'll see:
* **Health Status**: **Healthy** indicator on the deployment page
* **Deployment URL**: Direct access link to your application
### Troubleshooting
* Verify the health check endpoint is properly implemented in your application
* Ensure Docker image is accessible with the provided credentials
* Confirm port configuration matches your application