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Neptune deployments run your containerized applications on AWS with automatic health checks and zero-downtime deploys.

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How Deployments Work

1

Configure

Your AI assistant creates a neptune.json configuration file for your project
2

Build

Neptune builds your application using your Dockerfile (or your AI generates one for you)
3

Push

The container image is pushed to a private registry (Amazon ECR)
4

Deploy

Your container is deployed with access to all provisioned resources
5

Ready

You receive a public IP address to access your running application

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Deploying Your Application

Just ask your AI assistant:
“Deploy my application to Neptune”
Your AI assistant will handle everything:
  1. Generate a Dockerfile if your project doesn’t have one
  2. Create a neptune.json configuration file
  3. Provision resources (storage buckets, secrets)
  4. Build and push your Docker image
  5. Deploy and return your public IP

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Waiting for Deployment

After deploying, you need to wait for your app to start. Ask your AI assistant:
“Wait for my deployment to complete”
This is an important step! Your app won’t be accessible until the deployment finishes starting up. Your AI assistant will monitor the status and give you your public IP when ready.

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Checking Deployment Status

Ask your AI assistant:
“What’s the status of my deployment?”
This shows:
  • Infrastructure status: Whether resources are provisioned
  • Service status: Running, Pending, Stopped, or Error
  • Public IP: Your application’s public IP address
  • Resource details: Status of each storage bucket and secret

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Requirements

Your project needs:
  1. A Dockerfile - Neptune builds your app as a container
  2. Port 8080 - Your app should listen on port 8080 by default (configurable)
Don’t have a Dockerfile? No problem! Just ask your AI assistant to deploy and it will generate an optimized Dockerfile for your project automatically.

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Common Operations

TaskRequest
Deploy”Deploy my app”
Wait for ready”Wait for my deployment to complete”
Check status”What’s my deployment status?”
View logs”Show me the logs”
Redeploy”Redeploy my application”
Delete”Delete this project”

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Troubleshooting Deployments

If your deployment isn’t working, ask your AI assistant:
“My deployment isn’t working. Can you help debug?”
Your AI assistant will:
  1. Check the deployment status
  2. Retrieve application logs
  3. Identify the issue
  4. Suggest fixes
Common issues:
  • Stopped/Error: Application crashed - check logs for error messages
  • Pending too long: Container may be failing to start - ensure app listens on the correct port
  • Starting too long: Application may be hanging during startup

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Learn More

Configuration

Customize CPU, memory, ports, and more

Resources

Configure storage and secrets

Logs & Monitoring

Debug and monitor your deployments