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Neptune can provision and manage cloud resources alongside your application deployments. Resources are defined in your neptune.json configuration and automatically wired to your application.

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Available Resources

Storage Buckets

S3-compatible object storage for files and assets

Secrets

Secure storage for API keys and sensitive configuration

Databases

Managed Postgres databases

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Adding Resources

The easiest way to add resources is to ask your AI assistant:
“Add an S3 bucket for user uploads to my project”
Or you can define them directly in your neptune.json:
neptune.json
{
  "kind": "Service",
  "name": "my-app",
  "resources": [
    {
      "kind": "StorageBucket",
      "name": "uploads"
    },
    {
      "kind": "Secret",
      "name": "STRIPE_API_KEY"
    },
    {
      "kind": "Database",
      "name": "my-app-db"
    }
  ]
}

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Resource Lifecycle

1

Define

Add resources to your neptune.json configuration (or ask your AI assistant to add them)
2

Provision

Neptune provisions the cloud resources and returns the physical resource names to your AI assistant.
3

Code

Write your application code using the physical resource names, or let your AI assistant write it for you.
4

Deploy

Your app is deployed with all IAM permissions pre-configured to access its resources.
Your AI assistant handles this flow automatically - it provisions resources, knows the physical names, and can write code that accesses them correctly.

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How Resources Work

When Neptune provisions a resource, it creates:
  1. A unique physical name - e.g., neptune-abc123-uploads for global uniqueness
  2. IAM permissions - Your service automatically has access to its own resources
  3. No manual credential setup - Just use standard AWS SDKs like boto3
Your AI assistant receives the physical resource names after provisioning and can use them when writing code for you.

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Example: Web App with Storage and Secrets

Here’s a complete configuration for a typical web application:
neptune.json
{
  "kind": "Service",
  "name": "my-saas-app",
  "port_mappings": [
    { "container_port": 3000, "host_port": 8080 }
  ],
  "resources": [
    {
      "kind": "StorageBucket", 
      "name": "user-uploads"
    },
    {
      "kind": "Secret",
      "name": "STRIPE_SECRET_KEY"
    },
    {
      "kind": "Secret",
      "name": "RESEND_API_KEY"
    },
    {
      "kind": "Database",
      "name": "myapp-db"
    }
  ]
}
Your application can then access these resources using standard AWS SDKs: 
import boto3
import stripe
from resend import Resend

# Physical names provided by your AI assistant after provisioning
BUCKET_NAME = "neptune-abc123-user-uploads"
STRIPE_SECRET_NAME = "neptune-abc123-STRIPE_SECRET_KEY"
RESEND_SECRET_NAME = "neptune-abc123-RESEND_API_KEY"

# Storage - permissions are pre-configured
s3 = boto3.client("s3")
s3.put_object(Bucket=BUCKET_NAME, Key="example.txt", Body=b"Hello!")

# Secrets - accessed via AWS Secrets Manager
sm = boto3.client("secretsmanager")

stripe_key = sm.get_secret_value(SecretId=STRIPE_SECRET_NAME)['SecretString']
stripe.api_key = stripe_key

resend_key = sm.get_secret_value(SecretId=RESEND_SECRET_NAME)['SecretString']
resend = Resend(api_key=resend_key)

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Managing Resources

Ask your AI assistant to help with common resource operations:
TaskExample Request
Add a resource”Add an S3 bucket called ‘uploads’ to my project”
Add a database”Add a database called ‘app’ to my project”
Set a secret”Set my STRIPE_API_KEY secret”
List bucket files”What files are in my uploads bucket?”
Check status”What’s the status of my resources?”
Get resource names”What are the physical names of my resources?”