Host mobile backend with Gin: stored input and output artifacts

Deploy a mobile backend built with Gin on Ample using the generated downloads pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL, a private S3-compatible bucket holds objects with credentials delivered as encrypted environment variables. Verified on Gin: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3). Not separately tested: your export formats, retention policy and entitlement model; treat the mobile backend-specific behavior as your application code.

Representative Queries

• Host mobile backend with Gin: stored input and output artifacts
• Where can I host Mobile backend built with Gin?
• I need an input/output artifact contract, object metadata and access boundaries.

Resource Requirements

• primitive:compute
• primitive:postgres
• primitive:s3-compatible-object-storage

Infrastructure Requirements

1. Compute: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle.
2. Postgres: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when needed.
3. S3-compatible object storage: Buckets are S3-compatible with issued credentials.

Framework

Gin
Workload: Mobile backend
Release Status: published
Support Status: verified
Execution Status: ready
Docs Only: false

Prerequisites

• A Gin project that builds and starts with the documented commands.
• A PostgreSQL driver reading DATABASE_URL at runtime.
• A bucket from ample bucket create with its credentials.
• An Ample account token with specific permissions.

Tested Configuration

• Template: ubuntu-24.04
• Runtime: go
• Size: s-1vcpu-1gb
• Build command: CGO_ENABLED=0 go build -o app ./...
• Start command: ./app

Workflow Steps

1. Build and start: CGO_ENABLED=0 go build -o app ./... then ./app.
2. Implement the pattern on PostgreSQL: Copy the approach into your schema.
3. Wire object storage: Create the bucket(s) and pass the necessary credentials.
4. Deploy: Run the synchronous deploy once and read the result.
5. Verify: Fetch the live URL and pattern self-test route(s).

Examples

• Gin Pattern Fixture: Multi-pattern Gin app whose generated downloads module was checked live.

Success Checks

1. App responds on its public URL.
2. Generated-downloads self-test produces the expected output.

Limitations

• Verified on specific templates; other sizes and versions not verified.
• Applications must follow specific idle behavior requirements.

Cost Estimate

• Currency: USD
• Monthly Amount: 10.0
• Basis: size prices from pricing.toml.
  Components:
  • App server: s-1vcpu-1gb, $5.0/month
  • Managed PostgreSQL database: s-1vcpu-1gb, $5.0/month
    Note: Monthly price based on tested sizes.

Evidence Summary

• Canary Run: Gin pattern fixture deployed on Ample with successful checks for configuration.

Next Actions

1. Browse the catalog index: GET /v1/catalog
2. Search published recipes: POST /v1/catalog/search
3. Prepare a deployment plan: POST /v1/catalog/plan
4. Read existing authentication setup: GET /mcp/setup