### Host company website with Flask: object-stored public media

Deploy a company website built with Flask on Ample using the public media library 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, and a published bucket serves public assets from the CDN host. Verified on Flask: an object written to a published bucket with an immutable Cache-Control header, a mapping row, and the CDN URL serving it publicly. Not separately tested: your media processing, object layout and cache policy; treat the company website-specific behavior as your application code.

#### Representative Queries
- Host company website with Flask: object-stored public media
- Where can I host Company website built with Flask?
- I need an object layout, public asset URL policy and CDN delivery configuration.

### Resource Requirements
- Compute
- Postgres
- S3-compatible object storage
- CDN

### Infrastructure Requirements
1. **Compute**  
   Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
2. **Postgres**  
   Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.
3. **S3-compatible object storage**  
   Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.
4. **CDN**  
   The CDN host serves objects from published buckets. It does not front app compute and is not a cache or key-value store.

### Prerequisites
- A Flask project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template)
- A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env)
- A bucket from `ample bucket create` with its credentials passed as encrypted S3_* environment variables and a second, published bucket for public assets (CDN_*)
- An Ample account token with servers:write, databases:read, buckets:read

### Workflow Steps
1. **Build and start**  
   pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template. The server must bind 0.0.0.0 on PORT.
2. **Implement the pattern on PostgreSQL**  
   The fixture's module implements public media library: an object written to a published bucket with an immutable Cache-Control header, a mapping row, and the CDN URL serving it publicly.
3. **Wire object storage**  
   Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing. Keep private data in an unpublished bucket...
4. **Deploy**  
   Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked).
5. **Verify**  
   Fetch the live URL and the pattern self-test route(s)...

### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Flask major versions are not verified.
- The company website itself is application code and was not separately tested; the pattern checks are what was verified.

### Cost Estimate
- **Currency:** USD  
- **Monthly Amount:** $10.00  
- **Basis:** size prices from pricing.toml  
- **Components:** 
  - app server, size: s-1vcpu-1gb, monthly amount: $5.00
  - managed PostgreSQL database, size: s-1vcpu-1gb, monthly amount: $5.00
- **Note:** Always-on monthly price of the tested sizes.

### Success Checks
1. **App responds on its public URL**  
2. **Public-media-library self-test**

### Evidence Summary
- **Canary Run:**  
   Flask pattern fixture deployed on Ample; checks passed for public-media-library and configuration-secrets. Pattern proof: an object written to a published bucket...

### Next Actions
- **Browse the catalog index**
- **Search published recipes by intent, stack and constraints**