## Host campaign site with Django: bulk content imports

Deploy a campaign site built with Django on Ample using the bulk import staging 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 Django: a CSV staged as an object, row-level validation with per-row errors recorded, and a restart-safe import keyed by import id (imported=2 rejected=1 restart=ok). Not separately tested: your import format, mapping and conflict rules; treat the campaign site-specific behavior as your application code.

### Summary
- **Framework**: Django  
- **Workload**: Campaign site  
- **Release status**: Published  
- **Support status**: Verified  
- **Execution status**: Ready

### Representative Queries
1. Host campaign site with Django: bulk content imports  
2. Where can I host Campaign site built with Django?  
3. I need a staged import format, validation procedure and import recovery workflow.

### Resource Requirements
- primitive:compute  
- primitive:postgres  
- primitive:s3-compatible-object-storage

### Infrastructure Requirements
1. **Compute**:  
   - Status: verified  
   - Summary: 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**:  
   - Status: verified  
   - Summary: 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**:  
   - Status: verified  
   - Summary: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

### Prerequisites
- A Django project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.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  
- An Ample account token with servers:write, databases:read, buckets:read

### Tested Configuration
- **Template**: python-3.12  
- **Runtime**: python  
- **Size**: s-1vcpu-1gb  
- **Install**: python3 -m pip install --target .ample/python -r requirements.txt  
- **Start**: PYTHONPATH=.ample/python:${PYTHONPATH:-} python3 run.py

### Workflow Steps
1. **Build and start**  
   - pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.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 bulk import staging: a CSV staged as an object, row-level validation with per-row errors recorded, and a restart-safe import keyed by import id (imported=2 rejected=1 restart=ok). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.

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). Re-running with no change is a no-op.
   
   ```  
   ample deploy . --name  --public --start "python3 run.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=...  
   ```

5. **Verify**  
   - Fetch the live URL and the pattern self-test route(s) (/p/bulk-import-staging) from the example; then run your own checks. On failure read `ample logs  --kind build` then `--kind runtime`.
   
   ```  
   ample logs  --kind build  
   ```

### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Django major versions are not verified.
- The campaign site itself (your import format, mapping and conflict rules) is application code and was not separately tested; the pattern checks are what was verified.
- Region, compliance attestations and request-duration limits are unknown and not claimed.
- Apps auto-pause when idle and wake on the next request; always-on is an operator setting, not a plan feature.
- Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified; apps and their databases are placed together.
- PutObject and GetObject with path-style addressing are verified; multipart upload, listing, presigned URLs and lifecycle rules are not verified.

### Cost Estimate
- **Currency**: USD  
- **Monthly Amount**: 10.0  
- **Basis**: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty  
- **Components**:  
   - app server: size s-1vcpu-1gb, quantity 1.0, monthly amount 5.0  
   - managed PostgreSQL database: size s-1vcpu-1gb, quantity 1.0, monthly amount 5.0  
- **Note**: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.