# Host reporting dashboard with Django: structured data imports

Deploy a reporting dashboard 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 reporting dashboard-specific behavior as your application code.

## Representative Queries
- Host reporting dashboard with Django: structured data imports
- Where can I host Reporting dashboard built with Django?
- I need a workload-specific import mapping, conflict rules and restart behavior.

## Resource Requirements
- **Compute**
- **Postgres**
- **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

## 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.
   ```bash
   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`.
   ```bash
   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 reporting dashboard 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.

## Cost Estimate
- **Currency**: USD  
- **Monthly Amount**: 10.0  
- **Components**:
  - **App server**: monthlyAmount 5.0  
  - **Managed PostgreSQL database**: monthlyAmount 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.

## Examples
- **Django pattern fixture**: Multi-pattern Django app whose bulk import staging module was checked live; the module is under tests/deploy-canaries/_pattern-modules. Source: tests/deploy-canaries/django-patterns.

## Success Checks
- App responds on its public URL: expected "ample canary django patterns".
- Bulk-import-staging self-test at path /p/bulk-import-staging expected "imported=2 rejected=1 restart=ok".

## Evidence Summary
- **Canary Run**: Django pattern fixture deployed on Ample; checks passed for bulk-import-staging and configuration-secrets.
- Observed At: 2026-09-20T03:31:44Z 
  - Implementation Revision: 03b6402b1b3e19178985f08ea4033804521d85d4-dirty (CLI b75e104)  
  - Expires At: 2027-03-19T03:31:44Z

## Formats
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