Host approval workflow with Django: downloadable reports

Summary

Deploy a approval workflow built with Django 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 Django: 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 approval workflow-specific behavior as your application code.

Infrastructure requirements

• Compute: verified (Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.)
• Postgres: verified (Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.)
• S3-compatible object storage: verified (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

Exact 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

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 generated downloads: 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). 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 <app-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/generated-downloads) from the example; then run your own checks. On failure read ample logs <deployment_id> --kind build then --kind runtime.

   ample logs <deployment_id> --kind build

Tested examples

• Django pattern fixture (tests/deploy-canaries/django-patterns): Multi-pattern Django app whose generated downloads module was checked live; the module is under tests/deploy-canaries/_pattern-modules.

Success checks

• app responds on its public URL (/ on the live URL, expect ample canary django patterns)
• generated-downloads self-test (/p/generated-downloads on the live URL, expect export=ok rows=3 (with ?token=...; 401 without))

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 approval workflow itself (your export formats, retention policy and entitlement model) 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

Estimated 10.00 USD per month (size prices from pricing.toml at build revision a1b8c38919e59cd035ebabaced73cf84ece24371).

• app server x1 s-1vcpu-1gb: 5.00 USD
• managed PostgreSQL database x1 s-1vcpu-1gb: 5.00 USD

Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.

Verification evidence

• canary_run on 2026-09-20T03:31:44Z at revision 03b6402b1b3e19178985f08ea4033804521d85d4-dirty (CLI b75e104): Django pattern fixture deployed on Ample (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template); checks passed for generated-downloads and configuration-secrets. Pattern proof: 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). (expires 2027-03-19T03:31:44Z)
• canary_run on 2026-09-20T01:54:51Z at revision 199ff1dfd52683832ae75d3f98b53a7a4bff7f96-dirty (CLI e3181f5): The same Django app deployed with a --release-command migration; the marker it created was readable after activation. (expires 2027-03-19T01:54:51Z)

Last verified: 2026-09-20T03:31:44Z

Execution binding

MCP tool ample_deploy (registry mcp:ample_deploy), schema hash 876465fce906da0c observed 2026-09-21T03:19:59.461917+00:00 at revision 49962bcade4f, binding state current, required scopes: servers:write, databases:read, buckets:read.