Host reporting dashboard with Django: data exports

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

Representative Queries

• Host reporting dashboard with Django: data exports
• Where can I host Reporting dashboard built with Django?
• I need a scoped export format, artifact generation and authorized download procedure.

Resource Requirements

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

Infrastructure Requirements

Compute

Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.

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.

S3-compatible object storage

Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

Workflow Steps

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.

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.

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 Keep private data in an unpublished bucket.

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 <your_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=...

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 --kind build then --kind runtime.

ample logs --kind build

Examples

Django pattern fixture

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
• Generated-downloads self-test

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 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.