Management consultancies: form collection using Django

Summary

A form collection blueprint for management consultancies built with Django on Ample. Domain schema: client_entities (name, industry, primary_contact_role): client organizations; engagements (client_entity_id, scope_title, phase, period_start, period_end): engagement periods and phases; workstreams (engagement_id, name, owner, status, due_at): tracked workstreams; deliverables (engagement_id, title, version, object_key, released_at): versioned deliverables shared with the client; uploads (id, owner_reference, object_key, content_type, size, uploaded_at): validated uploads linked to their owner. Public information: service offerings and case studies (anonymized), consultant profiles, engagement model. Kept out of scope until handling is reviewed: client strategy documents, financial models, interview notes. Client strategy material is confidential; authorization is modeled per engagement and no compliance claim is made. Technical basis verified on Django: content-type and size validation that rejects disallowed files, an object written to a private bucket and a row linking the record to the object key (reject=ok upload=ok linked=ok).

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 (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 (auto-provisioned when omitted)
• Bucket credentials from ample bucket create passed as encrypted S3_* environment variables
• A review of which management consultancies data classes may be handled at all; this blueprint models public information only

Steps

1. Model the management consultancies domain. Create the tables client_entities, engagements, workstreams, deliverables, uploads. Client organizations lives in client_entities; keep the sensitive classes (client strategy documents, financial models, interview notes) out of this schema.

2. Workflow step 1. Model document requests per engagement with due dates and status

3. Workflow step 2. Validate uploaded files (type, size) before storing them in the private bucket and linking them to the request

4. Workflow step 3. Authorize uploads by client entity

5. Workflow step 4. Deploy and verify rejection of disallowed files and a linked upload

6. Deploy. Run the synchronous deploy once and read the result. 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=...
   

7. Verify. Run the pattern self-test(s) from the example (/p/browser-file-uploads) and your own acceptance checks for the management consultancies workflow.

   ample logs <deployment_id> --kind build
   

Tested examples

• Django pattern fixture (tests/deploy-canaries/django-patterns): Verified browser file uploads basis for this blueprint.

Success checks

• app responds on its public URL (/ on the live URL, expect ample canary django patterns)
• browser-file-uploads self-test from the example (/p/browser-file-uploads on the live URL, expect see the pattern fixture checks)

Limitations

• The technical basis (browser file uploads on Django) was verified with the pattern fixture; the management consultancies schema and workflow are an original design for this blueprint and were not executed as a separate application.
• No health, financial, privacy or other compliance claim is made. Client strategy material is confidential; authorization is modeled per engagement and no compliance claim is made.
• Public content and synthetic examples only until actual data-handling requirements have been reviewed.
• Verified on the python-3.12 template at s-1vcpu-1gb; region, request-duration limits and other sizes are unknown or unverified.
• Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified.
• PutObject and GetObject with path-style addressing are verified; other S3 operations and CDN cache rules are not.