Membership associations: asset library using Django

Summary

A asset library blueprint for membership associations built with Django on Ample. Domain schema:

• course_groups (chapter_or_program, start_at, end_at): chapters and programs as groups;
• memberships (course_group_id, member_email, tier, role, renewed_at): members and roles;
• sessions (course_group_id, starts_at, title, venue): meetings and events;
• materials (course_group_id, title, object_key, visibility): member resources;
• uploads (id, owner_reference, object_key, content_type, size, uploaded_at): validated uploads linked to their owner.

Public information

• About, chapters and benefits, public events, join information.

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).

Representative Queries

1. Membership associations: asset library using Django.
2. Where can I host Membership associations: Asset library built with Django?
3. I need a genuinely specialized asset library workflow covering membership tiers, event eligibility and shared resources.

Workflow Steps

1. Model the membership associations domain: Create the tables course_groups, memberships, sessions, materials, uploads. Chapters and programs as groups live in course_groups; keep sensitive classes out of this schema.
2. Model assets linked to their owning group or workspace.
3. Validate uploads and store them in the private bucket; link each object to its row.
4. Authorize downloads by membership.
5. Deploy and verify rejection of disallowed files and a linked upload.
6. Run the synchronous deploy once and read the result.

Input Schema

• env: Encrypted environment variables
• name: App name
• path: Project directory or ample.toml service
• release_command: Migration command run before activation
• start: Start command

Prerequisites

• A Django project.
• A PostgreSQL driver reading DATABASE_URL.
• Bucket credentials from ample bucket create as encrypted S3_* environment variables.
• A review of which membership associations data classes may be handled at all.

Infrastructure Requirements

1. Compute: Apps run in isolated x86_64 Firecracker microVMs.
2. Postgres: Managed PostgreSQL runs in its own microVM.
3. S3-compatible object storage: Buckets are S3-compatible with issued credentials.

Example

Django pattern fixture

Verified browser file uploads basis for this blueprint.

Limitations

1. Verified with the pattern fixture; the schema and workflow are an original design for this blueprint.
2. Member directories are personal data; only public events and member-authorized resources are modeled.

Cost Estimate

• Currency: USD
• Monthly Amount: 10.0
• Components:
  • App server: s-1vcpu-1gb, monthlyAmount: 5.0
  • Managed PostgreSQL database: s-1vcpu-1gb, monthlyAmount: 5.0

Success Checks

1. App responds on its public URL.
2. Browser-file-uploads self-test from the example.