# Rhythm Backend

High-performance Rust backend for a lightweight issue tracking platform focused on team execution.

## Main Objective

Build a simple, reliable issue tracker where teams can:

- Create and manage projects
- Add users to projects with role-based permissions
- Create, update, and track issues with practical metadata
- Organize work through Kanban and Scrum views

The first version prioritizes clean CRUD, clear access control, and fast text search on plain-text issue data.
Encryption and advanced collaboration features can be added in later iterations.

## How To Start

1. Lock the V1 scope
   - Entities: `users`, `projects`, `project_members`, `issues`
   - Roles: `owner`, `maintainer`, `member`, `viewer`
   - Issue fields: `title`, `description`, `status`, `priority`, `type`, `assignee_id`, `reporter_id`, optional `sprint_id`, timestamps
   - Keep Kanban and Scrum as filtered endpoints first (not separate DB models)

2. Bootstrap the Rust service
   - Stack: `axum`, `tokio`, `sqlx`, `postgres`, `tracing`
   - Suggested modules: `http/`, `service/`, `repo/`, `model/`, `auth/`, `db/`
   - First route: `GET /health`

3. Build the database first
   - Migrations for `users`, `projects`, `project_members`, `issues`
   - Add unique constraint on `(project_id, user_id)` in memberships
   - Add indexes for issue listing and filtering
   - Add `tsvector` + `GIN` index for title/description full-text search

4. Implement CRUD vertical slices
   - Projects: create, read, update
   - Memberships: add member, update role, remove member
   - Issues: create, list with filters + pagination, update, delete/soft-delete

5. Add board endpoints
   - Kanban endpoint grouped by status
   - Scrum endpoints for sprint + backlog views
   - Keep these as query/aggregation logic on top of `issues`

6. Harden the service
   - Add authentication (JWT or session)
   - Enforce role checks per project
   - Add request validation and consistent error responses
   - Add integration tests for permissions and issue lifecycle
   - Add slow-query logging and tune key SQL with `EXPLAIN ANALYZE`

## Technical Direction

- Language: Rust
- API: REST
- Database: PostgreSQL
- Search: PostgreSQL full-text search (`tsvector` + `GIN` indexes)
- Scale target: under 1M issues

## Notes

- Keep handlers thin, business rules in services, SQL in repository layer
- Prefer cursor pagination over deep offset pagination
- Add external search only when Postgres full-text search becomes limiting