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