page:blueprints:home services:order tracking:django

Home services: Order tracking using Django

Summary

A order tracking blueprint for home services built with Django on Ample. The domain schema includes:

• services (sku, name, category, price_from, duration_estimate): service catalog as SKUs.
• parts_stock (sku, delta, reason, moved_at): parts and consumables movements.
• jobs (job_no, service_area, status, scheduled_for): jobs as orders with status transitions.
• job_lines (job_no, sku, qty): services and parts on a job.
• events (seq, record_type, record_id, kind, at): application-owned history written in the same transaction.

Public information

• Service catalog and pricing.
• Service areas and hours.
• Licensing and insurance summary.

Kept out of scope until handling is reviewed

• Customer addresses and access notes.
• Payment details.

Customer addresses and access instructions are personal data and will be kept out until handling is reviewed.

Technical basis

• Verified on Django: Includes an optimistic version check and an event row written in the same transaction. A stale update is rejected, and a history query is conducted over the application-owned events (history=2 conflict=rejected).

Representative Queries

• Home services: order tracking using Django
• Where can I host Home services: Order tracking built with Django?
• I need a genuinely specialized order tracking workflow covering service areas, job materials and field-job status.

Infrastructure Requirements

• Compute: Apps run in isolated x86_64 Firecracker microVMs.
• Postgres: Managed PostgreSQL 16 runs in its own microVM.
• S3-compatible object storage: Buckets are S3-compatible with issued credentials.

Workflow Steps

1. Model the home services domain: Create the tables for services, parts_stock, jobs, job_lines, events.
2. Model orders: Include explicit status transitions and order lines.
3. Apply status changes: Transactionally and record an event per change.
4. Expose status history: To authorized callers only.
5. Deploy and verify: Execute the synchronous deploy once and read the result.
6. Verify: Run the pattern self-test(s) and acceptance checks.

Examples

• Django pattern fixture: Verified transactional workflows basis for this blueprint.

Cost Estimate

• Monthly Amount: $10.00 USD
• Components:
  • App server (s-1vcpu-1gb): $5.00
  • Managed PostgreSQL database (s-1vcpu-1gb): $5.00

Limitations

• The technical basis and workflow design for home services has not been executed as a separate application.
• Public content and synthetic examples only until actual data-handling requirements have been reviewed.

Evidence Summary

• Canary Run: Django pattern fixture deployed on Ample with passed checks for transactional workflows.

Next Actions

• Browse the catalog index.
• Search published recipes by intent, stack, and constraints.
• Prepare a side-effect-free deployment plan.
• Read the existing agent authentication setup.