bytefury/crater
Crater is a free, open-source invoicing and billing app for freelancers and small businesses, built on Laravel and Vue. Create invoices, estimates, expenses, payments, and reports, with multi-currency support, recurring invoices, and a REST API.
What this actually is: Crater is not a Composer library or a reusable SDK — it is a full, self-contained invoicing application (Laravel REST API backend + Vue SPA frontend, multi-company/multi-tenant data model) distributed as deployable product source. The correct TPM framing is "adopt or fork a product," not "add a dependency." Composer-level reuse of its internals is impractical.
Architecture fit: Strong fit only if our platform is Laravel/PHP and the business requirement is a standalone, self-hosted invoicing/billing surface (customers, invoices, estimates, items, taxes, payments, recurring invoices, PDF generation). Poor fit if we need an embeddable billing engine or white-label component inside a different stack — the codebase is monolith-shaped, and extracting bounded modules (e.g., invoice domain, PDF pipeline) is a fork-and-refactor effort, not an integration.
Integration feasibility: Feasible via two viable models: (1) deploy as a standalone service and integrate over its REST API with CRM, ERP, payments, and auth (Sanctum-based); (2) fork and white-label as our own product. Both require owning the deployment, database, queue workers, and cron. There is no meaningful plugin/extension ecosystem, so every customization is a code change in our fork.
Technical risk (high):
Key questions for the decision:
Stack fit: Good for Laravel/PHP teams already operating MySQL/Postgres, Redis, queue workers, and a scheduled-job runner. Frontend work assumes Node tooling for Vue 2 asset builds; plan for a Vue 3 or headless-API migration if the UI must live beyond this decade. Docker-based deployment is the lowest-friction starting point.
Migration path:
Compatibility: Verify PHP and Laravel constraints against our hosting baseline first — this is the most likely hard blocker. Confirm database engine support, storage requirements for generated PDFs, SMTP/email deliverability configuration, and timezone/currency/multi-company behavior under our data model.
Sequencing: Legal/license review → sandbox proof → fork + dependency and security audit → framework/frontend modernization spike → integration and branding → parallel run → production. Do not begin customization before the license decision and the security audit; both can invalidate the plan.
Maintenance: This is the dominant cost. With no active upstream release stream, our team owns security patching, framework upgrades, dependency remediation, and bug fixes. Budget continuous (not occasional) engineering capacity, plus a defined CVE response process, because invoice and payment data raise the blast radius of any unpatched issue.
Support: No vendor SLA. Support is community forums/GitHub plus internal expertise. Escalation paths for production incidents must be built internally, including runbooks for data corruption, stuck queues, and failed PDF/email delivery.
Scaling: The application scales conventionally — stateless web tier behind a load balancer, shared database, Redis cache, and dedicated queue workers for PDF generation and outbound email, which are CPU- and latency-heavy. Recurring invoicing depends on a reliable scheduler; treat missed cron/queue execution as a revenue-affecting failure. It is not architected for very high tenant counts or multi-region without our own work.
Failure modes to design for: unpatched vulnerabilities in a payment-adjacent system; scheduled-job failure silently skipping recurring invoices; PDF/email delivery failures that leave invoices unsent; tax/currency rounding defects across multi-company data; and fork drift if the community diverges from our customizations, making upstream patches unrebasable.
Ramp-up: Laravel developers become productive in the codebase within days, but production readiness — security hardening, upgrade path, observability, backup/restore drills, and billing reconciliation — is a multi-month effort, not a sprint. Plan for an owned technical lead, a documented fork strategy, and an explicit exit option (data export and API-compatible replacement) in case the fork becomes unsustainable.
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