# Build brief — a focused alternative to Svix > **Verdict:** Partly, if you narrow it · **Buildability:** 49/100 · **Category:** Dev Tools > **Source:** https://www.canitbevibecoded.com/svix > Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from Svix. Verify current pricing and capabilities before acting. ## Context **Svix** — Managed outbound webhook sending with retries, signing, logs and a customer-facing portal. It currently costs $490/mo. The core loop here is genuinely small: accept an event, look up subscribed endpoints, sign the payload, POST it, retry on failure with backoff, log the attempt. An agent will produce that in a session, and for a single product sending a few thousand events a day it will work fine. What does not fall out of a one-shot is the boring half: a queue that survives restarts, per-endpoint rate limiting and circuit breaking so one dead customer does not poison your worker pool, replay and manual retry tooling, a portal your customers can log into, and signature schemes that third-party libraries already understand. Svix is also open source, which means the honest DIY move is often self-hosting theirs rather than writing your own. Call it a focused implementation for something you would actually put in front of paying users, and understand that you are now on call for it. This brief describes a focused, single-operator replacement for the part of Svix that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest. ## What you are building Takes an event via API, fans it out to registered endpoints with HMAC-signed payloads, retries failures on exponential backoff, and records every attempt. - Build the focused developer workflow you use repeatedly, with local configuration. - A responsive interface with real empty, loading, success, and error states. ## Requirements ### Functional - A Postgres database. - Redis or Postgres-backed job queue. - A server that stays up, not a serverless function. - Somewhere to store attempt logs that will grow fast. ### Non-functional - Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support. - Security: server-side secrets, validated input, and no credentials in the client bundle. - Reliability: retries with backoff on external calls, and a clear failure state when a provider is down. - Portability: the operator can export their data and leave without losing it. ## Implementation brief Build a self-hosted outbound webhook delivery service. Single Node.js project, TypeScript, Fastify for HTTP, Postgres via Drizzle ORM, BullMQ on Redis for the delivery queue. Docker Compose for Postgres and Redis. No cloud accounts, no telemetry, no auth provider: a single static API key in .env guards the admin and ingest routes. Data model: - applications: id, name, created_at (one per tenant/customer of mine) - endpoints: id, application_id, url, description, secret, enabled, event_types (text array, empty means all), created_at - messages: id, application_id, event_type, payload jsonb, created_at - attempts: id, message_id, endpoint_id, attempt_number, status_code, response_body_excerpt, error, duration_ms, created_at HTTP API (all JSON, all behind the API key header): - POST /api/applications, GET /api/applications - POST /api/applications/:id/endpoints, GET, PATCH, DELETE - POST /api/applications/:id/messages: body has event_type and payload. Persist the message, resolve matching enabled endpoints, enqueue one delivery job per endpoint, return the message id with 202. - GET /api/messages/:id/attempts - POST /api/attempts/:id/replay: re-enqueue that single delivery immediately. Delivery worker: - POST the raw JSON payload with headers: webhook-id, webhook-timestamp (unix seconds), webhook-signature as "v1," plus base64 HMAC-SHA256 over "{id}.{timestamp}.{body}" using the endpoint secret. - 5 second connect timeout, 10 second total timeout. - Success is any 2xx. Retry on everything else with backoff: 5s, 30s, 5m, 30m, 2h, 5h, then give up and mark the endpoint as failing. - Record an attempt row for every try, truncating response bodies to 2KB. - Rate limit per endpoint to 20 concurrent deliveries max using a BullMQ group or per-endpoint limiter. Also build a minimal server-rendered admin UI at / using Fastify plus plain HTML templates and no frontend framework: list applications, list endpoints, list recent messages, drill into a message to see attempts and hit replay. Ugly is fine, tables and buttons only. Out of scope: a customer-facing self-serve portal, per-customer login, multi-region, event type schema validation, inbound webhook receiving, transformations. Include a README with docker compose up, migration command, and one curl example that creates an application, an endpoint pointing at a local sink, and sends a message. Add a small script that runs a throwaway HTTP sink on port 4000 that verifies the signature and prints the payload, so delivery can be tested end to end. Write integration tests for signature generation and for the retry backoff schedule. ## Delivery standard - Inspect the repository first, then write a short implementation plan before writing code. - Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data. - Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations. - Include responsive layouts plus genuine empty, loading, success, validation, and failure states. - Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data. - Add structured logs around every external call and return actionable errors without leaking sensitive details. - Write unit tests for the core logic and one automated test of the main user journey. - Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations. ## Acceptance criteria - [ ] A clean install starts the app using only the README and .env.example. - [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable. - [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state. - [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control. - [ ] Tests, type checking, linting, and a production build all pass with no ignored failures. - [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified. ## Non-goals Do not build these, and do not claim to have replaced them: - A customer-facing portal where your users manage their own endpoints and see failures. - Battle-tested signature format that existing verification libraries accept out of the box. - Per-endpoint circuit breaking and rate limiting so one slow consumer does not stall everyone. - Operational maturity: dead-letter handling, replay windows, throughput under a spike. - Someone else being paged when delivery breaks at 3am. ## What you still own after launch - Run migrations, backups, restores, and dependency updates. - Test the critical journey after every model, API, or hosting change. - Monitor failures and fix the edge cases a first prompt will miss. ## Risk **Operational risk.** The code is achievable; dependable data, integrations, and ongoing operations are the real cost. Editorial confidence in this assessment: medium. No reviewed project implementation is linked yet. --- Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/svix