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CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

Checkmate is an open-source uptime and infrastructure monitoring application. It monitors server hardware, uptime, response times, and incidents with real-time alerts. The companion agent Capture provides infrastructure metrics (CPU, RAM, disk, temperature).

Development Commands

Client (React/Vite)

cd client
npm install
npm run dev -- --port 10001 --strictPort   # Local dev port is 10001 (5173 is used by another project on this machine)
npm run build            # TypeScript check + production build
npm run lint             # ESLint (strict, max-warnings 0)
npm run format           # Prettier formatting
npm run format-check     # Check formatting

Server .env on this machine is configured with CLIENT_HOST="http://localhost:10001" to match the client dev port. If you change the client port, keep .env in sync.

Server (Node.js/Express)

cd server
npm install
npm run dev              # Start with hot-reload (nodemon + tsx) at http://localhost:52345
npm run build            # TypeScript compile + path alias resolution
npm run test             # Run Jest tests with coverage
npm run lint             # ESLint v9
npm run lint-fix         # Auto-fix lint issues
npm run format           # Prettier formatting

Docker Development

cd docker/dev
./build_images.sh
docker run -d -p 27017:27017 -v uptime_mongo_data:/data/db --name uptime_database_mongo mongo:6.0

Environment Setup

Server .env (minimum required)

CLIENT_HOST="http://localhost:5173"
JWT_SECRET="my_secret_key_change_this"
DB_CONNECTION_STRING="mongodb://localhost:27017/uptime_db"
TOKEN_TTL="99d"
ORIGIN="localhost"
LOG_LEVEL="debug"

Client .env

VITE_APP_API_BASE_URL="http://localhost:52345/api/v1"
VITE_APP_LOG_LEVEL="debug"

Architecture

Monorepo Structure

  • /client - React 18 + TypeScript + Vite + MUI frontend
  • /server - Node.js 20+ + Express + TypeScript backend
  • /docker - Multi-environment Docker configs (dev, staging, prod, arm, mono)

Backend Layers

server/src/
├── controllers/     # Route handlers (authController, monitorController, etc.)
├── service/         # Business logic
│   ├── business/    # Core monitoring logic
│   ├── infrastructure/  # Server/system utilities
│   └── system/      # App-level settings
├── db/
│   ├── models/      # Mongoose schemas (Monitor, Check, Incident, User, etc.)
│   ├── migration/   # Database migrations (run on startup)
│   └── modules/     # Database-specific modules
├── middleware/v1/   # verifyJWT, rateLimiter, sanitization, responseHandler
├── routes/v1/       # API route definitions
├── validation/      # Joi input validation schemas
└── repositories/    # Data access layer

Frontend Structure

client/src/
├── Components/      # Reusable UI components
├── Pages/           # Page components (Auth, Uptime, Infrastructure, Incidents, etc.)
├── Features/        # Redux slices (Auth, UI)
├── Hooks/           # Custom React hooks
├── Utils/           # Utilities (NetworkService.js is main API client)
├── Validation/      # Input validation
└── locales/         # i18n translations

API

  • Base URL: /api/v1
  • Documentation: http://localhost:52345/api-docs (Swagger UI)
  • OpenAPI spec: /server/openapi.json

Key Technologies

  • State Management: Redux Toolkit + Redux-Persist
  • Data Fetching: SWR + Axios
  • Database: MongoDB with Mongoose ODM
  • Queue/Cache: Redis + BullMQ + Pulse (cron scheduling)
  • i18n: i18next + react-i18next (translations via PoEditor)

Backend Architecture Patterns

Repository Pattern & Separation of Concerns

The backend enforces a strict three-layer separation between HTTP handling, business logic, and data access:

Request → Controller → Service → Repository → MongoDB (Mongoose)
  • Controllers (/controllers) handle HTTP concerns only: parsing request params, calling the appropriate service, and returning a response via the responseHandler middleware. They contain no business logic.
  • Services (/service/business) contain all business logic: deciding whether an incident should be created, whether a notification should fire, what state a monitor is in, etc.
  • Repositories (/repositories) are the sole layer that talks to MongoDB through Mongoose. They expose clean, reusable query methods (e.g. findByMonitorId, createCheck) so that services never construct raw DB queries directly.

This separation makes each layer independently testable and keeps Mongoose-specific code out of business logic. When adding a new feature, the pattern to follow is: add a repository method for any new DB query, call it from a service, and expose it via a controller route.

Monitoring Flow: From Check to Notification

Background monitoring runs on a scheduled queue, not on the HTTP request cycle. The high-level flow for uptime monitoring is:

Pulse (cron) → BullMQ Job → StatusService
                                 ├── performs HTTP/port/ping check
                                 ├── saves Check via CheckRepository
                                 ├── evaluates monitor state change
                                 │     └── calls IncidentService (create / resolve incident)
                                 └── calls NotificationService (email, Slack, Discord, webhook)
  1. Pulse (cron scheduler) enqueues a job into a BullMQ queue for each active monitor at its configured interval.
  2. A BullMQ worker picks up the job and calls StatusService, which performs the actual check (HTTP request, TCP port probe, ping, etc.).
  3. The result is persisted as a Check document via the repository layer.
  4. StatusService compares the new result against the monitor's previous state. If the monitor transitions from up → down (or down → up), it delegates to IncidentService to open or resolve an Incident document.
  5. On a state change, NotificationService reads the monitor's configured Notification documents and dispatches alerts to all enabled channels (email, Discord, Slack, webhooks).

Queue System (BullMQ + Redis)

Redis serves two roles: job queue storage for BullMQ and ephemeral caching. BullMQ manages concurrency, retries, and backpressure for monitoring jobs, ensuring checks are processed reliably even under load.

  • Each monitor type (HTTP, port, ping, infrastructure) maps to its own queue worker so failures in one type don't block others.
  • Job scheduling interval is driven by the interval field on the Monitor model.
  • Failed jobs are retried with configurable backoff before being moved to a dead-letter state.
  • Redis is also used to cache frequently read data (e.g. aggregated stats) to reduce MongoDB query pressure.

When working on anything related to check scheduling, incident lifecycle, or notifications, trace the flow starting from the relevant BullMQ worker rather than from the controller layer.

Code Conventions

Coding conventions (mandatory)

Read docs/coding-conventions.md before touching any .tsx or .ts file. The doc covers both frontend and backend rules, all enforced in code review.

Universal — rule 0: look at peer files first and follow the established pattern. Don't sneak in novel shapes.

Frontend (client/src):

  1. Prefer MUI native props over sx (e.g. color={…}, bgcolor={…}, mt={…} — not sx={{ color, bgcolor, mt }}).
  2. Use the full theme path for colors: color={theme.palette.text.secondary}, never color="text.secondary" (greppability).
  3. No hardcoded literals — use LAYOUT.*, typographyLevels.*, theme.shape.borderRadius, theme.palette.*.
  4. Use useTheme() inside components; don't import { theme } from "@/Utils/Theme/Theme".
  5. Pair runtime tuples with derived types: const X = [...] as const; type X = (typeof X)[number].

Backend (server/src): 6. Layering: Controller → Service → Repository → Mongoose. No DB calls outside repositories. 7. Provider conventions: DI for stdlib clients, SERVICE_NAME + TIMEOUT_MS constants, timeRequest() helper, inline setTimeout race for timeout, outer try/catch into AppError. 8. Mongoose schema fields with closed value sets must declare enum reusing the same types/* const tuple. 9. Provider tests at server/test/unit/providers/network/<name>.test.ts, from "@jest/globals", testStatusProviderContract, inline setup() per test (not beforeEach). 10. Centralize validation enums in types/* const tuples; never inline z.enum([…]) more than once. 11. New entity fields must land in the validator's *ResponseSchema so the auto-generated OpenAPI spec sees them.

Internationalization

All user-facing strings must use the translation function:

t('your.key')  // Never hardcode UI strings

Branching

  • Always branch from develop (not master)
  • Use descriptive names: feat/add-alerts, fix/login-error
  • PRs target develop branch

Formatting

  • Client: Prettier with printWidth: 90, tabs, double quotes
  • Server: Prettier with printWidth: 150, tabs, double quotes
  • Both use ESLint with strict settings

Testing

Server tests use Jest (with --experimental-vm-modules for ESM):

npm test                              # Run all tests with coverage
npm test -- -t "pattern"              # Run tests matching name pattern
npm test -- path/to/file.test.ts      # Run a specific file

Test files: server/test/**/*.test.ts

Database Models

Key Mongoose models in /server/src/db/models/:

  • Monitor - Monitoring configuration (website, infrastructure, port, etc.)
  • Check - Individual monitoring check results
  • Incident - Downtime incidents
  • User - User accounts
  • Team - Team/workspace management
  • StatusPage - Public status pages
  • Notification - Alert configuration (email, Discord, Slack, webhooks)
  • MaintenanceWindow - Scheduled maintenance periods
  • AppSettings - Global application settings