brainy/docs/PRODUCTION_SERVICE_ARCHITECTURE.md
David Snelling ca9129a924 chore(8.0): modernize toolchain + position Bun as a runtime
Consumer-invisible modernization pass — no public API or runtime-behavior
change; dist for the override-only files is byte-identical.

Toolchain:
- CI: GitHub Actions matrix — Node 22/24 (test:unit) + Bun latest (test:bun).
- engines: node ">=22" (was "22.x"), bun ">=1.1.0".
- tsconfig: isolatedModules + noImplicitOverride; add the 33 `override`
  modifiers the flag requires across storage/integrations/vfs/transaction.
- deps: @types/node ^22; add prettier; drop dead standard-version,
  @rollup/plugin-* and the redundant embedded eslintConfig (flat
  eslint.config.js is the active config — verified identical lint output).

paramValidation: replace the top-level `await import('node:os'/'node:fs')`
with static ESM imports. The top-level-await form poisoned the module graph;
static imports also drop the browser/edge fallback branches no supported
runtime reaches (8.0 is Node/Bun/Deno-only).

Bun positioning: recommend Bun as a runtime (`bun add` / `bun run`), which is
green (test:bun 8/8). Drop single-binary `bun build --compile` as a target —
native addons cannot embed into it, and Bun 1.3.10 has a `--compile` codegen
regression around top-level await. Rename the Bun test to bun-runtime-test.ts
and correct docs that overclaimed single-binary support.

Gates: typecheck 0, build 0, test:unit 1743/1743, test:bun 8/8.
2026-07-01 09:16:46 -07:00

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# Production Service Architecture Guide
**How to use Brainy optimally in production services (Bun, Node.js, Deno)**
> **Recommended Runtime:** [Bun](https://bun.sh) provides best performance with Brainy's Candle WASM engine. All examples work with both Bun and Node.js.
---
## The Problem: Instance-per-Request Anti-Pattern
### ❌ What NOT to Do
```typescript
// WRONG - Creates new instance EVERY request
app.get('/api/entities', async (req, res) => {
const brain = new Brainy({ storage: { path: './brainy-data' } })
await brain.init() // FULL INITIALIZATION EVERY TIME!
const entities = await brain.find(...)
res.json(entities)
})
```
### Why This is Terrible
After 40 API calls:
- **40 Brainy instances** running simultaneously
- **20GB memory** (40 × 500MB per instance)
- **2 seconds wasted** (40 × 50ms initialization)
- **Zero cache benefit** (each instance has its own empty cache)
- **Index rebuilding** on every request (TypeAware HNSW, LSM-trees, etc.)
- **Memory leaks** (old instances may not GC properly)
---
## ✅ The Solution: Singleton Pattern
**ONE Brainy instance per service, shared across ALL requests.**
### Performance Comparison
| Metric | Instance-per-Request | Singleton (Optimal) |
|--------|---------------------|---------------------|
| Memory (40 requests) | 20GB | 500MB |
| Request 1 latency | 60ms | 60ms (one-time init) |
| Request 2+ latency | 60ms (no cache!) | 2ms (80% cache hit!) |
| Cache hit rate | 0% | 80%+ |
| Speedup | - | **30x faster** |
---
## Implementation Patterns
### Pattern 1: Simple Singleton (Recommended)
```typescript
// server.ts
import { Brainy } from '@soulcraft/brainy'
// SINGLETON INSTANCE
let brainInstance: Brainy | null = null
async function getBrain(): Promise<Brainy> {
if (brainInstance) {
return brainInstance
}
console.log('🧠 Initializing Brainy singleton...')
brainInstance = new Brainy({
storage: {
path: './brainy-data',
autoOptimize: true
},
cache: {
maxSize: 1000, // Shared across ALL requests
ttl: 3600000, // 1 hour
enableMetrics: true
},
augmentations: {
include: ['cache', 'metrics', 'display', 'vfs']
}
})
await brainInstance.init()
console.log('✅ Brainy ready')
return brainInstance
}
// Initialize BEFORE starting server
async function startServer() {
await getBrain() // One-time initialization
app.get('/api/entities', async (req, res) => {
const brain = await getBrain() // Reuses same instance!
const entities = await brain.find(req.query)
res.json(entities)
})
app.listen(3000)
}
startServer()
```
**Benefits:**
- ✅ Simple to implement
- ✅ Thread-safe (async initialization)
- ✅ Shared cache and indexes
- ✅ 40x memory reduction
---
### Pattern 2: Service Class (Production-Grade)
```typescript
// services/BrainService.ts
export class BrainService {
private brain: Brainy | null = null
private initPromise: Promise<Brainy> | null = null
async getInstance(): Promise<Brainy> {
if (this.brain) return this.brain
if (this.initPromise) return this.initPromise
this.initPromise = this.initialize()
return this.initPromise
}
private async initialize(): Promise<Brainy> {
this.brain = new Brainy({
storage: {
path: process.env.BRAINY_DATA_PATH || './brainy-data'
},
cache: { maxSize: 1000, ttl: 3600000 }
})
await this.brain.init()
return this.brain
}
async shutdown(): Promise<void> {
if (this.brain) {
// Cleanup if needed
this.brain = null
}
}
}
// server.ts
const brainService = new BrainService()
app.get('/api/entities', async (req, res) => {
const brain = await brainService.getInstance()
const entities = await brain.find(req.query)
res.json(entities)
})
// Graceful shutdown
process.on('SIGTERM', async () => {
await brainService.shutdown()
process.exit(0)
})
```
**Benefits:**
- ✅ Prevents race conditions (multiple simultaneous inits)
- ✅ Testable (can inject mock)
- ✅ Clean shutdown handling
- ✅ Environment-configurable
---
### Pattern 3: Bun Server (Recommended)
```typescript
// server.ts - Clean Bun implementation
import { Brainy } from '@soulcraft/brainy'
let brain: Brainy | null = null
async function getBrain(): Promise<Brainy> {
if (!brain) {
brain = new Brainy({ storage: { path: './brainy-data' } })
await brain.init()
}
return brain
}
// Initialize before server starts
await getBrain()
Bun.serve({
port: 3000,
async fetch(req) {
const url = new URL(req.url)
if (url.pathname === '/api/entities') {
const b = await getBrain()
const entities = await b.find({})
return Response.json(entities)
}
if (url.pathname === '/api/entity' && req.method === 'POST') {
const b = await getBrain()
const body = await req.json()
const id = await b.add(body)
return Response.json({ id })
}
return new Response('Not Found', { status: 404 })
}
})
console.log('Server running on http://localhost:3000')
```
**Benefits:**
- ✅ Native Bun runtime performance
- ✅ No framework dependencies
- ✅ Pure WASM — no native binaries, bundler-friendly
- ✅ Built-in TypeScript support
### Pattern 4: Express/Node.js Middleware (Legacy)
```typescript
// middleware/brainy.ts
let brainInstance: Brainy | null = null
export async function initBrainy() {
if (!brainInstance) {
brainInstance = new Brainy({ storage: { path: './brainy-data' } })
await brainInstance.init()
}
}
export function brainMiddleware(req, res, next) {
if (!brainInstance) {
return res.status(500).json({ error: 'Brainy not initialized' })
}
req.brain = brainInstance // Attach to request
next()
}
// Type extension
declare global {
namespace Express {
interface Request {
brain: Brainy
}
}
}
// server.ts
import { initBrainy, brainMiddleware } from './middleware/brainy'
async function startServer() {
await initBrainy() // Initialize first
app.use('/api', brainMiddleware) // Apply to API routes
app.get('/api/entities', async (req, res) => {
const entities = await req.brain.find(req.query) // Type-safe!
res.json(entities)
})
app.listen(3000)
}
```
**Benefits:**
- ✅ Clean separation of concerns
- ✅ Type-safe (`req.brain` is typed)
- ✅ Easy to add auth/validation
---
## Optimization Strategies
### 1. Configure Cache for Your Workload
```typescript
const brain = new Brainy({
cache: {
maxSize: 1000, // Number of entities to cache
ttl: 3600000, // Cache lifetime (1 hour)
enableMetrics: true, // Track hit rate
evictionPolicy: 'lru' // Least recently used
}
})
```
**Cache sizing:**
- Small service (< 100 req/min): `maxSize: 500`
- Medium service (< 1000 req/min): `maxSize: 1000`
- Large service (> 1000 req/min): `maxSize: 5000`
### 2. Lazy Load Augmentations
```typescript
const brain = new Brainy({
augmentations: {
// Only load what you actually use
include: ['cache', 'metrics', 'display', 'vfs'],
exclude: ['neuralImport', 'intelligentImport'] // Skip heavy features
}
})
```
**Memory savings:**
- With all augmentations: ~800MB
- With minimal set: ~400MB
### 3. Warm Up Indexes
```typescript
async function startServer() {
const brain = await getBrain()
// Pre-warm frequently-used indexes
await brain.find({ type: 'person', limit: 1 })
await brain.find({ type: 'organization', limit: 1 })
console.log('✅ Indexes pre-warmed')
app.listen(3000)
}
```
**Benefit:** First requests are fast (no cold-start index building)
### 4. Memory-Aware Configuration
```typescript
import os from 'os'
const totalMemory = os.totalmem()
const availableMemory = os.freemem()
const brain = new Brainy({
cache: {
// Use 10% of total RAM for cache
maxSize: Math.floor(totalMemory * 0.1 / (1024 * 1024))
},
indexes: {
// Lazy load indexes if low memory
lazyLoad: availableMemory < totalMemory * 0.5,
preload: ['person', 'organization'] // Only preload common types
}
})
```
---
## Concurrency & Thread Safety
Brainy is **designed** for concurrent access. A single instance can handle:
```typescript
// Multiple concurrent requests - all using same instance
app.get('/api/read/:id', async (req, res) => {
const brain = getBrain()
const entity = await brain.get(req.params.id) // Safe - no state mutation
res.json(entity)
})
app.post('/api/write', async (req, res) => {
const brain = getBrain()
const id = await brain.add(req.body) // Safe - internal locking
res.json({ id })
})
```
**Concurrency mechanisms:**
-**Read operations**: Lock-free (MVCC)
-**Write operations**: Internal write-ahead logging (WAL)
-**Cache**: Thread-safe LRU implementation
-**Indexes**: Concurrent reads, locked writes
---
## Production Checklist
### Before Deploying
- [ ] **Initialize Brainy on startup** (not per-request)
- [ ] **Configure cache size** based on memory
- [ ] **Only load needed augmentations**
- [ ] **Warm up critical indexes**
- [ ] **Add graceful shutdown handler**
- [ ] **Monitor cache hit rate**
### Code Review Checklist
```typescript
// ❌ BAD - Instance per request
app.get('/api/route', async (req, res) => {
const brain = new Brainy(...) // RED FLAG!
await brain.init() // RED FLAG!
})
// ✅ GOOD - Singleton pattern
app.get('/api/route', async (req, res) => {
const brain = await getBrain() // Reuses instance ✓
})
```
---
## Monitoring & Metrics
```typescript
// Add metrics endpoint
app.get('/api/metrics', (req, res) => {
const brain = getBrain()
res.json({
cache: {
size: brain.cache?.size || 0,
maxSize: brain.cache?.maxSize || 0,
hitRate: brain.metrics?.cacheHitRate || 0 // Target: >70%
},
storage: brain.storage.getStats(),
memory: {
heapUsed: Math.round(process.memoryUsage().heapUsed / 1024 / 1024),
heapTotal: Math.round(process.memoryUsage().heapTotal / 1024 / 1024)
}
})
})
```
**Key metrics to track:**
- **Cache hit rate**: Should be >70% after warm-up
- **Memory usage**: Should stay constant (~500MB for singleton)
- **Request latency**: Should be <10ms for cached entities
---
## Common Pitfalls
### 1. Creating instances in routes
```typescript
// ❌ NEVER do this
app.get('/api/entities', async (req, res) => {
const brain = new Brainy(...) // Creates new instance every time!
})
```
### 2. Not awaiting initialization
```typescript
// ❌ Race condition - server starts before Brainy ready
app.listen(3000)
getBrain() // Async init happens AFTER server starts!
// ✅ Correct - wait for init
await getBrain()
app.listen(3000)
```
### 3. Multiple instances for different purposes
```typescript
// ❌ Wasteful - creates 2 instances
const readBrain = new Brainy(...)
const writeBrain = new Brainy(...)
// ✅ One instance handles both
const brain = new Brainy(...)
await brain.get(id) // Read
await brain.add(data) // Write
```
---
## Migration Guide
### Current (Anti-Pattern)
```typescript
// Probably in multiple route files
async function handler(req, res) {
const brain = new Brainy({ storage: { path: './brainy-data' } })
await brain.init()
// ... use brain
}
```
### Step 1: Create Singleton Module
```typescript
// lib/brainy.ts
let instance: Brainy | null = null
export async function getBrain(): Promise<Brainy> {
if (!instance) {
instance = new Brainy({ storage: { path: './brainy-data' } })
await instance.init()
}
return instance
}
```
### Step 2: Update Server Startup
```typescript
// server.ts
import { getBrain } from './lib/brainy'
async function startServer() {
// Initialize Brainy FIRST
await getBrain()
console.log('✅ Brainy initialized')
// THEN start server
app.listen(3000)
}
```
### Step 3: Update All Routes
```typescript
// Before
async function handler(req, res) {
const brain = new Brainy(...) // Remove this
await brain.init() // Remove this
// ... rest of code
}
// After
import { getBrain } from './lib/brainy'
async function handler(req, res) {
const brain = await getBrain() // Add this
// ... rest of code stays same
}
```
**Expected results:**
- 40x memory reduction (20GB 500MB)
- 30x faster requests (60ms 2ms average)
- 80%+ cache hit rate
- Your service can scale to 1000s of requests/minute
---
## Summary
**DO:**
- Initialize Brainy ONCE on server startup
- Share single instance across all requests
- Configure cache for your workload
- Monitor cache hit rate
- Handle graceful shutdown
**DON'T:**
- Create new Brainy instance per request
- Create multiple instances
- Start server before Brainy is initialized
- Load augmentations you don't use
**Result:** 40x less memory, 30x faster requests, Brainy optimizations actually work!
---
**Questions? Issues?**
- Report issues: https://github.com/soulcraftlabs/brainy/issues