Memory Leak in Adonisjs

Memory leaks in Adonisjs applications typically occur through improper handling of database connections, event listeners, and middleware chains. The framework's elegant async/await patterns can mask resource retention when developers don't properly clean up after operations.

A common Adonisjs-specific pattern involves event listeners in service providers. Consider this problematic code:

class UserService {
  constructor () {
    Event.on('user.created', this.handleUserCreated)
  }

  handleUserCreated (user) {
    // Processing logic
  }
}

class UserController {
  async store ({ request, response }) {
    const user = await User.create(request.all())
    Event.fire('user.created', user)
    return response.status(201).json(user)
  }
}

The issue: the event listener is bound to the class instance but never removed. Each HTTP request creates a new UserController instance, but the listener persists in memory, causing exponential growth.

Another Adonisjs-specific leak occurs with database query builders. The framework's Lucid ORM maintains internal caches:

class AnalyticsController {
  async index ({ response }) {
    const data = await Database
      .query('analytics_data')
', DateTime.local().minus({ days: 30 }))
      .fetch()

    // Missing: data.toJSON() forces full materialization
    return response.json(data)
  }
}

The query builder holds references to large result sets. Without proper materialization using .toJSON(), the ORM keeps database connections and result buffers alive longer than necessary.

Middleware chains in Adonisjs can also create leaks when async operations aren't properly awaited:

class AuthMiddleware {
  async handle ({ auth }, next) {
    const user = await auth.getUser()
    next()
  }
}

This pattern prevents the request lifecycle from completing, leaving HTTP connections and memory buffers allocated indefinitely.

Detecting memory leaks in Adonisjs requires understanding the framework's runtime behavior. The Node.js --inspect flag combined with Chrome DevTools provides the most effective approach:

node --inspect=0.0.0.0:9229 server.js

Once connected, use the Memory tab to take heap snapshots. Look for these Adonisjs-specific patterns:

• Increasing counts of EventEmitter instances
• Growing lucid model caches
• Accumulating HttpContext objects
• Expanding ServiceManager instances

middleBrick's API security scanner can identify memory-related vulnerabilities through its black-box scanning approach. For Adonisjs applications, it specifically tests:

middlebrick scan https://your-adonisjs-app.com/api/v1/users

The scanner detects patterns like:

• Unbounded response payloads that could exhaust client memory
• Missing rate limiting on resource-intensive endpoints
• API endpoints that don't properly handle connection termination

middleBrick's LLM security module also checks for memory-related issues in AI endpoints, testing for excessive agency patterns that could lead to resource exhaustion.

For production monitoring, Adonisjs's built-in profiler can track memory usage per request:

const { Profiler } = use('@adonisjs/profiler')

class UserController {
  async index ({ response }) {
    const profile = Profiler.create('user.index', this)
    const users = await User.all()
    profile.end()
    return response.json(users)
  }
}

This helps identify which endpoints consume the most memory over time.

Fixing memory leaks in Adonisjs requires leveraging the framework's lifecycle hooks and proper async patterns. For event listeners, use the boot() and shutdown() methods in service providers:

class UserServiceProvider {
  static get name() {
    return 'User'
  }

  boot() {
    this.app.once('adonis:aceCommand', () => {
      Event.on('user.created', this.handleUserCreated.bind(this))
    })
  }

  shutdown() {
    Event.off('user.created', this.handleUserCreated)
  }

  handleUserCreated(user) {
    // Processing logic
  }
}

This ensures listeners are registered once and cleaned up when the application shuts down.

For database operations, always materialize results explicitly:

class AnalyticsController {
  async index ({ response }) {
    const data = await Database
      .query('analytics_data')
', DateTime.local().minus({ days: 30 }))
      .fetch()

    // Proper materialization releases database resources
    const json = data.toJSON()
    return response.json(json)
  }
}

Adonisjs's middleware should use proper async/await patterns:

class AuthMiddleware {
  async handle ({ auth, response }, next) {
    try {
      await auth.check()
      await next()
    } catch (error) {
      return response.status(401).json({ error: 'Unauthorized' })
    }
  }
}

For long-running operations, use Adonisjs's job queue system to prevent request-based memory accumulation:

class UserReportJob {
  static get key() {
    return 'UserReportJob'
  }

  async handle (data) {
    const report = await this.generateReport(data.userId)
    await Mail.send('emails.report', report, (message) => {
      message.to(data.email)
    })
  }
}

// Trigger from controller
await Process.add('UserReportJob', { userId, email })

This moves memory-intensive operations off the request thread.

Implement proper timeout handling for external API calls:

class ExternalApiController {
  async fetchExternalData ({ response }) {
    try {
      const result = await Promise.timeout(
        this.getExternalData(),
      )
      return response.json(result)
    } catch (error) {
      if (error.code === 'ETIMEDOUT') {
        return response.status(504).json({ error: 'Gateway timeout' })
      }
      throw error
    }
  }
}

This prevents hanging connections from consuming memory indefinitely.