Memory Leak in Adonisjs with Dynamodb

AdonisJS is a Node.js web framework that relies on an IoC container and a structured lifecycle for request handling. When integrating AdonisJS with AWS DynamoDB, memory leaks can arise from how SDK clients, query builders, and event emitters are managed across requests. A leak occurs when resources such as database client instances, request-scoped objects, or large payload buffers are retained beyond the request lifecycle and not released.

DynamoDB’s SDK for JavaScript (AWS SDK v3) uses modular clients and paginators that return async iterables. If responses are not fully consumed or iterators are not closed, internal buffers can grow. In AdonisJS, this is common when using the DynamoDBDocumentClient inside services or controllers without ensuring streams are closed or paginator results are fully drained. For example, starting a scan without limiting results or failing to consume all pages keeps internal buffers alive, increasing heap usage over time.

The framework’s lifecycle hooks (e.g., before/after hooks, provider shutdown logic) can inadvertently retain references. If a DynamoDB client is attached to the application container and reused across requests without proper request-bound scoping, accumulated metadata and cached connections can increase memory footprint. Large item scans or queries that return thousands of items and are stored temporarily in arrays also contribute, especially if those arrays are stored on the request object or module-level caches.

Another vector is event-driven patterns. AdonisJS applications often use Event emitters to decouple logic; if DynamoDB operations are triggered inside events and those events are emitted repeatedly without cleaning up listeners, memory usage grows. Unauthenticated LLM endpoint checks are not relevant here, but the risk is that long-running processes accumulate unclosed SDK resources and inflated caches, degrading performance and stability.

Operational visibility helps detect this. middleBrick scans can surface configuration and integration risks, and its OpenAPI/Swagger spec analysis can identify unbounded operations (e.g., unparameterized scans) that may encourage large data pulls. While middleBrick does not fix leaks, its findings can guide safer patterns when integrating DynamoDB with AdonisJS.

To prevent memory leaks when using DynamoDB in AdonisJS, focus on proper client lifecycle, paginator consumption, and avoiding accumulation of large datasets in memory. Below are concrete, realistic code examples.

1. Use a request-scoped DynamoDB client and close paginators

Ensure the DynamoDB client is created per request or properly reused, and always drain async iterators returned by paginators.

// start services/dynamodb.js
const { DynamoDB } = require('@aws-sdk/client-dynamodb');
const { DynamoDBDocumentClient } = require('@aws-sdk/lib-dynamodb');

class DynamoDBService {
  constructor() {
    // Singleton client at module level is acceptable if configured safely
    this.client = new DynamoDB({});
    this.docClient = DynamoDBDocumentClient.from(this.client);
  }

  async scanWithConsumption(tableName) {
    let lastEvaluatedKey;
    const allItems = [];
    do {
      const input = { TableName: tableName, ExclusiveStartKey: lastEvaluatedKey };
      // Consume each page fully to avoid retained internal buffers
      const page = await this.docClient.send(new ScanCommand(input));
      allItems.push(...(page.Items || []));
      lastEvaluatedKey = page.LastEvaluatedKey;
    } while (lastEvaluatedKey);
    return allItems;
  }
}
module.exports = new DynamoDBService();

2. Stream and close async iterators for queries and scans

When using paginators, consume results fully and avoid storing entire pages in long-lived variables. If you only need to process items, stream and release each page promptly.

// In a controller or job
const { DynamoDBDocumentClient, ScanCommand } = require('./dynamodb'); // service above

async function processItems() {
  const service = container.use('DynamoDBService');
  let lastKey;
  do {
    const command = new ScanCommand({ TableName: 'MyTable', ExclusiveStartKey: lastKey });
    const paginator = service.docClient.send(command);
    // Explicitly iterate to ensure buffers are released
    for await (const item of paginator) {
      await handleItem(item); // process item
    }
    // After loop, paginator resources are released when iteration completes
    lastKey = undefined; // ensure we don't reuse stale keys
  } while (false); // controlled by your pagination logic
}

3. Avoid accumulating large datasets in memory

Instead of collecting all items into an array, process items incrementally. If you must collect, enforce limits and release references when done.

async function fetchLimitedItems(tableName, limit = 100) {
  const items = [];
  const command = new ScanCommand({ TableName, Limit: limit });
  const response = await container.use('DynamoDBService').docClient.send(command);
  items.push(...(response.Items || []));
  // Ensure no large retained references
  const result = processItemsSafely(items);
  items.length = 0; // release array content if no longer needed
  return result;
}

4. Manage event listeners and provider lifecycle

If using Event emitters with DynamoDB operations, remove listeners when contexts end. In AdonisJS providers, clean up in the shutdown hook if needed.

// start providers/DynamoDBProvider.js
const Event = use('Event');
class DynamoDBProvider {
  handleShutdown() {
    Event.removeAllListeners('dynamodb:operation');
  }
}

5. Use middleware to bound memory per request

In AdonisJS middleware, avoid storing large DynamoDB responses on the request object. If necessary, stream and transform incrementally.

// start/middleware/limitDynamoMemory.js
async function limitMemory({ request }, next) {
  request.maxDynamoItems = 1000; // enforce sensible defaults
  await next();
  // No need to attach large payloads to request
}

By combining scoped clients, full paginator consumption, incremental processing, and careful listener management, you mitigate memory retention risks when AdonisJS interacts with DynamoDB. middleBrick’s scans can highlight unchecked scan operations or missing pagination constraints, supporting safer integration design.