Integrating APItoolkit with MongoDB

This guide demonstrates how to integrate APItoolkit with MongoDB database operations using OpenTelemetry to monitor performance and identify issues.

Prerequisites

MongoDB database (local or Atlas)
MongoDB client application
APItoolkit account with an API key

Setting Up OpenTelemetry for MongoDB

1. Configure Environment Variables

Set up OpenTelemetry environment variables in your application environment:

# Specifies the endpoint URL for the OpenTelemetry collector
export OTEL_EXPORTER_OTLP_ENDPOINT="http://otelcol.apitoolkit.io:4317"

# Specifies the name of the service
export OTEL_SERVICE_NAME="mongodb-service"

# Adds your API KEY to the resource
export OTEL_RESOURCE_ATTRIBUTES="at-project-key=YOUR_API_KEY"

# Specifies the protocol to use for the OpenTelemetry exporter
export OTEL_EXPORTER_OTLP_PROTOCOL="grpc"

Replace YOUR_API_KEY with your actual APItoolkit project key.

2. Instrument MongoDB Client

Below are examples of MongoDB instrumentation using OpenTelemetry for different programming languages:

Node.js Example (using MongoDB Native Driver)

const { MongoClient } = require('mongodb');
const opentelemetry = require('@opentelemetry/api');

const tracer = opentelemetry.trace.getTracer('mongodb-instrumentation');
const uri = 'mongodb://localhost:27017';
const client = new MongoClient(uri);
const dbName = 'myproject';

async function findDocuments(collection, query = {}) {
  const span = tracer.startSpan('mongodb.query');

  try {
    span.setAttribute('db.system', 'mongodb');
    span.setAttribute('db.name', dbName);
    span.setAttribute('db.operation', 'find');
    span.setAttribute('db.mongodb.collection', collection);
    span.setAttribute('db.statement', JSON.stringify(query));

    await client.connect();
    const db = client.db(dbName);
    const coll = db.collection(collection);

    const documents = await coll.find(query).toArray();

    span.setAttribute('db.result_count', documents.length);
    return documents;
  } catch (error) {
    span.recordException(error);
    throw error;
  } finally {
    span.end();
  }
}

async function insertDocument(collection, document) {
  const span = tracer.startSpan('mongodb.insert');

  try {
    span.setAttribute('db.system', 'mongodb');
    span.setAttribute('db.name', dbName);
    span.setAttribute('db.operation', 'insert');
    span.setAttribute('db.mongodb.collection', collection);

    await client.connect();
    const db = client.db(dbName);
    const coll = db.collection(collection);

    const result = await coll.insertOne(document);

    span.setAttribute('db.mongodb.inserted_id', result.insertedId.toString());
    return result;
  } catch (error) {
    span.recordException(error);
    throw error;
  } finally {
    span.end();
  }
}

Java Example (using MongoDB Java Driver)

import com.mongodb.client.MongoClient;
import com.mongodb.client.MongoClients;
import com.mongodb.client.MongoCollection;
import com.mongodb.client.MongoDatabase;
import io.opentelemetry.api.GlobalOpenTelemetry;
import io.opentelemetry.api.trace.Span;
import io.opentelemetry.api.trace.Tracer;
import org.bson.Document;

import java.util.ArrayList;
import java.util.List;

public class MongoDBExample {
    private final Tracer tracer = GlobalOpenTelemetry.getTracer("mongodb-instrumentation");
    private final MongoClient mongoClient = MongoClients.create("mongodb://localhost:27017");
    private final MongoDatabase database = mongoClient.getDatabase("myproject");

    public List<Document> findDocuments(String collectionName, Document query) {
        Span span = tracer.spanBuilder("mongodb.query").startSpan();
        try {
            span.setAttribute("db.system", "mongodb");
            span.setAttribute("db.name", "myproject");
            span.setAttribute("db.operation", "find");
            span.setAttribute("db.mongodb.collection", collectionName);
            span.setAttribute("db.statement", query.toJson());

            MongoCollection<Document> collection = database.getCollection(collectionName);
            List<Document> documents = new ArrayList<>();

            collection.find(query).into(documents);

            span.setAttribute("db.result_count", documents.size());
            return documents;
        } catch (Exception e) {
            span.recordException(e);
            throw e;
        } finally {
            span.end();
        }
    }

    public void insertDocument(String collectionName, Document document) {
        Span span = tracer.spanBuilder("mongodb.insert").startSpan();
        try {
            span.setAttribute("db.system", "mongodb");
            span.setAttribute("db.name", "myproject");
            span.setAttribute("db.operation", "insert");
            span.setAttribute("db.mongodb.collection", collectionName);

            MongoCollection<Document> collection = database.getCollection(collectionName);
            collection.insertOne(document);

            span.setAttribute("db.mongodb.inserted_id", document.getObjectId("_id").toString());
        } catch (Exception e) {
            span.recordException(e);
            throw e;
        } finally {
            span.end();
        }
    }
}

3. Using OpenTelemetry Auto-Instrumentation Libraries

For easier integration, you can use auto-instrumentation libraries:

Node.js Auto-Instrumentation

Install required packages:

npm install @opentelemetry/sdk-node @opentelemetry/auto-instrumentations-node @opentelemetry/exporter-trace-otlp-proto

Set up auto-instrumentation in your application:

const { NodeSDK } = require('@opentelemetry/sdk-node');
const { getNodeAutoInstrumentations } = require('@opentelemetry/auto-instrumentations-node');
const { OTLPTraceExporter } = require('@opentelemetry/exporter-trace-otlp-proto');

const sdk = new NodeSDK({
  traceExporter: new OTLPTraceExporter({
    url: 'http://otelcol.apitoolkit.io:4317/v1/traces',
  }),
  instrumentations: [getNodeAutoInstrumentations()],
  resourceAttributes: {
    'at-project-key': 'YOUR_API_KEY',
    'service.name': 'mongodb-service',
  },
});

// Initialize the SDK before importing MongoDB
sdk.start();

// Now it's safe to import and use MongoDB
const { MongoClient } = require('mongodb');

Java Auto-Instrumentation (using Java Agent)

Download the OpenTelemetry Java agent:

wget https://github.com/open-telemetry/opentelemetry-java-instrumentation/releases/latest/download/opentelemetry-javaagent.jar

Run your application with the agent:

java -javaagent:path/to/opentelemetry-javaagent.jar \
     -Dotel.service.name=mongodb-service \
     -Dotel.exporter.otlp.endpoint=http://otelcol.apitoolkit.io:4317 \
     -Dotel.resource.attributes=at-project-key=YOUR_API_KEY \
     -jar your-application.jar

Advanced MongoDB Monitoring

Tracking Slow Queries

To track slow queries, you can enable MongoDB’s profiler:

const enableProfiling = async () => {
  const span = tracer.startSpan('mongodb.profiler.enable');
  try {
    const db = client.db(dbName);
    // Set profiling level: 0 = off, 1 = slow queries, 2 = all
    await db.command({ profile: 1, slowms: 100 });

    // Schedule a check for slow queries
    setInterval(checkSlowQueries, 60000);
  } catch (error) {
    span.recordException(error);
  } finally {
    span.end();
  }
};

const checkSlowQueries = async () => {
  const span = tracer.startSpan('mongodb.profiler.check');
  try {
    const db = client.db(dbName);
    const slowQueries = await db.collection('system.profile').find({}).toArray();

    for (const query of slowQueries) {
      const querySpan = tracer.startSpan('mongodb.slow_query');
      querySpan.setAttribute('db.mongodb.operation', query.op);
      querySpan.setAttribute('db.mongodb.collection', query.ns.split('.').pop());
      querySpan.setAttribute('db.mongodb.query', JSON.stringify(query.query || query.command));
      querySpan.setAttribute('db.mongodb.execution_time_ms', query.millis);
      querySpan.setAttribute('db.mongodb.scanned_objects', query.nscanned || 0);
      querySpan.setAttribute('db.mongodb.returned_objects', query.nreturned || 0);
      querySpan.end();
    }
  } catch (error) {
    span.recordException(error);
  } finally {
    span.end();
  }
};

Monitoring MongoDB Server Stats

const collectServerStats = async () => {
  const span = tracer.startSpan('mongodb.server_stats');
  try {
    const db = client.db('admin');
    const stats = await db.command({ serverStatus: 1 });

    // Record key metrics
    span.setAttribute('mongodb.connections.current', stats.connections.current);
    span.setAttribute('mongodb.connections.available', stats.connections.available);
    span.setAttribute('mongodb.opcounters.insert', stats.opcounters.insert);
    span.setAttribute('mongodb.opcounters.query', stats.opcounters.query);
    span.setAttribute('mongodb.opcounters.update', stats.opcounters.update);
    span.setAttribute('mongodb.opcounters.delete', stats.opcounters.delete);
    span.setAttribute('mongodb.memory.resident_mb', stats.mem.resident);
    span.setAttribute('mongodb.memory.virtual_mb', stats.mem.virtual);

    return stats;
  } catch (error) {
    span.recordException(error);
  } finally {
    span.end();
  }
};

// Collect server stats every minute
setInterval(collectServerStats, 60000);

Verifying the Setup

After setting up OpenTelemetry with your MongoDB application:

Run your application and perform several database operations
Check your APItoolkit dashboard to see the incoming telemetry data
Look for metrics such as: - Query execution time - Collection operation counts - Error rates - Result set sizes

Next Steps

Set up alerting in APItoolkit for slow MongoDB queries
Create custom dashboards for MongoDB performance monitoring
Correlate database operations with API endpoints to identify bottlenecks