Understanding Built-in MongoDB Metrics

Introduction

MongoDB provides a set of built-in metrics that help monitor and analyze the performance and health of your MongoDB deployments. This guide explains key built-in metrics and how to use them effectively.

Accessing Metrics

You can access MongoDB metrics using the serverStatus and dbStats commands. These commands provide detailed information about the server and database status.

// Example: serverStatus command
db.serverStatus()

// Example: dbStats command
db.stats()
                

Key Metrics

1. Connections

The connections metrics provide information about the number of current and available connections to the MongoDB server.

db.serverStatus().connections

2. Memory Usage

The mem metrics provide information about the server's memory usage, including resident, virtual, and mapped memory.

db.serverStatus().mem

3. Document Operations

The opcounters metrics provide information about the number of insert, query, update, delete, and getmore operations performed by the server.

db.serverStatus().opcounters

4. Locks

The locks metrics provide information about the locks held and acquired by the server, including the time spent holding locks.

db.serverStatus().locks

5. Index Metrics

The indexCounters metrics provide information about index access operations, including hits, misses, and resets.

db.serverStatus().indexCounters

Example: Monitoring Memory Usage

Here's an example of how to monitor memory usage using the MongoDB shell:

const memStats = db.serverStatus().mem;
print(`Resident Memory: ${memStats.resident} MB`);
print(`Virtual Memory: ${memStats.virtual} MB`);
print(`Mapped Memory: ${memStats.mapped} MB`);
                

Conclusion

Understanding and utilizing MongoDB's built-in metrics is essential for maintaining the performance and health of your MongoDB deployments. By regularly monitoring these metrics, you can identify and address potential issues before they impact your applications.