Monitor MongoDB with mongostat

Benchmark MongoDB with mongotop and mongostat

In this section, you will measure MongoDB’s performance in real time. You will install the official MongoDB database tools, start MongoDB and run a script to simulate heavy load. With the script running you will then measure the database’s live performance using mongotop and mongostat.

Install MongoDB database tools

    

        
        
wget https://fastdl.mongodb.org/tools/db/mongodb-database-tools-ubuntu2404-arm64-100.13.0.deb
sudo apt update
sudo apt install -y ./mongodb-database-tools-ubuntu2404-arm64-100.13.0.deb
echo 'export PATH=$PATH:~/mongodb-database-tools-ubuntu2404-arm64-100.13.0/bin' >> ~/.bashrc
source ~/.bashrc

    

These commands download and unpack MongoDB’s official monitoring tools (mongotop & mongostat), then add them to your PATH so you can run them from any terminal.

Verify the installation

    

        
        
mongostat 2

    

This prints a line every two seconds with key metrics. Press Ctrl+C to stop.

Connect explicitly if needed. If your instance is on a non‑default host or port, provide them:

    

        
        
mongostat --host 127.0.0.1 --port 27017 2

    

Example output

    

        
        insert query update delete getmore command dirty used flushes vsize  res qrw arw net_in net_out conn                time
     8    16      8      8     182     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  34.0k    172k   11 Sep  4 04:57:56.761
     4     8      4      4      98     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  18.3k    116k   11 Sep  4 04:57:58.762
     4     9      4      4      99     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  18.3k    117k   11 Sep  4 04:58:02.760
     8    17      8      8     202     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  37.0k    183k   11 Sep  4 04:58:04.762
     4     9      4      4     103     2|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  19.0k    119k   11 Sep  4 04:58:06.760
     8    15      7      7     183     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  33.5k    171k   11 Sep  4 04:58:08.761
     5    11      5      5     126     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  23.1k    135k   11 Sep  4 04:58:10.760
     6    12      6      6     133     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  24.5k    138k   11 Sep  4 04:58:12.760
     7    14      7      7     190     1|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  34.1k    174k   11 Sep  4 04:58:14.761
insert query update delete getmore command dirty used flushes vsize  res qrw arw net_in net_out conn                time
     4     9      4      4     108     2|0  0.0% 0.0%       0 3.54G 146M 0|0 0|0  19.6k    123k   11 Sep  4 04:58:16.760
     9    18      9      9     220     2|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0  39.7k    195k   11 Sep  4 04:58:18.760
     4     8      4      4     112     0|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0  20.1k    125k   11 Sep  4 04:58:20.762
     7    15      7      7     179     1|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0  32.4k    169k   11 Sep  4 04:58:22.760
     5    11      5      5     158     1|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0  28.1k    155k   11 Sep  4 04:58:24.761
     5     9      4      4     117     2|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0  21.1k    128k   11 Sep  4 04:58:26.761
     4     8      4      4     117     1|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0  20.7k    127k    6 Sep  4 04:58:28.761
    *0    *0     *0     *0       0     0|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0    98b   53.3k    6 Sep  4 04:58:30.762
    *0    *0     *0     *0       0     1|0  0.0% 0.0%       0 3.54G 147M 0|0 0|0    87b   51.0k    3 Sep  4 04:58:32.761

        
    

Explanation of mongostat metrics

• insert - number of document insert operations per second
• query - number of query operations (reads) per second
• update - number of document update operations per second
• delete - number of delete operations per second
• getmore - number of getMore operations per second (used when fetching more results from a cursor)
• command - number of database commands executed per second (e.g., createIndex, count, aggregate)
  • command = number of regular commands | number of getLastError (GLE) commands
• dirty/used - percentage of the WiredTiger cache that is dirty (not yet written to disk) and the percentage actively used
• flushes - how many times data has been flushed to disk (per second)
• vsize - virtual memory size of the mongod process
• res - resident memory size (actual RAM in use)
• qrw arw - queued and active readers/writers
  • qrw = queued read | queued write
  • arw = active read | active write
• net_in/net_out - amount of network traffic coming into (net_in) and going out of (net_out) the database per second
• conn - number of active client connections
• time - timestamp of the sample

Benchmark summary on Arm64

Here is a summary of benchmark results collected on an Arm64 D4ps_v6 Ubuntu Pro 24.04 LTS virtual machine

Highlights from Azure Ubuntu Pro 24.04 LTS Arm64 benchmarking

• insert, query, update, delete rates: throughput remains consistent, with inserts and queries ranging from 5–50 ops/sec, while updates and deletes generally track queries; a workload burst is observed with an insert spike of 404, highlighting MongoDB’s ability to handle sudden surges
• memory usage: resident memory remains stable at 141–145 MB, with virtual memory steady at 3.53–3.54 GB, confirming efficient memory allocation and stability
• network activity: network traffic scales proportionally with workload, with net_in ranging ~18k–96k and net_out ~111k–143k, showing balanced data flow
• connections: active connections hold steady at 10–11, indicating reliable support for concurrent client sessions without instability
• command execution & system load: command executions (0–8) stay minimal, with dirty/used at 0.0% and no flushes recorded, reflecting efficient internal resource handling
• overall system behavior: MongoDB demonstrates stable throughput, predictable memory usage, and balanced network performance, while also showcasing resilience under workload bursts on Arm64

You have now successfully benchmarked MongoDB on an Azure Cobalt 100 Arm64 virtual machine.