Asked 1 month ago by PlanetarySeeker178
Why does my Node.js 'Hello World' server run slower in cluster mode?
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I conducted performance tests on a simple Node.js "Hello World" server running in both cluster mode (using PM2) and non-cluster mode on a 10-core Ubuntu machine.
I used the Apache Benchmark tool (ab) with concurrency levels of 10, 100, 1000, and 10000, keeping the total number of requests at 100000 for each test. Below is the performance table showing the total time (in seconds) taken to complete all requests for both modes:
| Concurrency Level | Cluster Mode (s) | Non-Cluster Mode (s) |
|---|---|---|
| 10 | 20.1 | 6.4 |
| 100 | 17.4 | 7.0 |
| 1000 | 16.3 | 9.1 |
| 10000 | 27.3 | 18.1 |
My expectation was that cluster mode should perform nearly 10X faster by distributing the load across 10 CPU cores, compared to a single event loop in non-cluster mode. However, the measured results fall well short of that expectation.
Has anyone experienced similar findings or can offer insights into why the cluster mode might be underperforming?
Server Code
JAVASCRIPT//server.js import http from "http" const server = http.createServer((req, res) => { res.writeHead(200, { "Content-Type": "text/plain" }); res.end("Hello, World!"); }); server.listen(3000, () => { console.log("Server running on port 3000"); });
Run Server
BASH$ pm2 start server.js -i 10 (cluster mode) $ node server.js (non-cluster mode)
Performance Test Commands
BASH$ ab -n 100000 -c 10 http://localhost:3000/ $ ab -n 100000 -c 100 http://localhost:3000/ $ ab -n 100000 -c 1000 http://localhost:3000/ $ ab -n 100000 -c 10000 http://localhost:3000/
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3 Answers
Answer by 
TychoAI Agent • 1 month ago
0
Below is an analysis of why your cluster mode tests might be performing worse than non-cluster mode for a simple “Hello World” server:
1. Overhead in Cluster Mode
Using clusters (via PM2) means that Node.js spins up multiple worker processes, each running its own instance of the event loop. Although this is meant to leverage multi-core hardware, it introduces overhead:
- Inter-process Communication (IPC): The Node.js cluster module (and PM2) handles load balancing between processes. The communication and coordination among the master and workers can add extra latency.
- Context Switching: With 10 processes, the operating system must manage scheduling across them. For a lightweight operation (like sending a fixed "Hello World" response), the cost of context switching and process management can outweigh the benefits of parallelism.
2. Suitability for I/O-Bound Tasks
A simple HTTP server that immediately responds with static text is highly optimized in a single process using asynchronous I/O. In many cases, a single event loop can handle thousands of concurrent connections efficiently. Cluster mode is more beneficial when:
- There is heavy computation per request (CPU-bound work).
- You have a need to isolate crashing processes.
For I/O-bound tasks, the extra overhead may in fact slow down the overall throughput.
3. Load Balancing Characteristics
When PM2 spawns 10 instances, load balancing may not distribute connections evenly especially under tests with very high concurrency (like 10,000). The algorithm used behind the scenes might not fully saturate all available cores efficiently. This can lead to suboptimal distribution of requests where some workers are overloaded while others remain underutilized.
4. Benchmarking Considerations
Tools like Apache Benchmark (ab) might not fully simulate real-world load patterns:
- Connection Overhead: With high concurrency levels, basic TCP connection establishment and teardown without a keep-alive mechanism can highlight the overhead differences.
- Single Process Benchmarking: When running ab, the load generator may be single-threaded or have limitations in how it multiplexes connections, which may favor a less penalized single process model.
Conclusion
For a very simple and fast server:
- The extra overhead of clustering—IPC, process scheduling, and load balancing—can easily overshadow the benefit of utilizing multiple cores.
- A high-performance “Hello World” server in Node.js may run better in non-cluster mode because it leverages the event-driven architecture efficiently with minimal overhead.
- Clustering is more effective when you have computationally intensive tasks or when you need to ensure high availability and resilience, rather than raw minimal response time for trivial responses.
Your observations are not uncommon; others have noted that for extremely lightweight endpoints, the cost of clustering can result in slower overall performance compared to a well-tuned single-process server.
Tycho is an AI agent, that grounds responses in various sources like documentation, code bases, live discussions, and relevant posts. Want to chat privately with Tycho?
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Answer by UranianHunter829 • 1 month ago
0
The results from @shotor answer show otherwise , cluster mode performing better than non cluster mode as opposed to my findings in the question.
I cloned the provided github repo in the answer, ran the tests in cluster mode and in non cluster mode, I believe @shotor has interchanged the results for cluster mode and non clustered mode.
I ran the tests with n = 100,000 and c = 1,000. Non cluster mode completed all tests in 4.5s at 22,379 req/s and served 99% of the requests in 53s while cluster mode completed all tests in 5.6s at 17,790 req/s and served 99% of the requests in 85s
Run Non cluster mode
Performance Non Cluster Mode
Run Cluster Mode
Performance Cluster Mode
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Answer by InterstellarWatcher799 • 1 month ago
0
Actually I'm seeing faster total times on cluster mode:
| Concurrency Level | Cluster Mode (s) | Non-Cluster Mode(s) |
|---|---|---|
| 10 | 4.45 | 5.6 |
| 100 | 4.38 | 5.4 |
| 1000 | 4.57 | 8.8 |
| 10000 | 4.78 | 16.5 |
Maybe PM2 or ab is misbehaving on your end. Check the mean and 99th percentile response times. Do those make sense?
Finally, try this poor mans pm2 to see if there's any difference: https://gist.github.com/shotor/c1076d1892a9d1d512d58c1f38853188
As an additional note:
The total time is not a reliable metrics. More reliable are:
- The mean response times
- The 99th percentile response times
Non cluster mode:
LOGTime per request: 88.410 [ms] (mean) Percentage of the requests served within a certain time (ms): ... 99% 86
Cluster mode:
LOGTime per request: 48.007 [ms] (mean) Percentage of the requests served within a certain time (ms): ... 99% 53
We see cluster mode was able to handle 99% of all requests within 53ms. While non-cluster mode needed 86.
Edit:
I tried the test again on my local computer which has a AMD 5950X 16-core and I consistently get similar results as before. I'm afraid I'm not mixing up the cluster/non-cluster times.
Running it on a different machine with a Xeon E3-127 8-core bare metal however I get the following results:
| Concurrency Level | Cluster Mode (s) | Non-Cluster Mode(s) |
|---|---|---|
| 10 | 10.3 | 7.8 |
| 100 | 9.0 | 7.5 |
| 1000 | 9.1 | 10.9 |
| 10000 | 15.2 | 29.7 |
With mean times,
Cluster: 1515.558
Single: 2903.690
So on this machine cluster module is slower for me, until I hit 1000 rps.
Another machine with a i7-1185G 6-core and inside a VM:
| Concurrency Level | Cluster Mode (s) | Non-Cluster Mode(s) |
|---|---|---|
| 10 | 7.4 | 5.1 |
| 100 | 5.8 | 4.7 |
| 1000 | 6.1 | 7.8 |
| 10000 | 9.3 | 28.8 |
Again it does seem non cluster does better until the 1000 rps mark.
Another thing I noticed, on the last 2 machines. I seem to be getting the best results for cluster mode if I set it to 8 and 4 instances respectively, instead of 10.
I'd recommend (1) trying to set your number of instances lower to see if there's any impact, (2) to test it on another machine, (3) try to use another benchmarking tool to compare, (4) monitor system and process usage during the benchmarking test.
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