A benchmark reported that a plain Node.js WebSocket server on a 1-vCPU, 1-GB DigitalOcean Droplet in Frankfurt held 99,770 connections. That is a measured edge for one setup—not a general capacity promise. The benchmark author’s more cautious planning figure is about 80,000 mostly idle connections per GB, with room left for workload and operating-system overhead.
What did the $6 server actually handle?
In a 2026 article, Remdore reported testing a plain Node.js WebSocket server on a DigitalOcean s-1vcpu-1gb Droplet in Frankfurt. The price in the title refers to the server as described for that test; cloud prices and configurations change, so it should not be read as a current universal price for every 1-GB Droplet. DigitalOcean describes Droplets as Linux virtual machines running on virtualized hardware, with pricing dependent on configuration (DigitalOcean pricing documentation).
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The load came from a separate s-4vcpu-8gb Droplet in the same region. The benchmark author increased the connection count in waves of 5,000, pausing 2.5 seconds between waves, and reported reaching 85,000 connections before testing the upper limit. Both test Droplets were destroyed afterward; the author estimated the experiment cost at about thirty cents.
Why is 80,000 a better planning figure than 99,770?
The reported 99,770 connections mark the benchmark’s maximum, not a comfortable operating target. Near that edge, the server’s ability to accept new connections collapsed, tail latency spiked, and some sampled messages were lost. Remdore recommends treating roughly 80,000 mostly idle connections per GB as a more comfortable planning figure. Even that is a benchmark-derived guide, not a guarantee for another server or workload.
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The progression in the test shows why the maximum is a poor capacity target: at 98,000 connections the reported handshake rate was 3,731 per second; at 99,000 it had fallen to 34 per second; and at 99,770 it was zero. The author measured the ceiling at 99,770 and said the memory-based estimate predicted a limit near 98,500.
Where did the memory go?
Reported process RSS—the memory resident in the Node.js process—grew more slowly than the machine’s overall available memory fell. Remdore estimated about 3.6 KB of process RSS growth per connection and about 6.6 KB of whole-host memory decline per connection in this run. The author attributed the difference to kernel socket buffers that would not appear in process RSS or a heap snapshot. These are estimates from this test, not fixed per-connection constants: operating system, runtime, socket settings, and workload can change the result.
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| Connections | Server RSS reported | Free memory reported | CPU busy reported |
|---|---|---|---|
| 5,000 | 88 MB | 637 MB | 1% |
| 25,000 | 154 MB | 497 MB | 0% |
| 50,000 | 232 MB | 323 MB | 0% |
| 75,000 | 320 MB | 156 MB | 1% |
| 85,000 | 351 MB | 87 MB | 1% |
All figures in the table are measurements reported by Remdore for the Frankfurt test Droplet. They illustrate the run’s memory trend; they should not be extrapolated as a universal memory formula.
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Keeping many mostly idle sockets open is not the same workload as continuously processing messages. Message traffic and new handshakes consume CPU as well as memory, and the article does not establish a capacity figure for a particular message rate, payload size, or production application.
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Median latency also concealed the failure edge. Remdore reported the following samples; message-loss counts are out of the sample sizes given, and the figures are measurements from this run rather than independent replications.
| Connections | p50 latency | p99 latency | Messages lost |
|---|---|---|---|
| 20,000 | 1.0 ms | 27.1 ms | 0 of 100 |
| 40,000 | 0.8 ms | 2.5 ms | 0 of 100 |
| 60,000 | 1.4 ms | 23.3 ms | 0 of 100 |
| 80,000 | 1.0 ms | 9.1 ms | 0 of 100 |
| 99,770 | 2.3 ms | 1,572 ms | 46 of 300 |
At 99,770 connections, four of five external handshake attempts timed out; the one that succeeded took 6.17 seconds, according to the article. A low p50 does not make that condition healthy: p99 latency and message loss show that users can experience serious failures while the median remains comparatively small.
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How to use the benchmark when estimating capacity
Use the result as a starting point for a workload-specific test, not as a sizing rule. Compare candidate deployments under the conditions your application actually needs:
- Memory: Measure whole-host memory as well as process RSS. Do not assume a heap snapshot includes kernel socket memory.
- Traffic: Test representative message rates and payload sizes, alongside idle connections.
- Connection creation: Measure handshake throughput and failure rates, not just the number of established sockets.
- Service quality: Track p99 latency and message loss as well as the median.
- Headroom: Leave a margin below the point where handshakes, latency, or delivery degrade; do not plan to operate at the observed failure edge.
- Test path: Record region and network path, and confirm that the load generator can handle the socket count independently of the server.
The benchmark author described an earlier misleading latency run in which a single Node.js load-generator process was managing a very large number of sockets. A separate laptop test suggested the original client had become a limitation before the server was completely out of capacity. That is a useful warning: a benchmark can measure the client’s ceiling instead of the server’s unless both sides are checked.
What the result does not establish
This single reported run does not show how many connections another region, machine generation, operating system, WebSocket library, kernel configuration, or production application can sustain. It also is not a controlled comparison across cloud providers. DigitalOcean’s documentation describes Droplets and their pricing structure, but it does not validate Remdore’s benchmark or make the result transferable to other configurations.
The practical takeaway is bounded: one plain Node.js server on one Frankfurt 1-vCPU, 1-GB Droplet was reported to hold 99,770 connections at its measured limit, while about 80,000 mostly idle connections per GB is the author’s more cautious planning interpretation. Your own safe number depends on memory consumption, message activity, handshake demand, acceptable tail latency, and the capacity of the test setup.
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