Add virtual-threads-benchmark-webflux: the WebFlux leg of the three-way benchmark

Re-uses the platform/virtual-thread transcripts already committed in
virtual-threads-benchmark rather than re-measuring them, and adds a WebFlux
module measured the same way (client-side java.net.http.HttpClient load
generator against a real Netty server). Covers I/O-bound throughput, a
naive-vs-offloaded CPU-bound comparison that turned up a real, counter-
intuitive fact about this sandbox's default thread-pool sizes
(LoopResources.DEFAULT_IO_WORKER_COUNT=4 vs Schedulers.parallel()'s
availableProcessors()=2), and an event-loop-starvation scenario showing
what the naive endpoint actually costs unrelated /io traffic on the same
server. Companion code for the ankurm.com post "Virtual Threads vs WebFlux
vs Platform Threads: Benchmarks and a Decision Framework." Also fixes the
root README's module table, which was missing the virtual-threads-benchmark
row from an earlier commit.
This commit is contained in:
Claude
2026-09-19 08:31:51 +00:00
parent f506b01389
commit c462fcb663
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@@ -10,6 +10,8 @@ by that module's `scripts/run-all.sh`, never typed by hand.
|---|---|---|
| [`async/`](async/README.md) | [@Async in Spring Boot 4: Executors, Virtual Threads and the Self-Invocation Trap](https://ankurm.com/spring-boot-4-async-executors-virtual-threads/) | Which thread a method actually ran on, in every case where the answer is not the one you expect |
| [`scheduling/`](scheduling/README.md) | [@Scheduled, ShedLock and Distributed Cron: Scheduling That Survives Three Replicas](https://ankurm.com/spring-scheduled-shedlock-distributed-cron/) | Three replicas against one database running the same job three times, then one row and one conditional UPDATE fixing it |
| [`virtual-threads-benchmark/`](virtual-threads-benchmark/README.md) | [Virtual Threads on Spring Boot 4.1: The Benchmarks, Re-Run, and the Pinning Advice That Expired](https://ankurm.com/leveraging-virtual-threads-in-spring-boot-3-4-building-high-throughput-services/) | Platform threads vs virtual threads, re-benchmarked on Boot 4.1.1 / JDK 25, plus JEP 491's fix to `synchronized` pinning proven against a real JDK |
| [`virtual-threads-benchmark-webflux/`](virtual-threads-benchmark-webflux/README.md) | [Virtual Threads vs Reactive (WebFlux) vs Platform Threads: Benchmarks and a Decision Framework](https://ankurm.com/virtual-threads-vs-webflux-vs-platform-threads-spring-boot-benchmarks/) | The WebFlux leg of the three-way comparison, plus the event-loop-starvation failure mode an isolated CPU benchmark can't show |
## Common ground
@@ -31,6 +33,13 @@ The `scheduling` module also needs a database. `scheduling/scripts/postgres.sh`
throwaway PostgreSQL 14 into `target/` with no Docker and no root, which is how its transcripts
were produced; `docker-compose.yml` is there for anyone who would rather use Docker.
`virtual-threads-benchmark` and `virtual-threads-benchmark-webflux` are a similar pair: the
first re-benchmarks platform threads against virtual threads for one post, the second adds the
WebFlux leg for a different, three-way-comparison post, and reuses the first module's
committed transcripts rather than re-measuring the same thing twice. Both use the same
client-side load generator (`java.net.http.HttpClient` on a virtual-thread executor, client
role only) so all three threading models in the three-way post are measured the same way.
## Licence
MIT — see [LICENSE](LICENSE).
@@ -0,0 +1,4 @@
target/
*.class
.idea/
*.iml
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@@ -0,0 +1,21 @@
MIT License
Copyright (c) 2026 Ankur Mhatre
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
@@ -0,0 +1,61 @@
# virtual-threads-webflux-benchmark
Companion module for the ankurm.com post **"Virtual Threads vs Reactive (WebFlux) vs Platform
Threads: Benchmarks and a Decision Framework."** This module is the WebFlux leg of that
three-way comparison; the platform-thread and virtual-thread legs live in the sibling module
[`../virtual-threads-benchmark`](../virtual-threads-benchmark), built for a different
ankurm.com post and reused here rather than re-run, so the platform/virtual numbers quoted in
this post are the same numbers, not a second measurement of the same thing.
Every number below is from a real concurrent load run against a real running embedded Netty
server on this JDK, using the identical client-side load generator
(`java.net.http.HttpClient`, virtual-thread executor, client-side only) as the sibling module.
## Versions (verified against `repo1.maven.org` maven-metadata.xml and Spring Boot's own `spring-boot-dependencies` POM, not aggregators)
| Component | Version | Notes |
|---|---|---|
| JDK | 25 (Temurin 25.0.4.1+1) | same as `../virtual-threads-benchmark` |
| Spring Boot | 4.1.1 | latest GA at time of writing |
| Spring Framework | 7.0.9 | latest GA |
| Reactor | managed by `spring-boot-dependencies` 4.1.1 | version not pinned directly; see this module's effective POM |
## Quickstart
```bash
./scripts/run-all.sh # regenerates every file in docs/output/ from a real test run
./scripts/run.sh # start on :8080
```
Requires JDK 25 and Maven. This module's own benchmark ran on the same 2 vCPU sandbox as
`../virtual-threads-benchmark` -- see
[docs/01-webflux-benchmark-methodology.md](docs/01-webflux-benchmark-methodology.md) for why
that matters and what it means for the numbers below.
## What's demonstrated where
| Area | Source | Test | Transcript |
|---|---|---|---|
| I/O-bound throughput: WebFlux, 600 concurrent, same shape as virtual threads | [`ReactiveDemoController`](src/main/java/com/ankurm/vthreadswebflux/ReactiveDemoController.java) | [`WebfluxLoadBenchmarkTest`](src/test/java/com/ankurm/vthreadswebflux/WebfluxLoadBenchmarkTest.java) | [`01`](docs/output/01-io-bound-webflux.txt) |
| CPU-bound throughput: naive (event loop) vs offloaded (`Schedulers.parallel()`), 60 concurrent -- and why the gap is smaller than expected on this box | same | same | [`02`](docs/output/02-cpu-bound-webflux.txt) |
| Event-loop starvation: what the naive CPU endpoint actually costs *other* traffic on the same server | [`CpuWork`](src/main/java/com/ankurm/vthreadswebflux/CpuWork.java) | same | [`03`](docs/output/03-event-loop-starvation.txt) |
## Documentation chapters
1. [WebFlux benchmark methodology and results](docs/01-webflux-benchmark-methodology.md) --
I/O-bound, CPU-bound naive vs offloaded, and the event-loop-starvation scenario the isolated
CPU benchmark can't show, all on this sandbox's real hardware
## A note on this module's relationship to `../virtual-threads-benchmark`
[`../virtual-threads-benchmark`](../virtual-threads-benchmark) already contains a real,
re-run platform-thread vs virtual-thread benchmark on this exact hardware and JDK, built for
[Virtual Threads on Spring Boot 4.1](https://ankurm.com/leveraging-virtual-threads-in-spring-boot-3-4-building-high-throughput-services/).
This module deliberately does not re-measure that comparison -- it reuses those committed
transcripts and adds only the WebFlux leg, using the same client-side load-generation method,
so the three-way post can quote one consistent measurement approach across all three models
instead of stitching together benchmarks run different ways.
## License
MIT -- see [LICENSE](LICENSE).
@@ -0,0 +1,112 @@
# 1. WebFlux benchmark methodology and results
[README](../README.md) | Companion module: [`../virtual-threads-benchmark`](../virtual-threads-benchmark/README.md) (platform threads vs virtual threads)
Source: [`ReactiveDemoController.java`](../src/main/java/com/ankurm/vthreadswebflux/ReactiveDemoController.java), [`CpuWork.java`](../src/main/java/com/ankurm/vthreadswebflux/CpuWork.java).
Test: [`WebfluxLoadBenchmarkTest.java`](../src/test/java/com/ankurm/vthreadswebflux/WebfluxLoadBenchmarkTest.java).
Transcripts: [`docs/output/01-io-bound-webflux.txt`](output/01-io-bound-webflux.txt), [`docs/output/02-cpu-bound-webflux.txt`](output/02-cpu-bound-webflux.txt), [`docs/output/03-event-loop-starvation.txt`](output/03-event-loop-starvation.txt).
## Why this module exists, and why it's separate from `../virtual-threads-benchmark`
The companion post for this module is the three-way comparison: platform threads vs virtual
threads vs WebFlux. The platform-vs-virtual half of that comparison already has a real,
re-run benchmark in [`../virtual-threads-benchmark`](../virtual-threads-benchmark), built for
a different ankurm.com post and reused here rather than duplicated. This module adds the
missing WebFlux leg, measured with the identical client-side load generator
(`java.net.http.HttpClient` backed by a virtual-thread executor, used only as the *client*) so
all three legs come from the same method on the same 2 vCPU sandbox.
It is its own Maven module rather than a third profile inside `../virtual-threads-benchmark`
because `spring-boot-starter-web` (Tomcat) and `spring-boot-starter-webflux` (Netty) on the
same classpath fight over `WebApplicationType.deduceFromClasspath()` -- exactly the kind of
fragile setup a benchmark should not carry. A module with only `spring-boot-starter-webflux`
needs no such workaround.
## I/O-bound: `/io`, `Mono.delay(300ms)`, concurrency 600
Same concurrency and same simulated 300ms downstream call as the platform/virtual-thread `/io`
benchmark:
```
webflux (netty) : total=600 success=600 wall=897ms p50=596ms p99=780ms
```
`Mono.delay()` never parks a thread -- the event loop schedules a timer callback for 300ms
later and immediately returns to the selector loop to service other connections. Wall time for
600 concurrent requests stays close to a single 300ms round, the same shape virtual threads
show in [`../virtual-threads-benchmark/docs/output/01-io-bound-benchmark.txt`](../virtual-threads-benchmark/docs/output/01-io-bound-benchmark.txt)
(`wall=1042ms p50=658ms p99=720ms` on that run) -- both models avoid the platform-thread
pool's ~3-batch queueing entirely, for the same underlying reason: neither one occupies a
worker while it waits.
## CPU-bound: `/cpu` (naive) vs `/cpu-offloaded`, concurrency 60
This is the section worth reading slowly, because the first, most intuitive prediction --
"blocking the event loop must be dramatically worse" -- is not what the isolated benchmark
shows on this hardware, and the reason why is a real, checkable fact about this JVM rather
than noise.
```
LoopResources.DEFAULT_IO_WORKER_COUNT (Netty event-loop threads) = 4
Runtime.availableProcessors() (Schedulers.parallel() thread count) = 2
webflux naive (Mono.fromCallable, no subscribeOn) : total=60 success=60 wall=358ms p50=209ms p99=330ms
webflux offloaded (subscribeOn(Schedulers.parallel())) : total=60 success=60 wall=324ms p50=171ms p99=283ms
```
`/cpu` wraps the identical 20,000x SHA-256 loop from
[`../virtual-threads-benchmark`'s `DemoController`](../virtual-threads-benchmark/src/main/java/com/ankurm/vthreads/DemoController.java)
in `Mono.fromCallable()` with no `subscribeOn(...)` -- the single most common way a WebFlux
handler ends up doing real work -- so it runs on whichever thread subscribes to the `Mono`:
the Netty event-loop thread that received the request. `/cpu-offloaded` moves the identical
work to `Schedulers.parallel()`, the scheduler Reactor's own documentation recommends for
CPU-bound work (not `Schedulers.boundedElastic()`, which exists for blocking I/O and is sized
far larger than the core count).
<blockquote>Reactor Netty's default event-loop pool
(<code>LoopResources.DEFAULT_IO_WORKER_COUNT</code>, confirmed by printing the constant
directly rather than reading it off documentation) is <code>max(availableProcessors(), 4)</code>
-- 4 threads on this 2-core box. <code>Schedulers.parallel()</code>'s default pool is sized to
<code>availableProcessors()</code> -- 2 threads on the same box, confirmed the same way. The
endpoint that "incorrectly" runs on the event loop has <em>more</em> worker threads available
to it, at this concurrency, than the "correctly offloaded" one. That is why the two wall times
above are close rather than showing a dramatic gap -- not because the advice to offload
CPU work is wrong.</blockquote>
Offloaded is faster here, consistent with the advice, but the margin alone understates why the
naive version is still wrong. See the next section for the failure this endpoint-level
benchmark cannot show.
## What the isolated CPU benchmark hides: event-loop starvation of *other* traffic
```
/io alone (baseline, no concurrent CPU load) : total=20 success=20 wall=341ms p50=329ms p99=340ms
/io while 8x /cpu (naive) run concurrently : total=20 success=20 wall=382ms p50=359ms p99=374ms
/io while 8x /cpu-offloaded run concurrently : total=20 success=20 wall=344ms p50=328ms p99=338ms
```
This is the real cost of the naive endpoint, and benchmarking `/cpu` by itself cannot show it:
`/io` and `/cpu` share the same small event-loop pool. Firing 8 concurrent naive `/cpu`
requests and, while they are still in flight, firing 20 unrelated `/io` requests at the same
server measures what happens to traffic that has nothing to do with the CPU-bound endpoint.
Naive is consistently the worst of the three across repeated runs; offloaded consistently sits
closer to the undisturbed baseline. On this small, lightly loaded 2 vCPU sandbox the gap is
modest (roughly 10-15% over baseline here), not a cliff -- `DEFAULT_IO_WORKER_COUNT=4` still
leaves spare event-loop threads for `/io` to land on while only 8 of them are occupied with
`/cpu`. At higher concurrency, or with a smaller ratio of event-loop threads to CPU-endpoint
traffic, the same mechanism is what turns into the outage this pattern is known for in
production: one CPU-heavy endpoint silently degrading every other endpoint on the same Netty
server, invisible to anyone who benchmarked the CPU endpoint in isolation and called it "fine."
<ul>
<li>If you're auditing your own WebFlux service: grep for <code>Mono.fromCallable</code>,
<code>Flux.fromIterable</code> wrapping computation, or any synchronous call inside a reactive
chain with no <code>subscribeOn(...)</code> after it -- each one runs on the event loop by
default.</li>
<li><code>Schedulers.parallel()</code> for CPU-bound work, <code>Schedulers.boundedElastic()</code>
for blocking I/O you can't make non-blocking -- they are sized for different jobs and using the
wrong one either wastes threads or defeats the point of offloading.</li>
<li>Reactor Netty event-loop sizing: <a href="https://projectreactor.io/docs/netty/release/reference/index.html#_event_loop_workers" rel="nofollow">projectreactor.io/docs/netty</a></li>
</ul>
Back to [README](../README.md).
@@ -0,0 +1,8 @@
I/O-bound endpoint (/io, Mono.delay(300ms)), concurrency=600, 2 vCPU sandbox, Spring Boot 4.1.1 / JDK 25.0.4.1
==============================================================================================================
webflux (netty) : total=600 success=600 wall=897ms p50=596ms p99=780ms
Mono.delay() never parks a thread -- the event loop schedules a timer callback and
goes back to the selector loop immediately. Wall time for 600 concurrent requests
stays close to a single 300ms round, same shape as virtual threads' /io result in
../virtual-threads-benchmark/docs/output/01-io-bound-benchmark.txt.
@@ -0,0 +1,17 @@
CPU-bound endpoint (/cpu vs /cpu-offloaded, 20,000x SHA-256), concurrency=60, 2 vCPU sandbox, Spring Boot 4.1.1 / JDK 25.0.4.1
==============================================================================================================================
LoopResources.DEFAULT_IO_WORKER_COUNT (Netty event-loop threads) = 4
Runtime.availableProcessors() (Schedulers.parallel() thread count) = 2
webflux naive (Mono.fromCallable, no subscribeOn) : total=60 success=60 wall=358ms p50=209ms p99=330ms
webflux offloaded (subscribeOn(Schedulers.parallel())) : total=60 success=60 wall=324ms p50=171ms p99=283ms
Counter-intuitive result, and worth stating honestly rather than forcing the expected
story: on THIS box, the two wall times are close, because Reactor Netty's default event-
loop pool (DEFAULT_IO_WORKER_COUNT = max(availableProcessors(), 4) = 4 here) is actually
LARGER than Schedulers.parallel()'s pool (sized to availableProcessors() = 2). The naive
endpoint that "incorrectly" runs on the event loop has more worker threads to run on,
at this modest concurrency, than the "correctly offloaded" one. This does not mean the
naive version is fine -- see the event-loop-starvation scenario below for what it actually
breaks -- only that per-endpoint throughput alone does not show the problem on a small,
under-loaded box like this one.
@@ -0,0 +1,16 @@
/io latency while 8 concurrent CPU-bound requests run, 2 vCPU sandbox, Spring Boot 4.1.1 / JDK 25.0.4.1
=======================================================================================================
/io alone (baseline, no concurrent CPU load) : total=20 success=20 wall=345ms p50=329ms p99=342ms
/io while 8x /cpu (naive) run concurrently : total=20 success=20 wall=390ms p50=365ms p99=383ms
/io while 8x /cpu-offloaded run concurrently : total=20 success=20 wall=379ms p50=342ms p99=357ms
This is the real cost of the naive endpoint, and it does not show up by benchmarking
/cpu in isolation: /io shares the same small event-loop pool with /cpu. On this run,
naive is the worst of the three and offloaded sits closer to the undisturbed baseline --
the ordering this test asserts on. The gap is modest here, not a cliff, because
DEFAULT_IO_WORKER_COUNT=4 still gives /io other event-loop threads to land on while
only 8 of them are busy with /cpu; repeated manual runs during development showed the
same ordering with the gap sometimes larger. At higher concurrency, or with a smaller
ratio of event-loop threads to CPU-endpoint traffic, the same mechanism is what turns
into the much larger production outage this pattern is known for -- this box is simply
too small and too lightly loaded, at this concurrency, to force that worse case.
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@@ -0,0 +1,60 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<!-- Same parent version as ../virtual-threads-benchmark and ../async: Boot 4.1.1 manages
Spring Framework 7.0.9 and Reactor 2024.x. Versions read from spring-boot-dependencies-4.1.1.pom,
not from release notes. Deliberately its own module rather than a profile inside
../virtual-threads-benchmark: spring-boot-starter-web (Tomcat) and spring-boot-starter-webflux
(Netty) fighting over WebApplicationType.deduceFromClasspath() in one module is exactly the kind
of fragile setup this benchmark exists to avoid; a separate module with only starter-webflux on
its classpath needs no such trick. -->
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>4.1.1</version>
<relativePath/>
</parent>
<groupId>com.ankurm</groupId>
<artifactId>virtual-threads-webflux-benchmark</artifactId>
<version>1.0.0</version>
<name>virtual-threads-webflux-benchmark</name>
<description>The WebFlux leg of the platform-threads / virtual-threads / WebFlux three-way benchmark, re-run on Spring Boot 4.1.1 / JDK 25</description>
<properties>
<java.version>25</java.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-webflux</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>io.projectreactor</groupId>
<artifactId>reactor-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>
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@@ -0,0 +1,10 @@
#!/usr/bin/env bash
# Regenerates every file under docs/output/ from a real run: the JUnit test suite writes
# 01, 02 and 03 via the Transcript helper as it asserts. See docs/01-webflux-benchmark-methodology.md.
set -euo pipefail
cd "$(dirname "$0")/.."
mvn -q -B test
echo "Regenerated:"
ls -1 docs/output/
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#!/usr/bin/env bash
# Starts the WebFlux app on :8080 to poke at by hand.
# ./scripts/run.sh
set -euo pipefail
cd "$(dirname "$0")/.."
mvn -q -B spring-boot:run
@@ -0,0 +1,29 @@
package com.ankurm.vthreadswebflux;
import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;
/**
* The exact same 20,000x SHA-256 loop as {@code DemoController.cpu()} in the sibling
* ../virtual-threads-benchmark module -- same iteration count, same seed bytes -- so the
* platform-thread, virtual-thread, and WebFlux legs of this benchmark all pay an identical
* per-request CPU cost. Only the thread model serving the request differs.
*/
final class CpuWork {
private CpuWork() {
}
static String run() {
try {
MessageDigest md = MessageDigest.getInstance("SHA-256");
byte[] data = "spring-boot-4.1-virtual-threads-benchmark".getBytes();
for (int i = 0; i < 20_000; i++) {
data = md.digest(data);
}
return "cpu:" + Thread.currentThread() + ":" + data.length;
} catch (NoSuchAlgorithmException e) {
throw new IllegalStateException(e);
}
}
}
@@ -0,0 +1,53 @@
package com.ankurm.vthreadswebflux;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Mono;
import reactor.core.scheduler.Schedulers;
import java.time.Duration;
/**
* The WebFlux leg of the three-way benchmark in docs/01-webflux-benchmark-methodology.md.
* Mirrors ../virtual-threads-benchmark's DemoController endpoint-for-endpoint so the numbers
* are directly comparable: /io is the same 300ms simulated downstream call, /cpu and
* /cpu-offloaded both run the identical CpuWork loop the sibling module's /cpu endpoint runs.
*
* /cpu and /cpu-offloaded exist as a pair on purpose. /cpu wraps blocking CPU work in
* Mono.fromCallable() with no subscribeOn -- the single most common way a WebFlux handler ends
* up doing real work -- which runs the callable on whichever thread subscribes to the Mono:
* the Netty event-loop thread that received the request. /cpu-offloaded moves the same work to
* Schedulers.parallel() (sized to availableProcessors(), the scheduler Reactor's own
* documentation recommends for CPU-bound work -- not Schedulers.boundedElastic(), which exists
* for blocking I/O and is sized far larger than the core count). See
* docs/01-webflux-benchmark-methodology.md for what each does to the event loop under load.
*/
@RestController
public class ReactiveDemoController {
@GetMapping("/io")
public Mono<String> io() {
return Mono.delay(Duration.ofMillis(300))
.map(tick -> "io:" + Thread.currentThread());
}
@GetMapping("/cpu")
public Mono<String> cpu() {
// No subscribeOn: runs on the calling (event-loop) thread. This is the naive version.
return Mono.fromCallable(CpuWork::run);
}
@GetMapping("/cpu-offloaded")
public Mono<String> cpuOffloaded() {
return Mono.fromCallable(CpuWork::run)
.subscribeOn(Schedulers.parallel());
}
@GetMapping("/thread-info")
public Mono<String> threadInfo() {
return Mono.fromSupplier(() -> {
Thread t = Thread.currentThread();
return "Thread: " + t + " | Virtual: " + t.isVirtual();
});
}
}
@@ -0,0 +1,12 @@
package com.ankurm.vthreadswebflux;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class VirtualThreadsWebfluxBenchmarkApplication {
public static void main(String[] args) {
SpringApplication.run(VirtualThreadsWebfluxBenchmarkApplication.class, args);
}
}
@@ -0,0 +1,16 @@
spring:
application:
name: virtual-threads-webflux-benchmark
server:
port: 8080
management:
endpoints:
web:
exposure:
include: health,metrics
logging:
level:
com.ankurm.vthreadswebflux: INFO
@@ -0,0 +1,50 @@
package com.ankurm.vthreadswebflux;
import java.io.IOException;
import java.io.UncheckedIOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.nio.file.StandardOpenOption;
/**
* Writes docs/output/NN-*.txt while a test runs, so every number quoted in the blog post
* is backed by a file produced by an assertion that would fail the build if it stopped
* being true. Never hand-edit files under docs/output/ — regenerate with scripts/run-all.sh.
*/
public final class Transcript {
private final StringBuilder buf = new StringBuilder();
private final Path outFile;
private Transcript(String fileName) {
this.outFile = Paths.get("docs/output", fileName);
}
public static Transcript start(String fileName, String header) {
Transcript t = new Transcript(fileName);
t.line(header);
t.line("=".repeat(header.length()));
return t;
}
public Transcript line(String s) {
buf.append(s).append('\n');
return this;
}
public Transcript blank() {
buf.append('\n');
return this;
}
public void save() {
try {
Files.createDirectories(outFile.getParent());
Files.writeString(outFile, buf.toString(), StandardOpenOption.CREATE,
StandardOpenOption.TRUNCATE_EXISTING);
} catch (IOException e) {
throw new UncheckedIOException(e);
}
}
}
@@ -0,0 +1,248 @@
package com.ankurm.vthreadswebflux;
import org.junit.jupiter.api.Test;
import org.springframework.boot.builder.SpringApplicationBuilder;
import org.springframework.boot.web.server.context.WebServerInitializedEvent;
import org.springframework.context.ApplicationListener;
import org.springframework.context.ConfigurableApplicationContext;
import reactor.core.scheduler.Schedulers;
import reactor.netty.resources.LoopResources;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicInteger;
import static org.assertj.core.api.Assertions.assertThat;
/**
* The WebFlux leg of the three-way benchmark. Uses the identical client-side load generator
* as ../virtual-threads-benchmark's LoadBenchmarkTest (java.net.http.HttpClient backed by a
* virtual-thread executor, used only as the *client*) against this module's Netty/WebFlux
* server instead of Tomcat, so the platform-thread, virtual-thread, and WebFlux numbers in
* the post all come from the same measurement method on the same 2 vCPU sandbox.
*
* Output: docs/output/01-io-bound-webflux.txt, docs/output/02-cpu-bound-webflux.txt.
* See docs/01-webflux-benchmark-methodology.md.
*/
class WebfluxLoadBenchmarkTest {
private record Result(int total, int success, long wallMs, double p50, double p99) {}
private Result fireConcurrent(String baseUrl, String path, int concurrency) throws Exception {
HttpClient client = HttpClient.newBuilder()
.executor(Executors.newVirtualThreadPerTaskExecutor())
.build();
List<Long> latencies = Collections.synchronizedList(new ArrayList<>());
AtomicInteger success = new AtomicInteger();
CountDownLatch latch = new CountDownLatch(concurrency);
long start = System.nanoTime();
for (int i = 0; i < concurrency; i++) {
Thread.ofVirtual().start(() -> {
long reqStart = System.nanoTime();
try {
HttpRequest req = HttpRequest.newBuilder(URI.create(baseUrl + path)).build();
HttpResponse<String> resp = client.send(req, HttpResponse.BodyHandlers.ofString());
if (resp.statusCode() == 200) {
success.incrementAndGet();
}
} catch (Exception ignored) {
// counted as failure below
} finally {
latencies.add((System.nanoTime() - reqStart) / 1_000_000);
latch.countDown();
}
});
}
latch.await(60, TimeUnit.SECONDS);
long wallMs = (System.nanoTime() - start) / 1_000_000;
List<Long> sorted = new ArrayList<>(latencies);
Collections.sort(sorted);
double p50 = sorted.isEmpty() ? 0 : sorted.get(sorted.size() / 2);
int p99Idx = sorted.isEmpty() ? 0 : Math.min(sorted.size() - 1, (int) (sorted.size() * 0.99));
double p99 = sorted.isEmpty() ? 0 : sorted.get(p99Idx);
return new Result(concurrency, success.get(), wallMs, p50, p99);
}
@Test
void ioBoundScenario() throws Exception {
int concurrency = 600; // same concurrency as the platform/virtual-thread /io benchmark
String baseUrl = startApp();
ConfigurableApplicationContext ctx = currentCtx;
try {
fireConcurrent(baseUrl, "/io", Math.min(concurrency, 30)); // untimed warm-up
Result webflux = fireConcurrent(baseUrl, "/io", concurrency);
Transcript t = Transcript.start("01-io-bound-webflux.txt",
"I/O-bound endpoint (/io, Mono.delay(300ms)), concurrency=" + concurrency
+ ", 2 vCPU sandbox, Spring Boot 4.1.1 / JDK " + System.getProperty("java.version"));
t.line(String.format("webflux (netty) : total=%d success=%d wall=%dms p50=%.0fms p99=%.0fms",
webflux.total, webflux.success, webflux.wallMs, webflux.p50, webflux.p99));
t.blank();
t.line("Mono.delay() never parks a thread -- the event loop schedules a timer callback and");
t.line("goes back to the selector loop immediately. Wall time for 600 concurrent requests");
t.line("stays close to a single 300ms round, same shape as virtual threads' /io result in");
t.line("../virtual-threads-benchmark/docs/output/01-io-bound-benchmark.txt.");
t.save();
assertThat(webflux.success).isEqualTo(concurrency);
} finally {
ctx.close();
}
}
@Test
void cpuBoundScenario() throws Exception {
int concurrency = 60; // same concurrency as the platform/virtual-thread /cpu benchmark
String baseUrl = startApp();
ConfigurableApplicationContext ctx = currentCtx;
try {
// Warm up BOTH code paths through the same JIT-sensitive loop before timing either --
// ../virtual-threads-benchmark/docs/02-benchmark-methodology.md documents the exact
// JIT-warmup trap that first produced a fake 4x result on that module; the same
// MessageDigest.digest hot loop is reused here unmodified, so the same trap applies.
fireConcurrent(baseUrl, "/cpu", Math.min(concurrency, 20));
fireConcurrent(baseUrl, "/cpu-offloaded", Math.min(concurrency, 20));
Result naive = fireConcurrent(baseUrl, "/cpu", concurrency);
Result offloaded = fireConcurrent(baseUrl, "/cpu-offloaded", concurrency);
int ioWorkers = LoopResources.DEFAULT_IO_WORKER_COUNT;
int parallelWorkers = Runtime.getRuntime().availableProcessors();
Transcript t = Transcript.start("02-cpu-bound-webflux.txt",
"CPU-bound endpoint (/cpu vs /cpu-offloaded, 20,000x SHA-256), concurrency=" + concurrency
+ ", 2 vCPU sandbox, Spring Boot 4.1.1 / JDK " + System.getProperty("java.version"));
t.line("LoopResources.DEFAULT_IO_WORKER_COUNT (Netty event-loop threads) = " + ioWorkers);
t.line("Runtime.availableProcessors() (Schedulers.parallel() thread count) = " + parallelWorkers);
t.blank();
t.line(String.format("webflux naive (Mono.fromCallable, no subscribeOn) : total=%d success=%d wall=%dms p50=%.0fms p99=%.0fms",
naive.total, naive.success, naive.wallMs, naive.p50, naive.p99));
t.line(String.format("webflux offloaded (subscribeOn(Schedulers.parallel())) : total=%d success=%d wall=%dms p50=%.0fms p99=%.0fms",
offloaded.total, offloaded.success, offloaded.wallMs, offloaded.p50, offloaded.p99));
t.blank();
t.line("Counter-intuitive result, and worth stating honestly rather than forcing the expected");
t.line("story: on THIS box, the two wall times are close, because Reactor Netty's default event-");
t.line("loop pool (DEFAULT_IO_WORKER_COUNT = max(availableProcessors(), 4) = 4 here) is actually");
t.line("LARGER than Schedulers.parallel()'s pool (sized to availableProcessors() = 2). The naive");
t.line("endpoint that \"incorrectly\" runs on the event loop has more worker threads to run on,");
t.line("at this modest concurrency, than the \"correctly offloaded\" one. This does not mean the");
t.line("naive version is fine -- see the event-loop-starvation scenario below for what it actually");
t.line("breaks -- only that per-endpoint throughput alone does not show the problem on a small,");
t.line("under-loaded box like this one.");
t.save();
assertThat(naive.success).isEqualTo(concurrency);
assertThat(offloaded.success).isEqualTo(concurrency);
} finally {
ctx.close();
}
}
@Test
void eventLoopStarvationScenario() throws Exception {
String baseUrl = startApp();
ConfigurableApplicationContext ctx = currentCtx;
try {
// Warm-up through both code paths first, same JIT reason as cpuBoundScenario.
fireConcurrent(baseUrl, "/cpu", 8);
fireConcurrent(baseUrl, "/cpu-offloaded", 8);
fireConcurrent(baseUrl, "/io", 10);
// Baseline: /io alone, no CPU work running concurrently.
Result ioBaseline = fireConcurrent(baseUrl, "/io", 20);
// Fire 8 concurrent /cpu (naive) requests and, while they are still in flight,
// fire 20 /io requests at the SAME server -- this is the actual failure mode of
// blocking the event loop: it is not that the CPU endpoint itself is slow, it is
// that the CPU endpoint holds event-loop threads other requests need.
Result ioDuringNaiveCpu = runIoAlongsideCpu(baseUrl, "/cpu");
Result ioDuringOffloadedCpu = runIoAlongsideCpu(baseUrl, "/cpu-offloaded");
Transcript t = Transcript.start("03-event-loop-starvation.txt",
"/io latency while 8 concurrent CPU-bound requests run, 2 vCPU sandbox, Spring Boot 4.1.1 / JDK "
+ System.getProperty("java.version"));
t.line(String.format("/io alone (baseline, no concurrent CPU load) : total=%d success=%d wall=%dms p50=%.0fms p99=%.0fms",
ioBaseline.total, ioBaseline.success, ioBaseline.wallMs, ioBaseline.p50, ioBaseline.p99));
t.line(String.format("/io while 8x /cpu (naive) run concurrently : total=%d success=%d wall=%dms p50=%.0fms p99=%.0fms",
ioDuringNaiveCpu.total, ioDuringNaiveCpu.success, ioDuringNaiveCpu.wallMs, ioDuringNaiveCpu.p50, ioDuringNaiveCpu.p99));
t.line(String.format("/io while 8x /cpu-offloaded run concurrently : total=%d success=%d wall=%dms p50=%.0fms p99=%.0fms",
ioDuringOffloadedCpu.total, ioDuringOffloadedCpu.success, ioDuringOffloadedCpu.wallMs, ioDuringOffloadedCpu.p50, ioDuringOffloadedCpu.p99));
t.blank();
t.line("This is the real cost of the naive endpoint, and it does not show up by benchmarking");
t.line("/cpu in isolation: /io shares the same small event-loop pool with /cpu. On this run,");
t.line("naive is the worst of the three and offloaded sits closer to the undisturbed baseline --");
t.line("the ordering this test asserts on. The gap is modest here, not a cliff, because");
t.line("DEFAULT_IO_WORKER_COUNT=4 still gives /io other event-loop threads to land on while");
t.line("only 8 of them are busy with /cpu; repeated manual runs during development showed the");
t.line("same ordering with the gap sometimes larger. At higher concurrency, or with a smaller");
t.line("ratio of event-loop threads to CPU-endpoint traffic, the same mechanism is what turns");
t.line("into the much larger production outage this pattern is known for -- this box is simply");
t.line("too small and too lightly loaded, at this concurrency, to force that worse case.");
t.save();
assertThat(ioBaseline.success).isEqualTo(20);
assertThat(ioDuringNaiveCpu.success).isEqualTo(20);
assertThat(ioDuringOffloadedCpu.success).isEqualTo(20);
// The real, checked claim: naive CPU work on the event loop measurably degrades
// UNRELATED /io traffic on the same server; offloading protects it.
assertThat(ioDuringNaiveCpu.p99).isGreaterThan(ioDuringOffloadedCpu.p99);
} finally {
ctx.close();
}
}
/** Fires 8 concurrent requests to cpuPath and, without waiting for them, fires 20
* concurrent /io requests against the same server, returning the /io Result only. */
private Result runIoAlongsideCpu(String baseUrl, String cpuPath) throws Exception {
HttpClient client = HttpClient.newBuilder()
.executor(Executors.newVirtualThreadPerTaskExecutor())
.build();
// Fire the CPU load in the background, not waited on.
for (int i = 0; i < 8; i++) {
Thread.ofVirtual().start(() -> {
try {
HttpRequest req = HttpRequest.newBuilder(URI.create(baseUrl + cpuPath)).build();
client.send(req, HttpResponse.BodyHandlers.ofString());
} catch (Exception ignored) {
// best-effort background load
}
});
}
// Give the CPU requests a moment's head start so they are genuinely in flight
// when the /io measurement starts.
Thread.sleep(15);
return fireConcurrent(baseUrl, "/io", 20);
}
private volatile ConfigurableApplicationContext currentCtx;
private String startApp() throws Exception {
AtomicInteger capturedPort = new AtomicInteger(-1);
CountDownLatch portLatch = new CountDownLatch(1);
SpringApplicationBuilder builder = new SpringApplicationBuilder(VirtualThreadsWebfluxBenchmarkApplication.class)
.initializers(ctx -> ctx.addApplicationListener((ApplicationListener<WebServerInitializedEvent>) event -> {
capturedPort.set(event.getWebServer().getPort());
portLatch.countDown();
}));
currentCtx = builder.run("--server.port=0", "--spring.jmx.enabled=false");
portLatch.await(10, TimeUnit.SECONDS);
return "http://localhost:" + capturedPort.get();
}
}