Capacity Planning using the Universal Scalability Law with Java and usl4j
September 30th, 2018 by Micha KopsCapacity planning is an important task when trying to anticipate resources and scaling factors for our applications.
The usl4j library offers us an easy abstraction for Neil J. Gunther’s Universal Scalability Law and allows us to build up a predictive model based on the parameters throughput, latency and concurrent operations.
With a basic input set of two of these parameters, we are able to predict how these values change if we change one input parameter so that we can build our infrastructure or systems according to our SLAs.
Running usl4j prediction with Maven
Contents
Setup
Using Maven we need to add just one dependency to our project’s pom.xml:
<dependency> <groupId>com.codahale</groupId> <artifactId>usl4j</artifactId> <version>0.7.0</version> </dependency>
Creating the Model and Building Predictions
We’re using usl4j to build a model based on concurrency and throughput (we need to pick two of the three possible parameters concurrency, throughput and latency).
The input values are based on a quick measurement of a Spring Boot demo application (see my article: “Integrating Swagger into a Spring Boot RESTful Webservice with Springfox“) taken with the Apache Bench tool (see Appendix A: Apache Bench (ab)).
With this model, we’re calculating predictions 10, 50, 100, 500, 1000, 50000 and 100000 concurrent workers and we print them to the screen.
package com.hascode.tutorial; import com.codahale.usl4j.Measurement; import com.codahale.usl4j.Model; import java.util.Arrays; import java.util.function.Consumer; public class SampleUSLCalculation { public static void main(String[] args) { // measured with ab (apache benchmark) from a spring boot demo app (devmode) final double[][] input = {{1, 412.53}, {2, 1355.32}, {3, 2207.16}, {4, 2466.22}, {5, 2549.40}, {6, 2679.73}}; final Model model = Arrays.stream(input) .map(Measurement.ofConcurrency()::andThroughput) .collect(Model.toModel()); Consumer<Integer> stats = (workers) -> System.out .printf("At %-8d workers, expect %5.4f req/sec%n", workers, model.throughputAtConcurrency(workers)); stats.accept(10); stats.accept(50); stats.accept(100); stats.accept(500); stats.accept(1_000); stats.accept(50_000); stats.accept(100_000); } }
Running the code above e.g. in the console should produce a similar output to this one:
$ mvn exec:java -Dexec.mainClass=com.hascode.tutorial.SampleUSLCalculation [..] At 10 workers, expect 1723.3279 req/sec At 50 workers, expect 269.1074 req/sec At 100 workers, expect 127.8484 req/sec At 500 workers, expect 24.4997 req/sec At 1000 workers, expect 12.1833 req/sec At 50000 workers, expect 0.2424 req/sec At 100000 workers, expect 0.1212 req/sec [INFO] ------------------------------------------------------------------------ [INFO] BUILD SUCCESS [INFO] ------------------------------------------------------------------------ [INFO] Total time: 1.016 s [INFO] Finished at: 2018-09-30T19:29:16+02:00 [INFO] ------------------------------------------------------------------------
Animated ;)
Running usl4j example with Maven
Tutorial Sources
Please feel free to download the tutorial sources from my Bitbucket repository, fork it there or clone it using Git:
git clone https://bitbucket.org/hascode/usl4j-tutorial.git
Resources
Appendix A: Apache Bench (ab)
For more detailed information about using ab, please consult its man-page: http://httpd.apache.org/docs/2.4/programs/ab.html
ab -c 1 -n 1000000 -t 60 http://localhost:8080/currentdate/yyyy-MM Concurrency Level: 1 Time taken for tests: 23.554 seconds Complete requests: 50000 Failed requests: 0 Total transferred: 9950000 bytes HTML transferred: 2550000 bytes Requests per second: 2122.75 [#/sec] (mean) Time per request: 0.471 [ms] (mean) Time per request: 0.471 [ms] (mean, across all concurrent requests) Transfer rate: 412.53 [Kbytes/sec] received ab -c 2 -n 1000000 -t 60 http://localhost:8080/currentdate/yyyy-MM Concurrency Level: 2 Time taken for tests: 7.169 seconds Complete requests: 50000 Failed requests: 0 Total transferred: 9950000 bytes HTML transferred: 2550000 bytes Requests per second: 6974.09 [#/sec] (mean) Time per request: 0.287 [ms] (mean) Time per request: 0.143 [ms] (mean, across all concurrent requests) Transfer rate: 1355.32 [Kbytes/sec] received ab -c 3 -n 1000000 -t 60 http://localhost:8080/currentdate/yyyy-MM Concurrency Level: 3 Time taken for tests: 4.402 seconds Complete requests: 50000 Failed requests: 0 Total transferred: 9950000 bytes HTML transferred: 2550000 bytes Requests per second: 11357.44 [#/sec] (mean) Time per request: 0.264 [ms] (mean) Time per request: 0.088 [ms] (mean, across all concurrent requests) Transfer rate: 2207.16 [Kbytes/sec] received ab -c 4 -n 1000000 -t 60 http://localhost:8080/currentdate/yyyy-MM Concurrency Level: 4 Time taken for tests: 3.940 seconds Complete requests: 50000 Failed requests: 0 Total transferred: 9950000 bytes HTML transferred: 2550000 bytes Requests per second: 12690.49 [#/sec] (mean) Time per request: 0.315 [ms] (mean) Time per request: 0.079 [ms] (mean, across all concurrent requests) Transfer rate: 2466.22 [Kbytes/sec] received ab -c 5 -n 1000000 -t 60 http://localhost:8080/currentdate/yyyy-MM Concurrency Level: 5 Time taken for tests: 3.811 seconds Complete requests: 50000 Failed requests: 0 Total transferred: 9950000 bytes HTML transferred: 2550000 bytes Requests per second: 13118.51 [#/sec] (mean) Time per request: 0.381 [ms] (mean) Time per request: 0.076 [ms] (mean, across all concurrent requests) Transfer rate: 2549.40 [Kbytes/sec] received ab -c 6 -n 1000000 -t 60 http://localhost:8080/currentdate/yyyy-MM Concurrency Level: 6 Time taken for tests: 3.626 seconds Complete requests: 50000 Failed requests: 0 Total transferred: 9950000 bytes HTML transferred: 2550000 bytes Requests per second: 13789.17 [#/sec] (mean) Time per request: 0.435 [ms] (mean) Time per request: 0.073 [ms] (mean, across all concurrent requests) Transfer rate: 2679.73 [Kbytes/sec] received
Appendix B: wrk Benchmark Tool
For more detailed information about its usage, please consult the corresponding GitHub page: https://github.com/wg/wrk
Update: There’s now wrk2 that seems to be more precise.
wrk -d 1m -t 1 http://localhost:8080/currentdate/yyyy-MM 1 ↵ Running 1m test @ http://localhost:8080/currentdate/yyyy-MM 1 threads and 10 connections Thread Stats Avg Stdev Max +/- Stdev Latency 621.20us 0.88ms 28.49ms 93.63% Req/Sec 20.88k 4.47k 26.87k 85.83% 1246239 requests in 1.00m, 259.45MB read Requests/sec: 20770.26 Transfer/sec: 4.32MB wrk -d 1m -t 2 http://localhost:8080/currentdate/yyyy-MM Running 1m test @ http://localhost:8080/currentdate/yyyy-MM 2 threads and 10 connections Thread Stats Avg Stdev Max +/- Stdev Latency 658.82us 828.31us 15.59ms 92.42% Req/Sec 9.96k 842.39 12.14k 71.58% 1189582 requests in 1.00m, 248.67MB read Requests/sec: 19820.91 Transfer/sec: 4.14MB wrk -d 1m -t 3 http://localhost:8080/currentdate/yyyy-MM Running 1m test @ http://localhost:8080/currentdate/yyyy-MM 3 threads and 10 connections Thread Stats Avg Stdev Max +/- Stdev Latency 662.69us 0.92ms 19.63ms 92.20% Req/Sec 6.22k 827.86 8.28k 70.56% 1114545 requests in 1.00m, 232.98MB read Requests/sec: 18561.74 Transfer/sec: 3.88MB wrk -d 1m -t 4 http://localhost:8080/currentdate/yyyy-MM Running 1m test @ http://localhost:8080/currentdate/yyyy-MM 4 threads and 10 connections Thread Stats Avg Stdev Max +/- Stdev Latency 754.31us 1.00ms 20.00ms 92.17% Req/Sec 3.47k 0.97k 6.18k 62.98% 829340 requests in 1.00m, 173.36MB read Requests/sec: 13817.65 Transfer/sec: 2.89MB wrk -d 1m -t 5 http://localhost:8080/currentdate/yyyy-MM Running 1m test @ http://localhost:8080/currentdate/yyyy-MM 5 threads and 10 connections Thread Stats Avg Stdev Max +/- Stdev Latency 1.07ms 1.42ms 24.05ms 89.94% Req/Sec 2.76k 798.62 5.34k 66.50% 824038 requests in 1.00m, 172.25MB read Requests/sec: 13718.01 Transfer/sec: 2.87MB wrk -d 1m -t 6 http://localhost:8080/currentdate/yyyy-MM Running 1m test @ http://localhost:8080/currentdate/yyyy-MM 6 threads and 10 connections Thread Stats Avg Stdev Max +/- Stdev Latency 526.90us 0.87ms 36.32ms 95.35% Req/Sec 2.38k 443.07 3.46k 65.86% 853914 requests in 1.00m, 178.50MB read Requests/sec: 14211.87 Transfer/sec: 2.97MB
Tags: ab, Apache, bandwidth, benchmark, calculate, capacity, latency, little, measure, planning, predict, prediction, throughput, universal scalability law, usl4j, wrk, wrk2