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fib

This containerized reactive RESTful API implements an efficient Θ(log.n) fibonacci algorithm using Quarkus framework

Table of Contents

TLDR

./configure

Configure will check if all prerequisites are installed. It uses command application. See: Important Disclaimer at the top of the configure file for troubleshooting.

make && make install

To assemble Docker container and create executable file (just an alias for docker run command).

./fib

The output should be:

exec java -Dquarkus.http.host=0.0.0.0 -Djava.util.logging.manager=org.jboss.logmanager.LogManager -XX:+ExitOnOutOfMemoryError -cp . -jar /deployments/quarkus-run.jar
__  ____  __  _____   ___  __ ____  ______
 --/ __ \/ / / / _ | / _ \/ //_/ / / / __/
 -/ /_/ / /_/ / __ |/ , _/ ,< / /_/ /\ \
--\___\_\____/_/ |_/_/|_/_/|_|\____/___/
2021-07-29 18:40:32,968 INFO  [io.quarkus] (main) fib 0.0.1-SNAPSHOT on JVM (powered by Quarkus 2.0.3.Final) started in 0.996s. Listening on: http://0.0.0.0:8080
2021-07-29 18:40:32,970 INFO  [io.quarkus] (main) Profile prod activated.
2021-07-29 18:40:32,970 INFO  [io.quarkus] (main) Installed features: [cdi, resteasy-reactive, smallrye-context-propagation, vertx]

Running on Bash

Prerequisites

Make 4.2.1 Docker 20.10.2 OpenJDK 11 Minikube 1.22.0 Kubectl 1.18.3

To run in Docker container

You only need Make (tested with GNU Make 4.2.1, but it should work on others) and Docker (tested with Docker version 20.10.2, build 2291f61) installed. It is important to give execution permission for scripts/:

chmod +x scripts/

They are safe, but you could check it out if you don't believe me. 😄

To run locally

make run-local

It will build locally and run using java executable. (Must have a JVM installed)

Test

Unit test

make test

Large n argument

[r1cm3d]@[PISMOWL114]:~/dev/projects/fib
> (main) $ time curl http://localhost:8080/fib?n=70000000
a lot of numbers...
real    3m18,691s
user    0m0,018s
sys     0m0,167s

Deploy

make start-k8s && make deploy-k8s

It will start minikube and deploy fib application and fib_hpa which is an autoscaler based on CPU and memory utilization. Autoscaler is need to be compliance with scale requirement based on workload.