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vert.x micro-service workshop

In this workshop, you are going to develop a micro-service application called vert2go. This workshop covers:

  • how to build micro-services with vert.x
  • how you can use the event bus to bind your micro-services
  • how to consume a REST API
  • how to build an application using several persistence technologies
  • how to provide a REST API, and build proxies
  • how to deploy some micro-service to Openshift
  • how to centralize your logs
  • how to deploy a vert.x micro-service in a docker container
  • how to monitor your application

The vert2go application is a recommendation application where users can rates the place they like.

The slides for the talk are online.

Prerequisites:

  • Java 8 (JDK)
  • Git
  • Apache Maven
  • Docker (or docker-machine)
  • An IDE
  • RoboMongo (optional)

Using docker machine

Docker runs natively on Linux. Because the Docker daemon uses Linux-specific kernel features, you can’t run Docker natively in OS X or Windows. Instead, you must use docker-machine to create and attach to a virtual machine (VM). This machine is a Linux VM that hosts Docker for you on your Mac or Windows. If you are on Mac OS X or Windows, you can use docker via docker machine (https://docs.docker.com/machine/).

  1. Install docker and docker-machine from https://www.docker.com/docker-toolbox. Installation instructions are there: http://docs.docker.com/mac/step_one/
  2. Once done run docker run hello-world to verify your installation

The installation process will create a VM that has a minimal linux to run docker.

Components

Data Storage Service

This service shows how to connect to a mongodb database and genereate a API interface that will generate bindings for the 2 languages used across the demo, groovy and javascript.

cd data-storage-service
mvn clean package
java -jar target/data-storage-service-1.0-SNAPSHOT-fat.jar --cluster --conf=src/conf/config.json

Data Provisioning

This REST consumer will consume a REST service and populate the mongo collection directly it does not need to be part of a cluster

cd data-provisioning
mvn clean package
java -jar target/data-provisioning-1.0-SNAPSHOT-fat.jar --conf=src/conf/config.json

Data Storage Client

This is a simple client written in Groovy that show the usage of service proxies generated from the data storage service. Since this client has no knowledge on mongo and uses a proxy it needs to be part of the cluster to find where to delegate the the action from the proxy.

cd data-storage-client
mvn clean package
java -jar target/data-provisioning-1.0-SNAPSHOT-fat.jar --cluster

Frontend

This is the web part of the application it will show the usage of the sockjs bridge and that generated proxies can be consumed also from the browser. This part of the code show that a Verticle can be written in javascript.

cd frontend
mvn clean package
java -jar target/frontend-1.0-SNAPSHOT-fat.jar --cluster

Map Render Service

This component show a part of the application that can be deployed on the cloud and we will consume its service using REST. It works as the other components but since we are deploying it on OpenShift there are a few extra steps.

For the first time we need to create an app:

rhc create-app map0render0service https://raw.githubusercontent.com/vert-x3/vertx-openshift-cartridge/master/metadata/manifest.yml

And then

cd frontend
mvn clean package

cd openshift
git add -A
git commit -m "deploy my application"
git push

Map Render Proxy

We will consume the map service as a local proxy and add caching headers this we will deploy on Docker.

cd map-server-proxy
mvn clean install
mvn docker:build
mvn docker:start

If one refreshes the frontend javascript application the map should start showing on the right side of the screen.

Recommendation Service

This shows again how to connect to redis and use pub/sub mode to pubish votes if one opens 2 browsers and clicks on one restaurant and votes the counters should update in realtime on both web clients.

cd recommendation-service
mvn clean package
java -jar target/recommendation-service-1.0-SNAPSHOT-fat.jar --cluster --conf=src/conf/config.json

Extras

Centralized logging

replace the jul configuration content on data-storage-service with the example on etc and add the GELF dependency to the pom.xml.

Start graylog2 and enable the UDP transport.

Rebuild and restart the service

cd data-storage-service
mvn clean package
java -jar target/data-storage-service-1.0-SNAPSHOT-fat.jar --cluster --conf=src/conf/config.json

Using the client or the web browser load some data, the logs should now be collected in a graylog server.

Metrics

Hawkular

Start the server see the scripts folder. Add a bridge to hawkular to the deployment

cd eventbus-to-hawkular-bridge
mvn clean package
java -jar target/eventbus-to-hawkular-bridge-1.0-SNAPSHOT-fat.jar --cluster --conf=src/conf/config.json

Running some queries to the data storage service should generate some metrics to be called.

Grafana

Start grafana (see scripts) Add a connection use Influx 0.8 and connect to the hawkular server, then add a graph to the dashboard using the name vertx2go.metrics and you should start seeing the average requests metrics in a visual form.