A.L.A. (Automated Linguistic Analysis) application

Sample application showcasing usage of technologies such as:

• OSGi R7 Promises for asynchronous generation of transcriptions and linguistic analyses
• OSGi R7 Push Stream and JAX RS Server Sent Events for push notifications of processing status
• Apache Camel 2.23.1 and RabbitMQ 3.7 for asynchronous communication between services
• JPA 2.1 and Hibernate 5.2.12, along with OSGi R7 JPA and Transaction Control services, for persistence layer
• OSGi R7 HTTP and JAX RS Whiteboard for registering servlets, resources and REST controllers
• OSGi R7 Configurator, Configuration Admin and Metatype services for automatic configuration of components
• OSGi R7 Declarative Services for dependency injection
• Maven automated build of Docker images
• Maven automated deployment into Kubernetes cluster
• RabbitMQ message broker as a StatefulSet
• CockroachDB relational database as a StatefulSet

For detailed overview, please see the following articles:

• Using Camel and RabbitMQ in an OSGi R7 application, including custom message types
• Implementing asynchronous processing with OSGi R7 Promises
• Implementing efficient monitoring of long running operations with OSGi R7 Push Stream and Server Sent Events
• OSGi R7 HTTP Whiteboard, JAX-RS Whiteboard and Converter services applied
• Painless Monolith breakup or how automation and efficient design enables smooth transitions
• Automating Kubernetes deployments

Configuring

I. Mono version

1. Set up PostgreSQL database

• Create database and user using PostgreSQL command line or GUI

• If not already installed, install the postgresql-contrib package as that’s what’s required to use the gen_random_uuid() function; same function is available out-of-the-box on CockroachDB which is used for Kubernetes version

2. Set up RabbitMQ message broker

• (optional) Set up RabbitMQ Web Management console – once set up it will be accessible via http://localhost:15672/ (u/p: guest/guest)

  rabbitmq-plugins enable rabbitmq_management

3. Open configuration.json file residing in mono-app module in src/main/resources/OSGI-INF/configurator directory

• Under org.apache.aries.tx.control.jpa.xa~ala PID, configure database, user name and password
• (optional) Under software.into.ala.service.messaging PID, configure message broker host and port or leave as is to use defaults
• Under org.apache.aries.jax.rs.whiteboard.default PID, configure file storage location – this must match file storage location seen in software.into.ala.service.transcription PID
• Under software.into.ala.service.transcription PID, configure IBM Watson Speech to Text endpoint and API key – small footprint instances are free and sufficient to test drive this application; for more information see https://www.ibm.com/watson/services/speech-to-text/
• Under software.into.ala.service.linguistics PID, configure IBM Watson Tone Analyzer endpoint and API key – small footprint instances are free and sufficient to test drive this application; for more information see https://www.ibm.com/watson/services/tone-analyzer/

II. Kubernetes version

1. Web application (k8-web-app module) – no configuration is necessary, unless you wish to use custom settings, i.e.

• Open configuration.json file residing in k8-web-app module in src/main/resources/OSGI-INF/configurator directory
• Unless you wish to use different settings, DO NOT modify configuration for org.apache.aries.tx.control.jpa.xa~ala PID – in Kubernetes version, both user and database are created automatically during cluster initialization, which also happens automatically during deployment
• Unless you wish to use different settings, DO NOT modify configuration for software.into.ala.service.messaging PID
• Unless you wish to use different settings, DO NOT modify configuration for org.apache.aries.jax.rs.whiteboard.default PID, e.g. file storage location

2. Transcription application (k8-transcription-app module) – only IBM Watson configuration is required, i.e.

• Open configuration.json file residing in k8-transcription-app module in src/main/resources/OSGI-INF/configurator directory
• Under software.into.ala.service.transcription PID, configure IBM Watson Speech to Text endpoint and API key – small footprint instances are free and sufficient to test drive this application; for more information see https://www.ibm.com/watson/services/speech-to-text/

3. Linguistics application (k8-linguistics-app module) – only IBM Watson configuration is required, i.e.

• Open configuration.json file residing in k8-linguistics-app module in src/main/resources/OSGI-INF/configurator directory
• Under software.into.ala.service.linguistics PID, configure IBM Watson Tone Analyzer endpoint and API key – small footprint instances are free and sufficient to test drive this application; for more information see https://www.ibm.com/watson/services/tone-analyzer/

4. In main project POM

• Modify the docker-registry property to use external Docker registry or set up a local Docker registry; for more information see https://docs.docker.com/registry/deploying/
• If not using local Docker registry, remove the k8-maven.insecureRegistry property – this one is used for minikube automation and required if using local Docker registry
• (optional) Adjust the k8-maven.memory and k8-maven.cpus properties as needed – this is used for minikube automation

5. Set up and start Kubernetes cluster – e.g. minikube can be used to quickly set up local Kubernetes cluster; for more information see https://github.com/kubernetes/minikube

6. (optional) Customize Kubernetes descriptors for deploying cluster versions of RabbitMQ and CockroachDB as StatefulSets – these reside in k8-infra project, in src/main/k8 directory; for more information see:

• “Deploy RabbitMQ on Kubernetes with the Kubernetes Peer Discovery Plugin”
• “CockroachDB on Kubernetes as a StatefulSet”

Building

I. Mono version

mvn install

II. Kubernetes version

Build project and Docker images, automatically pushing Docker images to configured repository

mvn -P k8 install

Deploying

I. Mono version

1. Go to mono-app module directory and run

java -jar target/mono-app.jar

2. Open http://localhost:8080/spa/index.html in web browser

II. Kubernetes version

1. To deploy onto Kubernetes cluster from main project directory, run

mvn -P k8 deploy

2. Find IP and service port of ala-k8-web-app service – e.g. for minikube you can use

minikube service --url ala-k8-web-app

3. Open http://IP:SERVICEPORT/spa/index.html in web browser

Architecture

I. Mono version

1. Deployment view

2. Component view

II. Kubernetes version

1. Deployment view

2. Component view

• Web application

• Transcription application

• Linguistics application

Technology stack

• Java 8

• OSGi Release 7 Core and Enterprise specifications implementations, including

  • OSGi Configurator
  • OSGi Metatype Service
  • OSGi Configuration Admin Service
  • OSGi DTO
  • OSGi Declarative Services
  • OSGi Converter
  • OSGi JPA Service
  • OSGi HTTP Whiteboard
  • OSGi JAX-RS Whiteboard
  • OSGi Transaction Control Service
  • OSGi Push Stream
  • OSGi Promises

• Equinox OSGi container 3.13.100

• JPA API 2.1
• Hibernate 5.2.12
• Apache Camel 2.23.1, including Camel RabbitMQ component
• Apache Felix Http Jetty 4.0.6
• IBM Watson SDK 6.14.2, including Speech to Text and Tone Analyzer
• Message broker:
  • Mono deployment: RabbitMQ 3.6.16
  • Kubernetes deployment: RabbitMQ 3.7
• Relational database:
  • Mono deployment: PostgreSQL 10.7
  • Kubernetes deployment: CockroachDB 2.1.6