Realtime Dashboard

This is my playground to learn about streaming technologies. This bench project also aims to technically showcase that it is possible to link up different technologies to build a realtime dashboard to show analysis results.

The technologies/tools/libraries/frameworks that will be involved are:

• Web Development: Angular, Angular Material, Socket.io, Express, JWT authentication.

• Distributed Streaming Platform: Apache Kafka

• Distributed Data Processing: Apache Spark

Current Features

It has been quite a while since the last time I did web development (5 years!!) so it took some time to get up and running. The current features of this project are:

• Authentication using JWT to improve authentication approach and better support for non-browser clients.
• • The user store is still mocked using a list of users in JSON format.
• • Only some API endpoints are secured
• Separation of authentication service and the analytics service. The purpose it to let them scale independently later on.
• Angular Material and Ngx Charts for good user interface and easy visualisation update on data changes.
• Realtime WebSockets using Socket.io for realtime UI updates. The access to it has also been secured using JWT.
• API services connected to Kafka to push data (unsecured)
• Local Spark connected to dockerized Kafka
• A relay service to relay Kafka messages to analytics (and eventually to UI through websockets)

Stretch Goals

• UI using Teradata Covalent
• UI using Vue.JS
• Websockets using SocketCluste
• Multiple metrics or data sets
• Dockerization of services
• Separation of Websocket layer
• Authentication against a database + role-based access.
• Create a simple prediction model, serve a prediction service and use the dashboard to display prediction results.

How to Use

Start Dockerized Streaming Services

I'm using some publicly available docker images for Kafka and Spark:

• Kafka
• • https://hub.docker.com/r/wurstmeister/kafka/
• • https://hub.docker.com/r/wurstmeister/zookeeper/
• Spark
• • https://hub.docker.com/r/bde2020/spark-master/
• • https://hub.docker.com/r/bde2020/spark-worker/

The Kafka service needs to be started before the analytics API since it depends on Kafka. Make sure you have docker installed and running before doing the following (assuming that you're in the project root folder): docker-compose up

Start API Services

There are 2 APIs: Authentication and Analytics. Both are developed using ExpressJS and are in and api-auth-express and api-analytics-express respectively. Make sure you have NodeJS and NPM installed before you do the following

Go to the api-auth-express folder and start the service (will be on port :3001)

• cd api-auth-express
• npm install
• PORT=3001 nodemon

Open a new terminal, go to the api-analytics-express folder, and start the service (will be on port :3000)

• cd api-analytics-express
• npm install
• PORT=3000 nodemon

Start UI Services

Open a new terminal, go to the ui-dashboard-angular and start the service (will be on port :4200) npm install -g @angular/cli cd ui-dashboard-angular npm install ng serve

Project/Subproject Naming Convention

Just an idea to name projects and subprojects. The naming convention is as follows: [module-name/project-name]-component-function-[version]-[technology]

Examples:

• api-auth-express
• api-auth-restify
• ui-dashboard-0.1
• api-socket-0.7-socketcluster

Other example with example projects:

• shell-oilwell-predictions/stream-messaging-0.3-kafka
• walmart-store-analysis/stream-analytics-0.1-spark
• poc-project-name/api-socket-0.1-socketcluster