Project 3 details

Integrating MERRA data, deploying on Jetstream and integration of messaging service in our microservices communications.

It is deployed on Jetstream. The link to access it :

                                       http://149.165.156.154:30500/

We have deployed our microservices with Kubernetes on jetstream, with each service running multiple instances. It includes both Merra and existing implementation of the Nexrad dataset.

We have used kubeadm to deploy it on Jetstream forming a k8 cluster, the database connection doesn't work on the exosphere, so we are going with deploying it on atmosphere with the same code base . We have used Openstack to spawn instances of the Master and worker nodes on the exosphere.

The branch for these changes is : develop-MERRA2-visualization

We have also implemented the RabbitMq changes on our system but we are facing issues to deploy it on jet stream. The branch for rabbitmq changes is: develop-rabbitmq To test the messaging queue, local testing can be done. For testing locally, all the services have to be up.

Navigate to each of the folders and run the commands in order:

Frontend (reactjs):

• npm install
• npm start

Api Gateway (nodejs):

• npm install
• node app.js

Auth Service (nodejs)

• npm install
• npm start

Cache Service (Springboot):

• Run as java application using eclipse

Data Ingestor (python):

• cd Data\Ingestor/
• conda env create -f environment.yml (setting up virtual env)
• conda activate nexrad-env (activating env)
• pip install -r requirements.txt
• conda run -n nexrad-env --no-capture-output python3 main.py (starting flask server)

Completed items:

• Merra data visualisation
• CI/CD [Refer branches: Auth-ci-pipeline, cache-ci-pipeline, client-ci-pipeline, data-ingestor-ci-pipeline]
• Jetstream deployment [Refer link: http://149.165.156.154:30500/]
• Implemented rabbitmq