Microservice Application on a VM

Goal

Create a microservice based application on a vm. Later we will compare this with running the same app containerized.

Instructions

Clone my repo instead of the one in the instructions below. Here it is.

Complete all of step 1 on this page.

Make sure you stop when you get to step 2.

To Pass off

In class:

Demonstrate that you can view sentiment when accessing the single ip that hosts this application.

Hints

Here is the quick and dirty to get part 1 done. Note:if you are re-using a vm that has apache installed on it, you will need to disable apache as it could conflict with nginx.

git clone https://github.com/nachofree/k8s-mastery.git

• cd k8s2-mastery
• frontend
  • cd sa-frontend
  • sudo apt install npm nginx
  • npm install
  • npm run build
  • sudo cp -r build/* /var/www/html
  • service nginx restart
  • Make sure it loads in the browser now
• webapp
  • cd sa-webapp
  • sudo apt install maven
  • mvn install
  • cd target
  • java -jar sentiment-analysis-web-0.0.1-SNAPSHOT.jar --sa.logic.api.url=http://localhost:5000 (leave it running in the terminal)
• logic (from a different terminal)
  • cd sa-logic
  • sudo apt install python3
  • sudo apt install python3-pip
  • cd sa
  • Edit requirements.txt so that it will also have the following line (if it’s not already there):
    • itsdangerous==2.0.1
  • pip3 install -r requirements.txt
  • python3 -m textblob.download_corpora
  • Add these two lines to the top of your sentiment_analysis.py file:
    • import nltk
    • nltk.download('punkt_tab')
  • python3 sentiment_analysis.py (leave it running in the terminal)

Now when you load your web interface, the sentiment app should work. Note: If you are running this on a remote vm, you will have to construct a few tunnels to make everything work. My command was something like this: ssh jfrancom@ssh.cs.utahtech.edu -L 8888:144.38.193.248:80 -L 8080:144.38.193.248:8080. Then you will visit http://localhost:8888 in the browser. So, nginx is hosting the frontend at port 80, it then sends some information to the python module on port 8080. A video here might also help.