NYU DevOps Products

This is the development and utilization documentation for products squad. The products service represents the store items that the customer can buy. They have a unique product id, a name, description, price, and an imageURL for display.

Team Members:\ Shilong Dong, Yujia Zhu, Weilin Chen, Tiancheng Zhang, Arya Goyal

Overview

This project inherits basic code structure from lab-flask-tdd.

• The /service folder contains our models.py file for our model and a routes.py file for our service.
• The /tests folder has test case code for testing the model and the service separately.

Project Setup

You need to clone this repo to your local dir and enter the project's directory. Then open it in VSCode, and make sure reopen it in Docker Container.

git clone https://github.com/CSCI-GA-2820-FA24-001/products.git
cd products
code .

Usage

REST APIs

We provide basic CRUD, List, Query and Purchase operations for our product service.

When using Query service, we can specify name or price for fuzzy query, such as GET /products?name=iPhone and GET /products?price=1088. First request returns products whose name contains iPhone, and the second request returns those with price around 1088.

Test

We follow the TDD manner during our development. If you want to test the project, you can follow the following commands.

flask db-create
make test
make lint

Our test report is as follows:

---------- coverage: platform linux, python 3.11.10-final-0 ----------
Name                               Stmts   Miss  Cover   Missing
----------------------------------------------------------------
service/__init__.py                   22      2    91%   50-51
service/common/cli_commands.py        12      0   100%
service/common/error_handlers.py      32      3    91%   91-93
service/common/log_handlers.py        10      1    90%   35
service/common/status.py              45      0   100%
service/config.py                      7      0   100%
service/models.py                     93      0   100%
service/routes.py                     96      0   100%
----------------------------------------------------------------
TOTAL                                317      6    98%

Required test coverage of 95% reached. Total coverage: 98.11%

===================================================== 59 passed in 1.86s ===

Run

You can start the service using the following commands.

make run

Then you are able to visit the homepage from http://localhost:8080/ or http://0.0.0.0:8080/, and utilize our services with prompts on the homepage.

Deployment

Deployment of our products service can be done in following steps:

1. Create dev cluster

make cluster

2. Build this project as a Docker image

docker build -t products:latest .

3. Configure registry

Check if cluster-registry is configured in /etc/hosts:

cat /etc/hosts

If there is no entry for cluster-registry, add it by running:

sudo bash -c "echo '127.0.0.1    cluster-registry' >> /etc/hosts"

4. Create tag and push our image to K3d registry

docker tag products:latest cluster-registry:5000/products:latest
docker push cluster-registry:5000/products:latest

5. Create and switch to a new Kubernetes Namespace

kubectl create namespace deployment
kubectl config set-context --current --namespace deployment

6. Deploy our image with postgresql and products service

kubectl apply -f k8s/postgresql/
kubectl apply -f k8s

wait for approximately 20 seconds until all services are running, using following command to track status

kubectl get all

7. View logs from a service

kubectl get pods
kubectl logs pod/<pod-name>

Now we can access http://localhost:8080 for our product service that is deployed on local cluster

8. Remove all services from the namespace and remove cluster

kubectl delete -f k8s -R
make cluster-rm

Deployment on Red Hat OpenShift

Login command within shell

(See slides)

Switch to project namespace

oc project vectorzyj-dev

Deploy PostgreSQL Database

oc apply -f k8s/postgresql/

Add Event Listener

oc apply -f .tekton/events/

Then click on Trigger -> Deployment -> el-cd-listener, in deployment details, set scaling to 1 pod.

Contents

The project contains the following:

.gitignore          - this will ignore vagrant and other metadata files
.flaskenv           - Environment variables to configure Flask
.gitattributes      - File to gix Windows CRLF issues
.devcontainers/     - Folder with support for VSCode Remote Containers
dot-env-example     - copy to .env to use environment variables
pyproject.toml      - Poetry list of Python libraries required by your code

service/                   - service python package
├── __init__.py            - package initializer
├── config.py              - configuration parameters
├── models.py              - module with business models
├── routes.py              - module with service routes
└── common                 - common code package
    ├── cli_commands.py    - Flask command to recreate all tables
    ├── error_handlers.py  - HTTP error handling code
    ├── log_handlers.py    - logging setup code
    └── status.py          - HTTP status constants

tests/                     - test cases package
├── __init__.py            - package initializer
├── factories.py           - Factory for testing with fake objects
├── test_cli_commands.py   - test suite for the CLI
├── test_models.py         - test suite for business models
└── test_routes.py         - test suite for service routes

License

Copyright (c) 2016, 2024 John Rofrano. All rights reserved.

Licensed under the Apache License. See LICENSE

This repository is part of the New York University (NYU) masters class: CSCI-GA.2820-001 DevOps and Agile Methodologies created and taught by John Rofrano, Adjunct Instructor, NYU Courant Institute, Graduate Division, Computer Science, and NYU Stern School of Business.