Bloomreach Exponea API challenge

Getting started

There are three ways to run the app:

To run it from the source code:

Clone the repository to a local machine
From ./bloomreach_interview/api directory
execute pip install -r requirements.txt
run main.py or execute uvicorn main:app

To run it with docker:

Clone the repository to a local machine
From ./bloomreach_interview/api directory
Execute commands:
docker build -t bloomreach_api .
docker run -p 8000:8000 --name bloomreach_api bloomreach_api

To run it with docker compose:

This will also start Prometheus and Grafana services

Clone the repository to a local machine
Execute command:
docker-compose up

Fetching the API

Send an HTTP GET request to endpoint

http://127.0.0.1:8000/api/smart?timeout=1500

For accessing OpenApi documentation: localhost:8000/
JSON OpenApi endpoint: localhost:8000/openapi.json
FastAPI metrics endpoint: localhost:8000/metrics
Prometheus endpoint: localhost:9090
Grafana Endpoint: localhost:3000

Configuring

To configure the server check the docker-compose.yml file and set the environmental variables to your liking. If you don't want to use docker compose, you can change the default variables in the config.py directly
To configure Grafana credentials check env.example file and rename it to env. You can also modify dashboard with dashbords/fastapi-dashboard.json
To configure Prometheus check datasource.yml

Additional Information

Terraform

There is a script for creating ec2 t2.micro server on AWS, and installing all the packages needed to run this app with docker-compose. All the commands for executing this are listed below:

terraform init

terraform validate

terraform plan

terraform apply

Responsible file - init.tf, and instructions.sh for bash initialization script

Technologies used

Python 3.10
FastAPI framework
Various libraries for python: httpx, asyncio, pytest, prometheus-fastapi-instrumentator, uvicorn
Prometheus image for monitoring the system
Grafana for analytics and dashboards
Terraform for quicker deployment on dev servers in the cloud
Docker with docker-compose plugin for containerization and deployment
GitHub as repository host

Logs

Logs can be checked in the shell where you ran the app, or in api.log file with better formatting.

To set log-level check LOGLEVEL variable in config.py file.

Testing

Check the report directory, I hope it's self explanatory.

Testing was done using jMeter with plugins for Transactions per Second and Requests per Second metrics.

I regret not having more time to add unit and integration testing for the project. I would have added various tests covering smart endpoint and it's behaviour in different circumstances, such as low/high timeout parameter values, simulating low system resources avaliability, etc.

LordNani/bloomreach_interview