Finder Application

Challenge: Design a system which can store and index a large number of places

Prototype

Prototype built using:

• Redis - database backend
• Falcon - web framework
• Docker and docker compose - container environment

To get up and running, run:

docker-compose up

The web interface will be availabe at http://localhost:8000

The seed_db_with_random_places.py script is used to populate redis with random data, the command to run is:

docker-compose run app python seed_db_with_random_places.py

Design considerations

• High performance throughput
• data oriented as key-value

Assumptions made

• Data store size remains relatively constant (slow growth)
• API's radius units are in meters.

Future improvements

• Use a production grade HTTP server such as Nginx infront of Gunicorn
• Disable Transparent Huge Tables for redis - better performance
• Tune redis's fsync settings
• Explore docker networking stack - default setting may not be ideal

Performance report

Used locust for benchmarking. Results are availabe in the benchmarks folder including screenshots.