Load Testing ML Microservices for Robustness and Scalability

Feb 10, 2022 1 min read

About The Demo

The demo is aimed at getting started with load testing a microservice before taking it to production. We use FastAPI microservice (to predict weather) and Locust to load test the service (locally or on cloud). You can find detailed instructions in the Engineering MLOps book.

Built With

Major frameworks used to build the project:

Installation

These are instructions to install and get the services up and running.

Clone the repo

git clone https://github.com/emmanuelraj7/loadtesting-microservices.git

Install Locust.io
```
pip install locust
```
Go to FastAPI_microservice folder and build the FastAPI service docker image
```
docker build -t fastapi .
```
Run the FastAPI service docker container locally
```
docker run -d -p 80:80 fastapi
```
Go to Load_testing folder and run locust.io service for load testing
```
Locust -f load_test-py
```

License

Distributed under the MIT License. See LICENSE for more information.

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