Enterprise MLOps Project Template
An enterprise grade Machine Learning project scaffold for streamlining MLOps best practices.
Features
- Quickly create dev/prod environments
- MLOps Best Practices at heart
- Bring your own project to enterprise grade repository
- CI/CD Integrations
- Micro-Service Architecture
- Cross platform/ Multi-Cloud Architecture
- Scientist/DataEng/MLEng/PlatformEng teams can collaborate easily
Usage
Write your own files suited to each category folder.
Example: Writing a Makefile for the project
install:
pip install --upgrade pip &&\
pip install -r requirements.txt
install-azure:
pip install --upgrade pip &&\
pip install -r requirements-azure.txt
format:
black *.py
lint:
pylint --disable=R,C hello.py
lint Dockerfile
docker run --rm -i hadolint/hadolint < Dockerfile
test:
python -m pytest -vv --cov=hello test_hello.py
deploy:
echo "deploy goes here"
all: install lint test
Example: Writing a Terraform for the project as Docker
terraform {
required_providers {
docker = {
source = "kreuzwerker/docker"
version = "~> 2.13.0"
}
}
}
provider "docker" {}
resource "docker_container" "lamda_terraform" {
image = "lamda_test"
name = "lamda-terraform"
ports {
internal = 8080
external = 9000
}
}Roadmap
- Add jenkins support
- Add kubernetes scale-out template
- Add demo infrastucture code
Feedback
If you have any feedback, please reach out to me at saiham.rahman@outlook.com