MLOPS-PROJECT

Workflows

1. Update config.yaml
2. Update schema.yaml
3. Update params.yaml
4. Update the entity
5. Update the configuration manager in src config
6. Update the components
7. Update the pipeline
8. Update the main.py
9. Update the app.py

How to run?

STEPS:

Clone the repository

https://github.com/hamza-amin-4365/MLOPS-Project.git

STEP 01- Create a virtual environment after opening the repository

python -m venv mlproj

source mlproj/bin/activate  # On Windows use `mlproj\Scripts\activate`

STEP 02- install the requirements

pip install -r requirements.txt

# Finally run the following command
python app.py

MLflow

Documentation

dagshub

dagshub

import dagshub
dagshub.init(repo_owner='_____', repo_name='______', mlflow=True)

import mlflow
with mlflow.start_run():
  mlflow.log_param('parameter name', 'value')
  mlflow.log_metric('metric name', 1)

Run this to integrate MLFOW in your local envirnment

AWS-CICD-Deployment-with-Github-Actions

1. Login to AWS console.

2. Create IAM user for deployment

#with specific access

1. EC2 access : It is virtual machine

2. ECR: Elastic Container registry to save your docker image in aws


#Description: About the deployment

1. Build docker image of the source code

2. Push your docker image to ECR

3. Launch Your EC2 

4. Pull Your image from ECR in EC2

5. Lauch your docker image in EC2

#Policy:

1. AmazonEC2ContainerRegistryFullAccess

2. AmazonEC2FullAccess

3. Create ECR repo to store/save docker image

- Save the URI: 851725347557.dkr.ecr.ap-south-1.amazonaws.com/mlops_proj

4. Create EC2 machine (Ubuntu)

5. Open EC2 and Install docker in EC2 Machine:

#optinal

sudo apt-get update -y

sudo apt-get upgrade

#required

curl -fsSL https://get.docker.com -o get-docker.sh

sudo sh get-docker.sh

sudo usermod -aG docker ubuntu

newgrp docker

6. Configure EC2 as self-hosted runner:

setting>actions>runner>new self hosted runner> choose os> then run command one by one

7. Setup github secrets:

AWS_ACCESS_KEY_ID=

AWS_SECRET_ACCESS_KEY=

AWS_REGION = us-east-1

AWS_ECR_LOGIN_URI = demo>>  566373416292.dkr.ecr.ap-south-1.amazonaws.com

ECR_REPOSITORY_NAME = simple-app

About MLflow

MLflow

• Its Production Grade
• Trace all of your expriements
• Logging & tagging your model