Chicken-Disease-Classification-Using-MLflow

Workflows

1. Update config.yaml
2. Update secrets.yaml [Optional]
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 dvc.yaml

How to run?

STEPS:

Clone the repository

https://github.com/HARSHALKUMRE/MLflow-DVC-Chicken-Disease-Classification

STEP 01- Create a conda environment after opening the repository

conda create -n cnncls1 python=3.9 -y

conda activate cnncls1

STEP 02- install the requirements

pip install -r requirements.txt

# Finally run the following command
python app.py

Now,

open up you local host and port

DVC cmd

1. dvc init
2. dvc repro
3. dvc dag

MLflow

Documentation

cmd

• mlflow ui

dagshub

dagshub

MLFLOW_TRACKING_URI=https://dagshub.com/HARSHALKUMRE/MLflow-DVC-Chicken-Disease-Classification.mlflow MLFLOW_TRACKING_USERNAME=HARSHALKUMRE MLFLOW_TRACKING_PASSWORD=<MLFLOW_TRACKING_PASSWORD> python script.py

Run this to export as env variables:

export MLFLOW_TRACKING_URI=https://dagshub.com/HARSHALKUMRE/MLflow-DVC-Chicken-Disease-Classification.mlflow

export MLFLOW_TRACKING_USERNAME=HARSHALKUMRE

export MLFLOW_TRACKING_PASSWORD=6824692c47a369aa6f9eac5b10041d5c8edbcef0 

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: 4334534238.dkr.ecr.us-east-1.amazonaws.com/chicken

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_ACCESS_KEY_ID>

AWS_SECRET_ACCESS_KEY=<AWS_SECRET_ACCESS_KEY>

AWS_REGION = ap-south-1

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

ECR_REPOSITORY_NAME = simple-app

AZURE-CICD-Deployment-with-Github-Actions

Save pass:

s3cEZKH5yytiVnJ3h+eI3qhhzf9q1vNwEi6+q+WGdd+ACRCZ7JD6

Run from terminal:

docker build -t chickenapp.azurecr.io/chicken:latest .

docker login chickenapp.azurecr.io

docker push chickenapp.azurecr.io/chicken:latest

Deployment Steps:

1. Build the Docker image of the Source Code
2. Push the Docker image to Container Registry
3. Launch the Web App Server in Azure
4. Pull the Docker image from the container registry to Web App server and run

About MLflow & DVC

MLflow

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

DVC

• Its very lite weight for POC only
• lite weight expriements tracker
• It can perform Orchestration (Creating Pipelines)