https://github.com/sathviknayak123/wine-ml
End-to-End ML project to predict wine quality. Learning ML Project Life-cycle.
https://github.com/sathviknayak123/wine-ml
aws-ec2 docker flask github-actions html-css machine-learning
Last synced: 3 months ago
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End-to-End ML project to predict wine quality. Learning ML Project Life-cycle.
- Host: GitHub
- URL: https://github.com/sathviknayak123/wine-ml
- Owner: SathvikNayak123
- Created: 2024-08-03T08:49:47.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-04T10:07:45.000Z (almost 2 years ago)
- Last Synced: 2025-01-17T07:09:49.821Z (over 1 year ago)
- Topics: aws-ec2, docker, flask, github-actions, html-css, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 254 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Workflows
- 1. create GitHub repo with .gitignore
- 2. create env
- 3. code setup.py
- 4. install requirements.txt
- 5. run template.py
- 6. update config, params and schema.yaml
- 7. update utils common.py
- 8. update constants __init__.py
repeat for every stage:
- update config.yaml
- update enitiy_config
- update configuaration_manager
- update components
- update pipeline
- update main.py
- 10. run main.py
- 11. create class PredictPipeline in pipepline
- 12. create flask app
- 13. docker
- 14. create .github/workflows/cicd.yaml
## 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
# 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: dem0>> 136566696263.dkr.ecr.us-east-1.amazonaws.com/mlproject
## 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