- Vs code: https://code.visualstudio.com/download
- Git: https://git-scm.com/
- Flowchart: https://whimsical.com/
- MLOPs Tool: https://www.evidentlyai.com/
- MongoDB: https://account.mongodb.com/account/login
- Data link: https://www.kaggle.com/datasets/moro23/easyvisa-dataset
git add .
git commit -m "Updated"
git push origin main
conda create -n visa python=3.10 -y
conda activate visa
pip install -r requirements.txt
- Constants
- Entities
- Components
- Pipeline
- Main file
Option 1: Include the variables inside your .env file as:
MONGODB_CREDENTIAL="mongodb+srv://<username>:<password>...."
AWS_ACCESS_KEY_ID=<AWS_ACCESS_KEY_ID>
AWS_SECRET_ACCESS_KEY=<AWS_SECRET_ACCESS_KEY>
Option 2: Include the above credintials/URLs in your OS system environment as environment varaibles.
export MONGODB_URL="mongodb+srv://<username>:<password>...."
export AWS_ACCESS_KEY_ID=<AWS_ACCESS_KEY_ID>
export AWS_SECRET_ACCESS_KEY=<AWS_SECRET_ACCESS_KEY>
#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
- Save the URI: E.g: "480865595393.dkr.ecr.us-east-1.amazonaws.com/visa"
#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
Repo Setting > Actions > Runner > new self-hosted runner > choose os (Linux) > then copy and run the connection and config commands in the EC2 terminal.
- AWS_ACCESS_KEY_ID
- AWS_SECRET_ACCESS_KEY
- AWS_DEFAULT_REGION
- ECR_REPO
- MONGODB_URL