- Update config.yaml
- Update secrets.yaml [Optional]
- Update params.yaml
- Update the entity
- Update the configuration manager in src config
- Update the components
- Update the pipeline
- Update the main.py
- Update the dvc.yaml
- mlflow ui
MLFLOW_TRACKING_URI=https://dagshub.com/faseehahmed26/CCC-Application.mlflow
MLFLOW_TRACKING_USERNAME=faseehahmed26
MLFLOW_TRACKING_PASSWORD=68de35679ce0a31d34f8eb9ff6a37374a64a4ad3
python script.py
Run this to export as env variables:
export MLFLOW_TRACKING_URI=https://dagshub.com/faseehahmed26/CCC-Application.mlflow
export MLFLOW_TRACKING_USERNAME=faseehahmed26
export MLFLOW_TRACKING_PASSWORD=68de35679ce0a31d34f8eb9ff6a37374a64a4ad3
- dvc init
- dvc repro
- dvc dag
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)
#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: 566373416292.dkr.ecr.us-east-1.amazonaws.com/chicken
#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
setting>actions>runner>new self hosted runner> choose os> then run command one by one
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