Initial Requirments
Tools: Linux, Docker , AWS account, kubectl, VS Code Language: Python-3(Flask, psutil)
Important Note if you want to start this project
AWS is risky and every thing is not not free in Free tier 🤖😥I got bill of (4.70$ + 0.85$(TAX) = 5.55$ ) bill while working on this project So don't leave any EKS/ECR/ECS service active for 2-3 days just for project 💔
some links which may help --- CloudTrail: https://aws.amazon.com/cloudtrail/getting-started/ CloudWatch: http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-cloudwatch.html Budgets: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/budgets-managing-costs.html
Install & use Docker (manage containers)
https://docs.docker.com/engine/install/ubuntu/
https://hub.docker.com/
https://labs.play-with-docker.com/
AWS (Free Tier Account)
setup aws terminal CLI tool in linux.
Create user and generate 'access key' so that we can intract with it locally.
provide CLI permission with programmatic access.
// some commands aws configure aws iam list-users
kubectl is a tool to manage multiple kubernetes containers through local terminal setup itt as well as we have did for aws or docker or git
Psutil >> Psutil is a Python library for retrieving information about processes and system utilization, including CPU usage, memory usage, disk I/O, network I/O, and more. The name "psutil" stands for "process and system utilities".
Flask >> like express JS ; Flask is a lightweight and flexible web application framework for Python. It is classified as a micro-framework because it does not require particular tools or libraries, and it doesn't impose a particular way of structuring your application.
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1> Create basick Flask application using 'psutil' library which displays cpu and memory status on browser root addres.
2> create html template for the app with 'plotly' framework
3> create a docker file which will create image based on the given commands
some commands for docker build imag // docker build -t my-flask-app .
show images // docker images
create cont.(run) // docker run -p 5000:5000
login // docker exec -it <container_name_or_id> bash
stop // docker stop my-container
start // docker start my-container
remove stopped containers // docker rm my-container
4> Create ECR repo using Boto3 API and deploy the image (creaet ECR repo, upload docker image in ecr repo, create EKS cluster )
create python file (ecrfile.py)
write python code using Boto3 API and deploy the image on aws ecr.
import boto3
ecr_client = boto3.client('ecr')
repository_name = "my-repo-app-aws"
response = ecr_client.create_repository(repositoryName = repository_name)Now run the following commands to
Retrieve an authentication token and authenticate your Docker client to your registry. Use the AWS CLI:
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 404426248672.dkr.ecr.us-east-1.amazonaws.com
Note: If you receive an error using the AWS CLI, make sure that you have the latest version of the AWS CLI and Docker installed.
Build your Docker image using the following command. For information on building a Docker file from scratch see the instructions here . You can skip this step if your image is already built:
docker build -t my-repo-app-aws .
After the build completes, tag your image so you can push the image to this repository:
docker tag my-repo-app-aws:latest 404426248672.dkr.ecr.us-east-1.amazonaws.com/my-repo-app-aws:latest
Run the following command to push this image to your newly created AWS repository:
docker push 404426248672.dkr.ecr.us-east-1.amazonaws.com/my-repo-app-aws:latest
5> Create EKS(Elastic Kubernetes Service) cluster
AWS services> EKS> Add Cluster> Create
6> kubernetes deployment and services
kubernetes uses deployment to maintain the state // resources
https://kubernetes.io/docs/concepts/workloads/controllers/deployment/
our application runs on pods and we uses Service method for exposing a network application that is running as one or more Pods in your cluster.
// terminal commands for Kubectl
// check of deployments
kubectl get deployment -n default
// update deployments (first image url in eksfile.py then change from console);
kubectl edit deployment <dep. name> -n default
# this command will open editable file in 'vim terminal' change containers>image link
# to save and exit => 'esc + :wq'
// check of pods
kubectl get pods -n default -w
// all the details regarding pods
kubectl describe pods <pod name> -n default
// check of services
kubectl get svc -n default
// port-forward ; run pods in localhost
kubectl port-forward svc/my-flask-service 5000:5000
End now our app has been hosted on kubernetes cluster <