It's Capstone Udacity project to actually apply DevOps engineer skills and it requires a few steps:

• Test project code using linting.

• Build and test a Docker file to containerize the application.

• build the image and push it to dockerhub.

• Create a kubernetes deployment and test it locally with minikube.

• Create our deployment file that is going to use the image that is in docker hub.

• Create a service that makes the containers publicly accessible.

• Create a cluster locally using minikube.

• Deploy the service and the deployment to the cluster locally and test that the application works.

• Project demonstrate implemnting docker image and kubernetes using Circleci pipeline.

• In this project Circleci orbs has been used:

  • circleci/[email protected]
  • circleci/[email protected]

• Create a Circleci pipeline to automate the processes:

  • linting.
  • building the docker image.
  • pushing the image to dockerhub.
  • deploying the containers to the kubernetes cluster.

• Upload a complete Github repo with CircleCI to indicate that the code has been tested.

• requirements.txt: all dependencies to be installed.
• app.py: The python API starter source code.
• Makefile: the defination of the helper commands.
• Dockerfile: defination of the container content.
• deployment.yml: deployment file that is going to use the image that is in docker hub, also contains a service that makes the containers publicly accessible.
• config.yml: circleci configuration file that is going to automate everything in this project.

• Create a virtualenv and activate it: python3 -m venv .devops-proj4 && source ~/.devops-proj4/bin/activate

• Run make install to install the dependencies defined in requirements.txt file

• optional test app.py: python app.py

• run lint: make lint

• build and upload docker by completing the two files ./run_docker.sh and ./upload_docker.sh, then

  1. Setup requirements for docker such as Login credentials.
  2. Run app.py in Docker: ./run_docker.sh
  3. Upload it: ./upload_docker.sh

• Kubernetes instructions and steps as following:

  1. Setup requirements for kubernetes such as installing minikube and hypervisor.
  2. First start your minikube cluster: (minikube start)
  3. run script run_kubernetes.sh
  4. apply the deployment.yml locally that is going to make the containers publicly accessible

 steps:
   - checkout
   - restore_cache:
       keys:
         - v1-dependencies-{{ checksum "requirements.txt" }}
         - v1-dependencies-
   - run:
       name: install dependencies
       command: |
         python3 -m venv venv
         . venv/bin/activate
         make install
         # Install hadolint
         sudo wget -O /bin/hadolint https://github.com/hadolint/hadolint/releases/download/v1.16.3/hadolint-Linux-x86_64 &&\
         sudo chmod +x /bin/hadolint
   - save_cache:
       paths:
         - ./venv
       key: v1-dependencies-{{ checksum "requirements.txt" }}
   - run:
       name: run lint
       command: |
         . venv/bin/activate
         make lint 

aws-eks/create-cluster:
      cluster-name: gsvcapstone

  parameters:
    cluster-name:
      description: |
        proj5-capstone1
      type: string
  steps:
    - checkout
    - kubernetes/install
    - aws-eks/update-kubeconfig-with-authenticator:
        cluster-name: << parameters.cluster-name >>
        install-kubectl: true
    - kubernetes/create-or-update-resource:
        get-rollout-status: true
        resource-file-path: deployment.yml
        resource-name: deployment/proj5-capstone1

aws-eks/update-container-image:
  cluster-name: gsvcapstone
  container-image-updates: gsvcapstone=proj4mlmicroservice/proj5-capstone
  post-steps:
      - kubernetes/delete-resource:
          resource-names: proj5-capstone
          resource-types: deployment
          wait: true
  record: true
  requires:
      - create-deployment
  resource-name: deployment/proj5-capstone

  parameters:
    cluster-name:
      description: |
        proj5-capstone1
      type: string
  steps:
    - kubernetes/install
    - aws-eks/update-kubeconfig-with-authenticator:
        cluster-name: << parameters.cluster-name >>
    - run:
        name: Test cluster
        command: |
          kubectl get svc
          kubectl get nodes
          kubectl get deployment

• https://circleci.com/developer/orbs/orb/circleci/kubernetes
• https://circleci.com/developer/orbs/orb/circleci/aws-eks