Kubernetes Series 20/Oct/2019

Running Docker and K8S Workloads on Cloud (AWS and Azure)


Docker in Azure

Docker in AWS

  • Elastic Container Services (ECS):
    • EC2 Machine Based:
      • Create a ec2 machine with particular ami
      • You can group ec2 machines with that image to a cluster
      • Create Task Definition with Docker Commands
      • These tasks can be executed as servcies
      • Paying bill for ec2 machines
    • Fargate:
      • Paying only for containers which you are running.
  • Elastic Container Registry (ECR):
  • Elastic BeanStalk

Kubernetes on Cloud

  • Kubernetes has master and worker nodes.
  • Cloud providers offerings such as AKS/EKS/GKE
    • master nodes are managed by Cloud provider
    • Authentications integrated with cloud authentications (AWS => IAM, Azure => AAD)
    • Monitoring and logging integrated with Cloud Solutions
    • Cloud provider storage options

Azure Kubernetes Services (AKS)

Creating AKS Cluster

Amazon Elastic Kubernetes Services (EKS)


  • Even in the case of k8s we want the container lifecycle to be separated from Storage/Volume Life cycle

  • K8s has majorly the following options

    • Volumes
    • Persistent Volumes
  • Refer here for AKS

Docker & Kubernetes DevOps Workflow.


Important Activities


  • Create a Game of life Deployment with autoscaling enabled for pods if cpu utilization is greater that 80%. Tomcat webapps or logs folder should be persisted. Ensure your are storing docker image in DockerHub or ACR or ECR

  • Create a Game of life Docker Container which takes service ip address as input while running the container. Prove this on Kubernetes

  • How to Submit Exercise?

    • Write a mail to qtdevops@gmail.com with your git hub repository containing the YAML and Dockerfiles. You can also use attachments.
    • In the mail enter your gmail id & you will have a hangout call.

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devops & cloud enthusiastic learner