Final Exam: Solutions for Multi-cloud Load Balancing

WHAT YOU WILL LEARN

• 

  bootstrap a real Kubernetes cluster with 4 nodes
  

  compare and contrast various cloud-based load balancer providers
  

  compare and contrast various hardware load balancer providers
  

  configure data backup in AWS
  

  configure data backup in GCP
  

  configure data backup in Microsoft Azure
  

  define hardware load balancer and describe the benefits and challenges of using hardware load balancers
  

  define virtual load balancer and describe the benefits and challenges of using virtual load balancers
  

  demonstrate how to configure a swarm on ubuntu linux
  

  demonstrate how to install, configure and test docker on ubuntu linux
  

  demonstrate how to install Kubernetes on an ubuntu linux based system
  

  demonstrate network traffic management in Kubernetes using network policies
  

  describe basic and native docker load balancing scenarios, including load balancing with nginx load balancer and using swarm mode
  

  describe docker engine, docker client, docker registries
  

  describe docker objects including images, containers, volumes, networks, docker swarm, docker compose
• 

  describe how fully managed cloud services compare to self-managed services
  

  describe how services are used to abstract a logical set of Pods and a policy by which to access them and how this pattern is also referred to as a micro-service
  

  describe Kubernetes components and architecture focusing on their specific roles, control plane, worker node, and discuss add-ons
  

  describe Kubernetes objects like pods, deployments, replicasets, daemonsets, ingress, services and how they are created and managed using a declarative versus imperative approach
  

  describe the best practices for performance monitoring on multi-cloud environments, including hybrid cloud
  

  describe the overall role of load balancers in improving performance
  

  describe the performance challenges introduced by multi-cloud environments
  

  discuss how data backup strategies work in GCP
  

  discuss the challenges of DBAR in cloud environments
  

  discuss the concept of failover in multi-cloud, how it relates to load balancing, and how it improves reliability
  

  discuss the history of backups, restores and disaster planning
  

  discuss the significance of performance monitoring on-premises and in the cloud
  

  monitor metrics with AWS CloudWatch
  

  recognize docker objects including images, containers, volumes, networks, docker swarm, docker compose
  

  talk about how k8s works with containers, images, and Pods to deploy containerized apps and services and how it aligns with CI/CD and microservices