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Advanced Kubernetes and Docker Workshop

From This Docker and Kubernetes Training Course, You will gain in-depth skills of the Deploying, scaling microservices, usage and maintaining the aplications in Docker and Kubernetes, with real-world examples from industry experienced trainers.
  • Training Type
    Live Training
  • Category
    DevOps
  • Duration
    24 Hours
  • Rating
    4.8/5
Advanced Kubernetes and Docker Workshop

Docker and Kubernetes Training Course Introduction

About Docker and Kubernetes Training Course

On days 1 you will center on developing the skills and knowledge needed for orchestrating workloads on Kubernetes. Understanding containerization and everything required to deploy application on Kubernetes. On day 2, you will deploy an actual microservice application on Kubernetes cluster deployed on AWS , different type of workloads, providing storage and how to enable logging and monitoring using industry standard tools like Elastic Stack, Prometheus and Grafana. On day 3, you will learn more advanced concepts on Kubernetes such as RBAC, network policies, Taints & Toleration and Using Helm package manager.

Docker and Kubernetes Training Course Objective

Participants should understand development workflow and should be familiar with build tools, source management with git, branching, automated testing, build and deployment automation.

Who is the Kubernetes Training Course Target Audience?

Devops Engineer or Data Engineer who want to start using Kubernetes

What Basic Knowledge Required to Learn Kubernetes Training?

Though there are no prerequisites. However, basic Knowledge of working with Linux & AWS will be add on.

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Docker and Kubernetes Training Course Curriculum
Total Duration : 24 Hours
Dockers Overview
  • What is Containerization  
  • Creating your first container  
  • Understanding Docker Architecture  
  • Building and pushing Docker Images  
Kubernetes Overview
  • What is Kubernetes  
  • Kubernetes Architecture  
  • Working with Kubernetes basic components  

    Pods, Deployment, ReplicaSet and Namespaces

Managing Application Deployment
  • Orchestrating workloads using pods on worker nodes  
  • Examine the node selector  
  • Discuss implementing the impact of taints and tolerations for Kubernetes workloads  
  • Review both pod and node affinity and anti-affinity  
Releasing Application Updates
  • Working with Kubernetes Deployment  
  • Release updates to applications running on the Kubernetes platform  
  • Working with various deployment strategies- Green/Blue and Canary  
Multi-Tenancy in Kubernetes
  • Discuss multi-tenancy in a Kubernetes cluster  
  • Using Namespace to achieve multi tenancy  
  • Assigning Resource Quota/Limit Ranges to namespaces  
Configuring Application
  • Using config Maps and environment variables  
  • Using Secrets for configuring confidential information  
Understanding different workloads
  • Working with Stateful Sets  
  • Working with DaemonSet  
  • Working with Cronjobs/Jobs  
Deploying Microservices Application on AWS
Logging and Monitoring Kubernetes
  • Deploy and configure the Elastic Stack logging stack, and use it to browse container logs  
  • Deploying Prometheus and Grafana for monitoring  
Provisioning Storage
  • Review available storage options for applications  
  • Discuss constraints of persistent storage in a standard Kubernetes cluster deployment  
  • Examine the storageClass object  
Kube Security: Implementing RBAC
  • Discuss RBAC implementation within Kubernetes  
  • Examine Kubernetes RBAC components  
  • Review Auditing within Kubernetes  
  • Determine how to enable Auditing within a Kubernetes cluster  
Routing Network Traffic
  • Discuss network routing options within Kubernetes  
  • Discuss the benefits of the Ingress controller and object  
  • Examine the Ingress object and controller pattern  
Using Helm Package Manager
  • Understanding Helm  
  • Using helm to deploy and manage applications on Kubernetes