Docker and Kubernetes Bootcamp

Course Code: 3007

$899

Overview
Schedule classes
What you'll learn
Outline
Prerequisites
Certification

Overview

Kubernetes is an open-source orchestration system for automating management, placement, scaling and routing of containers. It provides an API to control how and where the containers would run. Docker is also an open-source container-file format for automating the deployment of applications as portable, self-sufficient containers that can run in the cloud or on-premises. Together, Kubernetes and Docker have become hugely popular among developers, especially in the DevOps world.

Both Docker and Kubernetes are huge open-source technologies, largely written in the Go programming language, that use human-readable YAML files to specify application stacks and their deployment.

Cognixia brings to you a unique bootcamp covering basic to advanced-level concepts of Docker and Kubernetes. The bootcamp offers an engaging and immersive learning experience for participants where they can take advantage of connecting with an industry expert trainer, develop their competencies to meet industry and organizational standards, as well as learn about real-world best practices.

Schedule Classes

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Course Delivery

This course is available in the following formats:

Live Virtual Classroom
Duration: 10 days

What You'll learn

Fundamentals of Docker
Fundamentals of Kubernetes
Running Kubernetes instances on Minikube
Creating and working with Kubernetes clusters
Working with resources
Creating and modifying workloads
Working with Kubernetes API and key metadata
Working with specialized workloads
Scaling deployments and application security
Understanding the container ecosystem

Outline

Module 1: Docker essentials

Docker introduction
Docker architecture
Docker installation on Red Hat and Ubuntu OS
Working with images (Docker Hub, Docker Registry)
Working with containers
Container networking
Working with volumes and persistent data
Managing container apps using Docker Swarm
Overview of Docker Enterprise tool

Module 2: Minikube

Using Kubernetes without installation
Installing the Kubernetes CLI, kubectl
Installing Minikube to run a local Kubernetes instance
Using Minikube locally for development
Starting your first application on Minikube
Accessing the dashboard in Minikube

Module 3: Kubernetes cluster

Installing kubeadm to create a Kubernetes cluster
Bootstrapping a Kubernetes cluster using kubeadm
Downloading a Kubernetes release from Github
Downloading client and server binaries
Using a hyperkube Image to run a Kubernetes master node with Docker
Writing a systemd unit file to run Kubernetes components
Creating a Kubernetes Cluster on Google Kubernetes Engine (GKE)
Creating a Kubernetes Cluster on Azure Container Service (ACS)

Module 4: Kubernetes client

Listing resources
Deleting resources
Watching resource changes with kubectl
Editing resources with kubectl
Asking kubectl to explain resources and fields

Module 5: Creating and modifying workloads

Creating a deployment using kubectl run
Creating objects from file manifests
Writing a pod manifest from scratch
Launching a deployment using a manifest
Updating a deployment

Module 6: Services

Creating a service to expose your application
Verifying the DNS entry of a service
Changing the type of a service
Deploying an ingress controller on Minikube
Making services accessible from outside the cluster

Module 7: Exploring the Kubernetes API and key metadata

Discovering the API endpoints of the Kubernetes API server
Understanding the structure of a Kubernetes manifest
Creating namespaces to avoid name collisions
Setting quotas within a namespace
Labeling an object
Using labels for queries
Annotating a resource within one command

Module 8: Managing specialized workloads

Running a batch job
Running a task on a schedule within a pod
Running infrastructure daemons per node
Managing stateful and leader/follower apps
Influencing pods’ startup behavior

Module 9: Volumes and configuration data

Exchanging data between containers via a local volume
Passing an API access key to a pod using secrets
Providing configuration data to an application
Using a persistent volume with Minikube
Understanding data persistency on Minikube
Dynamically provisioning persistent storage on GKE

Module 10: Scaling

Scaling a deployment
Automatically resizing a cluster in GKE
Automatically resizing a cluster in AWS
Using horizontal pod autoscaling on GKE

Module 11: Security

Providing a unique identity for an application
Listening and viewing access control information
Controlling access to resources
Securing pods

Module 12: Monitoring and logging

Accessing the logs of a container
Recover from a broken state with a liveness probe
Controlling traffic flow to a pod using a readiness probe
Adding liveness and readiness probes to your deployments
Enabling Heapster on Minkube to monitor resources
Using Prometheus on Minikube
Sing Elastic Search-Fluentd-Kibana (EFK) on Minikube

Module 13: Maintenance and Troubleshooting

Enabling autocomplete for kubectl
Removing a pod from a service
Accessing a ClusterIP service outside the cluster
Understanding and parsing resource statuses
Debugging pods
Getting a detailed snapshot of the cluster state
Adding Kubernetes worker nodes
Draining Kubernetes nodes for maintenance
Managing etcd

Module 14: Developing Kubernetes

Compiling from source
Compiling a specific component
Using a Python client to interact with the Kubernetes API
Extending the APU using Custom Resource Definitions (CRD)

Module 15: The ecosystem

Installing Helm, the Kubernetes package manager
Sing Helm to install applications
Creating your own chart to package your applications with Helm
Converting your Docker compose files to Kubernetes manifests
Creating a Kubernetes cluster with Kubicorn
Storing encrypted secrets in version control
Deploying functions with kubeless

Prerequisites

Basic command knowledge of Linux
Basic understanding of DevOps
Basic knowledge of YAML programming language (beneficial, not mandatory)

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Certification

Once the course is completed, you need to appear for an objective question-based assessment conducted by Cognixia. Based on your performance on different parameters such as attendance in the sessions, assessment scores, etc. you will be awarded a certificate by Cognixia.

Course Decsription

What is the current outlook for Docker and Kubernetes globally?

Gartner predicts that by 2023, 70% of the organizations will be running three or more containerized applications in production. Containers, Kubernetes and Microservices application patterns are the three main drivers of enterprise IT innovation and digital transformation. The number of organizations that have containerized more than half of their applications is currently growing at a pace of close to 22%. Docker and Kubernetes are two of the most popular tools bridging the gap between Development and Operations today, and are shaping the future of business architecture. The future outlook for these tools is very positive, and with time, their demand and applications are going to grow manifold.

How important is a Docker and Kubernetes certification for my career?

Docker and Kubernetes s one of the top 10 fastest rising tech skills today, according to Indeed. During the four-year period between October 2015 to October 2019, the share of Kubernetes jobs per million grew by 2141.03% and the share of Kubernetes job searches increased by 2125.66%. The top five tech roles related to Docker and Kubernetes are DevOps engineer, Software engineer, Software architect, Cloud engineer and Full stack developer. With such a huge demand in the market, a certification in Docker and Kubernetes from a globally recognized institution would set you apart in the crowd, would add immense value to your resume, and validate your skills and expertise in the field.

Is the Docker and Kubernetes training and certification offered by Cognixia globally recognized?

Yes, the Docker and Kubernetes training and certification offered by Cognixia is globally recognized. This certificate is given out by Cognixia itself upon successful completion of the training and clearing the assessments, as well as other parameters. You can add this credential to your resume, your LinkedIn profile, share it on social media, as well as present it along with your resume as a validation of your skills in Docker and Kubernetes.

What does this Docker and Kubernetes training cover?

The Docker and Kubernetes training offered by Cognixia covers:

Fundamentals of Docker
Fundamentals of Kubernetes
Running Kubernetes instances on Minikube
Creating and working with Kubernetes clusters
Working with resources
Creating and modifying workloads
Working with Kubernetes API and key metadata
Working with specialized workloads
Scaling deployments and application security
Understanding the container ecosystem

Who is this Docker and Kubernetes training course for?

This Docker and Kubernetes training course is best suited for current and aspiring DevOps developers, DevOps engineers, Java developers, C# and .Net developers, Software engineers, Backend developers, IoT architects and Quality Assurance engineers.

What are the prerequisites for this Docker and Kubernetes training course?

For this Docker and Kubernetes training and certification course, participants need to have a basic command knowledge of Linux and a basic understanding of DevOps. Having a fundamental knowledge of YAML programming language would be beneficial.