Docker and Kubernetes Bootcamp

Course Code: 3007



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.

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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


  • 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
  • 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
  • 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)
  • Listing resources
  • Deleting resources
  • Watching resource changes with kubectl
  • Editing resources with kubectl
  • Asking kubectl to explain resources and fields
  • 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
  • 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
  • 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
  • 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
  • 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
  • Scaling a deployment
  • Automatically resizing a cluster in GKE
  • Automatically resizing a cluster in AWS
  • Using horizontal pod autoscaling on GKE
  • Providing a unique identity for an application
  • Listening and viewing access control information
  • Controlling access to resources
  • Securing pods
  • 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
  • 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
  • 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)
  • 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
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  • Basic command knowledge of Linux
  • Basic understanding of DevOps
  • Basic knowledge of YAML programming language (beneficial, not mandatory)

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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

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.

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.

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.

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

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.

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.