Dockers & Kubernets Professional Training


Kubernet and Dockers are the two most popular online courses which are being offered by Max Online Training. Though they are better when they are together yet have a basic difference between the two. Kubernets is for the cluster run while on other hand Dockers is for the run on single node. Kubernets is found to be more extensive than the Dockers which can run efficiently for cluster nodes.

But the infrastructure can be made more effective when you run Kubernetes with Docker which can give you an ultimate result. It can make you software robust, and highly available too. In cases any nodes gets offline, the other nodes will show offline.

So if you are interested in learning the Kubernetes and the Dockers for efficient run of the nodes, then you must take up the Dockers and Kubernetes online training.We offer you the Dockers and Kubernetes certification course where we will provide you certificate after the successful completion of the course.

Things you will learn in the Dockers and Kubernetes online corporate training by Max Online Training are:

  • What is docker and Kubernetes
  • The basic and fundamentals
  • Understanding docker engine and the swarm
  • Kubernetes orchestration
  • POC

In case you are a system administrator or developer or anyone who is basically engaged with the OOPs and the DevOps work, they can easily do this course to learn new thing and keep themselves updated.

This is a great way of learning the set up and handles the Linux container applying Docker.


Although this Dockers and Kubernetes Course Online training in India, USA & UK is meant both for students and professionals, yet you should have a basic knowledge about the Linux server administration and the Linux command line.

So to brush you knowledge and get more focused on career progress, it is very essential to learn new things. Take up this course and know how to handle both of this technologies.

Kubernets is an open-source container orchestration tool or system that is used to automate tasks such as the management, monitoring, scaling, and deployment of containerized applications. It is used to easily manage several containers (since it can handle grouping of containers), which provides for logical units that can be discovered and managed.

Orchestration refers to the integration of multiple services that allows them to automate processes or synchronize information in a timely fashion. Say, for example, you have six or seven microservices for an application to run. If you place them in separate containers, this would inevitably create obstacles for communication. Orchestration would help in such a situation by enabling all services in individual containers to work seamlessly to accomplish a single goal.

K8s is another term for Kubernetes.

Docker is an open-source platform used to handle software development. Its main benefit is that it packages the settings and dependencies that the software/application needs to run into a container, which allows for portability and several other advantages. Kubernetes allows for the manual linking and orchestration of several containers, running on multiple hosts that have been created using Docker.

There are two primary components: the master node and the worker node. Each of these components has individual components in them.

A node is the smallest fundamental unit of computing hardware. It represents a single machine in a cluster, which could be a physical machine in a data center or a virtual machine from a cloud provider. Each machine can substitute any other machine in a Kubernetes cluster. The master in Kubernets controls the nodes that have containers.

Docker Swarm is Docker’s native, open-source container orchestration platform that is used to cluster and schedule Docker containers. Swarm differs from Kubernetes in the following ways:

  • Docker Swarm is more convenient to set up but doesn’t have a robust cluster, while Kubernetes is more complicated to set up but the benefit of having the assurance of a robust cluster
  • Docker Swarm can’t do auto-scaling (as can Kubernetes); however, Docker scaling is five times faster than Kubernetes
  • Docker Swarm doesn’t have a GUI; Kubernetes has a GUI in the form of a dashboard
  • Docker Swarm does automatic load balancing of traffic between containers in a cluster, while Kubernetes requires manual intervention for load balancing such traffic
  • Docker requires third-party tools like ELK stack for logging and monitoring, while Kubernetes has integrated tools for the same
  • Docker Swarm can share storage volumes with any container easily, while Kubernetes can only share storage volumes with containers in the same pod
  • Docker can deploy rolling updates but can’t deploy automatic rollbacks; Kubernetes can deploy rolling updates as well as automatic rollbacks

The main components of a node status are Address, Condition, Capacity, and Info.

Pods are high-level structures that wrap one or more containers. This is because containers are not run directly in Kubernetes. Containers in the same pod share a local network and the same resources, allowing them to easily communicate with other containers in the same pod as if they were on the same machine while at the same time maintaining a degree of isolation.

The Kube-api server process runs on the master node and serves to scale the deployment of more instances.

The kube-scheduler assigns nodes to newly created pods.

The Google Container Engine is an open-source management platform tailor-made for Docker containers and clusters to provide support for the clusters that run in Google public cloud services.

A cluster of containers is a set of machine elements that are nodes. Clusters initiate specific routes so that the containers running on the nodes can communicate with each other. In Kubernets, the container engine (not the server of the Kubernets API) provides hosting for the API server.

A Daemon set is a set of pods that runs only once on a host. They are used for host layer attributes like a network or for monitoring a network, which you may not need to run on a host more than once.

Namespaces are used for dividing cluster resources between multiple users. They are meant for environments where there are many users spread across projects or teams and provide a scope of resources.

  • Default
  • Kube – system
  • Kube – public

A Heapster is a performance monitoring and metrics collection system for data collected by the Kublet. This aggregator is natively supported and runs like any other pod within a Kubernetes cluster, which allows it to discover and query usage data from all nodes within the cluster.

The controller manager is a daemon that is used for embedding core control loops, garbage collection, and Namespace creation. It enables the running of multiple processes on the master node even though they are compiled to run as a single process.

Kubernets uses etcd as a distributed key-value store for all of its data, including metadata and configuration data, and allows nodes in Kubernets clusters to read and write data. Although etcd was purposely built for CoreOS, it also works on a variety of operating systems (e.g., Linux, BSB, and OS X) because it is open-source. Etcd represents the state of a cluster at a specific moment in time and is a canonical hub for state management and cluster coordination of a Kubernets cluster.

The primary controller managers that can run on the master node are the endpoints controller, service accounts controller, namespace controller, node controller, token controller, and replication controller.

Dockers and Kubernates:

  • Installing Docker on Ubuntu
  • Installing Docker on CentOS
  • Updating Docker
  • Granting Docker Control to Non-root Users
  • Configuring Docker to Communicate Over the Network
  • Playing Around with Our First Docker Container
  • Module Intro
  • The docker Bridge
  • Virtual Ethernet Interfaces
  • Network Configuration Files
  • Exposing Ports
  • Viewing Exposed Ports
  • Linking Containers
  • The Build Context
  • Image Layers
  • Caching
  • Base Images
  • Dockerfile Instructions
  • Module Intro
  • The High Level Picture
  • The Docker Engine
  • Docker Images
  • Docker Containers
  • Docker Hub
  • A Closer Look at Images and Containers
  • Volumes
  • Persistent Data and Production Containers
  • Image Layers
  • Union Mounts
  • Where Images Are Stored
  • Copying Images to Other Hosts
  • The Top Writeable Layer of Containers
  • One Process per Container
  • Commands for Working with Containers
  • The run Command
  • Managing Containers
  • Docker Info
  • Container Info
  • Dealing with Images
  • Using the Registry
  • Hands On Use Cases
  • Deploying Web Applications on Docker
  • Kubernetes Setup.
  • Local Setup with minikube.
  • Introduction to Kops.
  • Running first app on Kubernetes.
  • Module Intro
  • Starting and Stopping Containers
  • PID 1 and Containers
  • Deleting Containers
  • Looking Inside of Containers
  • Low-level Container Info
  • Getting a Shell in a Container
  • Health checks.
  • Deploy 4 VM's running centos7 or other Linux.
  • SH to to VM1 and configure it Kubernetes master node
  • SSH to to VM2 and configure it
  • Kubernetes Minion node-01,02,03.
  • Module Intro
  • Introducing the Dockerfile
  • Creating a Dockerfile
  • Building an Image from a Dockerfile
  • Inspecting a Dockerfile from Docker Hub
  • Module Intro
  • Creating a Public Repo on Docker Hub
  • Using Our Public Repo on Docker Hub
  • Introduction to Private Registries
  • Building a Private Registry
  • Using a Private Registry
  • Docker Hub Enterprise
  • POD Autoscaling
  • Rolling Updates
  • POD CPU and Memory reservation
  • Bring down complete cluster and recover back
  • Service Discovery
  • Volumes and Volumes Auto provisioning
  • Pet Sets and Daemon Sets
  • Resource Usage Monitoring
  • Autoscaling
  • Module Intro
  • The Build Cache
  • Dockerfile and Layers
  • Building a Web Server Dockerfile
  • Launching the Web Server Container
  • Reducing the Number of Layers in an Image
  • The CMD Instruction
  • The ENTRYPOINT Instruction
  • The ENV Instruction
  • Volumes and the VOLUME Instruction
  • The Kubernetes Master Services
  • Resource Quotas
  • Namespaces
  • User Management
  • Networking
  • Node Maintenance