DevOps - Dockers And Kubernetes Training in Pune
Introduction of Docker & Kubernetes Course
Docker and Kubernetes are prominent names, highly appreciated for software development and deployment. Kubernetes is an open-source container–orchestration system used for automating the process of application development, scaling, and management. It intends to ensure a seamless platform to automate implementation, scaling, and procedures of application containers across clusters of hosts. Google designed it in 2014, and right now, it has been maintained by the Cloud Native Computing Foundation. It works with a different type of container tool comprising Docker. Many cloud services provide a Kubernetes-based platform as a service (IaaS or PaaS) on which Kubernetes can be implemented as a platform providing service. Moreover, many providers additionally offer their own branded Kubernetes distributions.
Docker is a platform that uses OS-level virtualization to offer software in applications referred to as containers. Containers are remoted from each other and package their own software, libraries, and configuration files; they can communicate with every different through well-defined channels. The fact is, all containers are executed by means of a single operating system kernel and are therefore highly lightweight than virtual machines. Docker Inc, designed in 2013, and users can avail of this service free or for premium tiers.
Dockers, being utilized by tech giants, which include Google and Microsoft, will maintain to remain in fashion.
Moreover, it’s simple to orchestrate a handful of containers and programs without delay, and the undertaking grows exponentially while the numbers attain masses or lots. This is wherein Kubernetes and container orchestration is available in place to assist in the control, automation, and scaling of packages that can be containerized. Even though both these applications Docker and Kubernetes are seemed comparable, they function at different layers and also can be used collectively. They may be the idea of as analogous to an airport. In a case, containers are aircraft, Kubernetes is the air traffic control.
What are Docker and Kubernetes?
- What is Docker?
Docker is a prominent software containerization platform that packages the application into one standardized unit, enfolding it into an entire file system that includes everything required to execute on a server.
- What is Kubernetes?
Kubernetes is a software developed by Google to self-regulate the deployment, ascending, and supervision of containerized applications.
Concisely, these two software together makes it easier to install, transport, and maintain complicated software applications anytime, anywhere.
Essential features of Docker
Docker is very necessarily needed during the development, analyzing, testing, and also on the deployment processes of a software project. The fact is, the docker container works in the same way in each environment; it’s seamless the implementation of a software application into a complicated environment.
- It works in isolated environments for managing the applications
- It can be easily Modeling
- It has a version control
- It has an application Agility
- It offers operational Efficiencies
- It provides productivity for developers
Essential features of Kubernetes
Kubernetes is a robust tool able to perform a lot of tasks. It makes sure that the production application is executing in the ways as it should be. Briefly, it turns the applications self-healing. It means it assists in finding out detects or errors at the time when an existing container goes to an unresponsive state, and it takes a new one to swap it.
- It offers easy service with pods
- It is the biggest community among container orchestration tools.
- It provides a different storage option like public clouds, on-premises SANs, etc.
- It was developed by Google.
Drawbacks of Docker and Kubernetes
The biggest drawback of Kubernetes is that it has a massively complicated configuration or configuration process while the Docker isn’t able to ensure any storage option.
Why From 3RI?
To learn about Kubernetes & Dockers from the best provider is essential, 3RI is deemed as the best destination to learn about these. It makes the users aware of the following:
- It offers wide hands-on with Kubernetes & Dockers components
- It includes Kubernetes & Dockers Components, installation, and architecture
- It will make the users learn how to expose the app outside the cluster
- It makes the users aware of the process of setting up stateless and stateful apps on the cluster
- It makes the users know the cases of Docker and Containers
What will you learn?
VMs & Containers
You will learn about Containers and know the basic difference between VMs and Containers.
You will learn how to install Docker and know all the concepts needed for Docker Architecture, installation, and Components.
You will learn how to use Docker Orchestration Services comprising Docker Compose and Docker Swarm.
Microservices & Monolithic applications
You will learn about the basic difference between Monolithic and Microservices applications.
You will be able to know the work to do with the docker Registry for pushing and pulling images and find out the other features.
Docker Volumes & Networks
You will know the exact understanding of the concepts near Docker Volumes and Docker Networks.
You will be able to learn how to install Kubernetes, along with its role and advantages.
Docker Swarm & Kubernetes
You will gain the information along with the difference between Docker Swarm and Kubernetes.
Create with Kubernetes
You will gain knowledge of how to work with Kubernetes to create Pods, deployments, and services.
1. DevOps Introduction
- What is DevOps?
- Why DevOps is needed?
- DevOps Transition?
- Technical Challenges
- DevOps Market Trends
- Various DevOps Tools
- DevOps pipelines
2. Basic Linux and Networking Concepts
- Architecture and Filesystem of Linux
- Linux Bash Commands
- Managing Services on Linux
- User and Group management
- Filesystem usage.
- IP assignment and Service Ports
- Installing and Configuring Apache
3. Cloud Computing with AWS
- Fundamentals of Cloud Computing
- Introduction to AWS
- AWS Cloud - EC2, Security Groups, Amazon Machine Images
- Key Management, Elastic & Public IP
- IAAS PAAS SAAS,S3,Roles,Policies etc.
- VPC creation and understanding Networking in AWS
- Hypervisor, Baremetals, KVM,XEN
- Why Cloud is required for DevOps
- AWS – Defining EC2 Instances
- Introduction to ELB, CDN, Auto Scaling
4. Shell Scripting
- Understanding fundamentals of Software Programming
- Scripting Introduction
- Shell Scripting - Learning to automate Operating System
5. Source Code Management and Version Control
- Source Code Management using GitHub
- History of version control systems
- Centralized vs Distributed version control system
- Source Code Management System using Github
- Working on Git Command Line and GitHub GUI
- Cloning and check-in and committing. Repository creation etc
- Build Tools (Maven/Graddle)
- Understanding Branching, Merging, Forking, pull etc
6. Continuous integration with Jenkins
- Jenkins - Installation
- Jenkins - Configuration
- Jenkins - Management
- Jenkins - Setup Build Jobs
- Integration of JENKINS with GIT
- Integration of Maven with Jenkins
- Jenkins Dashboard
- Remote Builds and user management in Jenkins
- Understating Plugins and dependency
- Pipeline Creation using Jenkins for CI
- Jenkins - Testing
7. Chef and its Component
- Chef: Introduction
- Chef: knife
- Chef: knife demo
- Chef: knife with chef-server
- Chef: Roles
8. Continuous Monitoring with Nagios
- Host Monitoring using Nagios
- Nagios Coding Language
- Windows Monitoring
- Linux Monitoring
- Port Monitoring
9. Ansible, Infrastructure as a Code
- Understanding Configuration Management
- Understanding Configuration Automation
- Understanding Desired State Configuration Management
- Understanding Continuous Configuration Automation
- Understanding Server Client based Configuration Automation
- Understanding Remote Configuration Automation
10. Ansible Tool
- Introduction of Ansible tool
- Introduction to YAML Syntax
- How to Install Ansible?
- Ansible: Playbooks and Modules live examples on several industry scenarios
- Basic: Running Commands
- Ansible: Roles, Files, Templates, Handlers
- Ansible: Best Practices
11. Docker Session & Orchestration Tools
- Introduction to micro services
- Introduction to Docker
- Introduction to Docker commands practical
- Working with containers
- Introduction to docker HUB
- Docker Demo
- Docker Swarm
- Docker Compose
- What is Kubernetes
- Technical Overview of Kubernetes
- What is Terraform
- Build infrastructure using Terraform code
- Change, destroy, manage infrastructure
- Integrating Terraform on AWS
- Updates to existing setup using Terraform
1. Ansible Case Studies:
- Ansible playbook to install apache and configure httpd.conf as per required.
- httpd daemon should be started and change index.html using lineinmodule for specific parameters
- Ansible playbook using copy module to copy the vsftpd/httpd conf file to /var/www location
- Replace all instances of 'AllowOverride None' with 'AllowOverride AuthConfig' in /etc/httpd/conf/httpd.conf using replace module or lineinmodule
- Files copied should have backup in place and read permissions for all users
- Playbook to copy /usr/local/bin/runme.sh to /usr/bin/runme.sh on all nodes and the files should have execute permissions and owned by DevOps users
- Ansible playbook to create users and add them to respective groups
- Ansible playbook to execute multiple playbooks at same time without executing single yml every time
- Hardening of AWS instances to be done where httpd/nfs needs to be installed
- Users can be created with specific privileges, crontabs should be added with desired ask
- DNS entries needs to be updated etc/httpd/conf/httpd
- Understand Templates, Roles, Handlers etc in Ansible and best practices being used in Production environment
2. Terraform Case Studies:
- Terraform code to create 5-7 EC2 instances at same time
- Terraform code for dependency module
- Code to create multiple EC2 instances only if s3 bucket exists else discard the spawning.
- Create multiple users in AWS using terraform code at same time with specific privileges
- How to destroy only specific type instances from an existing code or run only specific task for an existing terraform code without hampering other running infrastructure.
- Best other practices for terraform and limitations
3. Jenkins Case Studies:
- Jenkins project to integrate Git with it. Run remote builds using Jenkins and later push/pull the builds from Git so that its automatically picked via Jenkins
- Project to integrate Maven with Jenkins and automate project to do Maven build using Jenkins
- User management using specific plugins in Jenkins so that all users doesn’t have access to all projects in Jenkins. Security tuning in Jenkins
- Other best practices used in companies for Jenkins
- Pipeline creation using Jenkins to automate several tasks.
- Several scenarios to do actual troubleshooting in Jenkins related to errors, failures in builds.
1. Understanding Containers?
2. Start with Docker
3. Install docker on Linux/windows
4. Understand :
- Docker images
- Docker repository
- Docker commands
5. Run your first containers
6. build container images
7. Mount local volumes to docker container
8. Get into a container, login to a container
9. Deploy static html website using docker
10. Deploy java application using docker container
12. See container insights using docker stats
13. Docker best practices
1. Why Kubernetes?
2. What is Kubernetes?
3. Install Kubernetes/minikube and kubetools
- Kubernetes architecture
5. Understand use case of Kubernetes
6. deploy first container in Kubernetes
7. learn data persistence
8. Access kube dashboard
9. Scale your containers
10. Load balance containers
11. Kubernetes best practices
Docker and Kubernetes are both effectual de-facto solutions to cleverly control containerized programs and offer robust capabilities, and from this, a few confusions have developed. Kubernetes is now occasionally used as a shorthand for the whole environment based totally on Kubernetes. In fact, they’re no longer without delay comparable, have specific roots, and used for various things.
Docker is a tool used for building, distributing, and executing Docker containers. It gives its very own local clustering device that can be used to orchestrate and plan containers on machine clusters while kubernetes is considered as a container orchestration technique for docker containers that are extra considerable than Docker Swarm and is supposed to coordinate clusters of nodes at scale in manufacturing in a worthwhile way. It executes around the concept of pods that are scheduling units in the Kubernetes environment, and they’re allotted among nodes to ensure high availability. The fact is, the users can seamlessly execute a docker establish on a Kubernetes cluster; however, kubernetes itself isn’t a whole solution and is supposed to encompass custom plugins.
In a nutshell, Docker and Kubernetes are each fundamentally exceptional technology; however, they execute very well collectively, and each facilitates the control and implementation of containers in a dispensed architecture.
|When released||It was released in 2013 by Docker Inc||It was released in 2014 by Google|
|How’s during a cluster Setup?||It is daunting and challenging.||It is simple as its cluster strength is not too strong.|
|About installation||It is easy and seamless to install||It is complicated to install, thus time-consuming.|
|Can it support for logging and monitoring?||It permits the users to use a 3rd party tool such as ELK.||It permits an in-built tool for users for logging and monitoring.|
|How’s it Scalable?||It is faster than K8S, however, it’s cluster strength is not as solid.||It is lesser scalable than docker, but it guarantees robust cluster.|
|Optimized For||Optimized for a single large cluster||Optimized for multiple smaller clusters of SDLC|
|How much node Support?||It supports more than 2000 nodes||It supports not more than 5000 nodes|
|What’s container limit?||It is limited to around 95000 container||It is limited to around 300000 containers|
|Where it applicable?||It is used by Pinterest, eBay, Spotify, Twitter, etc.||It is used by Buffer, Evernote, 9GAG, Intuit, etc.|
|About auto-scaling||It doesn’t auto-scale||It is auto-scaled|
|How’s it tolerance ratio?||It has a high fault tolerance||It has a low fault tolerance|
|What’s its compatibility?||It is less extensive and customizable||It is more comprehensive and massively customizable|
|What’s it data volume?||It assists in sharing storage volumes among different containers in the similar Pod.||It assists to share storage volumes with other containers.|
Kubernetes helps better demands with greater complexity even as Docker Swarm offers an easy solution that is instant to get started out with. Docker Swarm has been quite popular among application developers who need fast deployments and ease. Concurrently, Kubernetes is used in production environments through numerous top-notch internet companies executing popular offerings.
Concisely, both Docker and Kubernetes run most of the same services, however may also need barely unique approaches to certain information. So, via getting to know Kubernetes and Docker and evaluating them for different functions, you can make a decision on selecting the right device for your container orchestration.
Kubernetes is an open-source platform created in 2014 by Google. It is needed to control a containerized application in diverse kinds of virtual, physical, and cloud environments. It is a massively flexible container device used seamlessly even in the most complex applications. It also permits the users to manage their containerized application more effectually and flawlessly.
Features of Kubernetes:
- It offers automated scheduling
- It has self-healing skills
- It has enterprise-ready features
- It automates rollouts and rollback
- It has an application-centric management
- It offers horizontal Scaling & Load Balancing
- It ensures a massive density of resource utilization
- It ensures declarative configuration
- It has an auto-scalable infrastructure
- It offers predictable infrastructure
- It ensures environment consistency during development, analysis, testing, and production