Kubernetes is a powerful open-source system, initially developed by Google, for managing containerized applications in a clustered environment. It aims to provide better ways of managing related, distributed components and services across varied infrastructure.
Kubernetes, at its basic level, is a system for running and coordinating containerized applications across a cluster of machines. It is a platform designed to completely manage the life cycle of containerized applications and services using methods that provide predictability, scalability, and high availability.
Kubernetes - Exeliq
Prerequisites:
Good knowledge of commands Linux distributions (ubuntu,fedora,centos)
Knowledge knowledge in Python ,shell scritping
knowledge in microservices.
knowledge in RDBMS mysql.
knowledge in basic networking
Target Audience:
This class is for you if:
want to learn how the webcommncation in spider web.
Want to learn and gain experience containerization and orchestration
Have experience in linux system administor and want to enhance knowledge
Have experience in basic Devops engineers and want make career in devops orchestration
Developer who can contribute using orchestration methods
Learning Outcomes:
Upon completion of this course, you will:
Understand benifits of virtulization and containerization
Learn how to convert single comuputing into multi computing system through virtuabox virtualization and docker contianerization
Learn how to develop an orchestration load balanced and high availability
Learn orchestrate though automated deployment methods
Learn how to orchestrate hybrid containers on cetralized and distributed models
Learn how to depoy basic Python based microservices and deploy on application server
Gain Kubernetes knowledge on premise and cloud environment tthough various techniques
Gain Knowledge on Airflow scheduling system through containerization
Course Objectives
At the end of this course, you will be able to:
Install Docker and a Kubernetes cluster from scratch
Learn how to run and manage containers effectively
Create Kubernetes pods, deployments, and services
Build Docker images and configure Docker Hub from scratch
Deploy a multi-component software application efficiently and easily
Training
Curriculum
Introduction
The Focus of this course
Day 1 - Virtualization
1. Introduction to Virtualization
2. Introduction to containers
3. Virtualizion vs Containerized Architecture
4. Centralized containerization vs Distributed containerization
Day 2 - Docker
1. Introduction to Docker
2. Docker Architecture
3. Docker Components
4. Installation of Docker
Day 3 - Docker Commands - I
Most widely used docker commands
Day 4 - Docker Commands - II
Most widely used docker commands
Day 5 - Docker Registry Setup
Deploy a registry server
Basic configuration
Run an externally-accessible registry
USE AN INTERMEDIATE CERTIFICATE
Support for Let’s Encrypt
Run the registry as a service
Load balancing considerations
Important/Required HTTP-Headers
Restricting access
Deploy your registry using a Compose file
Considerations for air-gapped registries
Next steps
Day 6 - Dockerfile
What is Dockerfile?
Why Dockerfile?
Create image with Dockerfile
Day 7 - Docker lab exercise
Empty section. Edit page to add content here.
Day 8 - Intro To Kubernetes
1. Container Orchestration
2. History of Orchestration tools
3. Kubernetes architecture
4. Kubernetes Components
5. Kubernetes concepts
Day 9 - Kubernetes Cluster Setup
Develeper/local Kubernetes
Day 10 - Cloud Agnostic Installation
KUBEADM
KOPS
Day 11 - Self-Hosted Kubernetes Cluster
Single Master multi-node
Provisioning Pod Network Routes
Smoke Testing
Contact Us
Contact Us for the Data Science Foundations Online Course
The next Data Science Foundations Online Course will run from 2019-03-05 to 2019-04-25. Classes are generally held on Tuesdays and Thursdays from 6:30-9:30 PM ET / 3:30-6:30 PM PT, with some exceptions for holidays. The deadline for registration is 2019-02-22. The course tuition is $3495 with early-bird discounts available. The exact dates for the next session will be: 3/5, 3/7, 3/12, 3/14, 3/19, 3/21, 3/25, 3/28, 4/2, 4/4, 4/9, 4/11, 4/16, 4/18, 4/23, 4/25
Testimonials
The data science skills I sharpened at The Data Incubator helped me analyze diversity in STEM education, model SaaS stock prices, and compare industry growth rates. The instructor’s background in ...
From day one I was getting my hands dirty working with data using industry-relevant tools. Having completed the program I’m now better equipped to manage engineering and product teams, and ...
Their heavy focus on applied learning meant that I was working on real data and solving real problems right from the start. While lectures were a valuable component of their ...
A few of our 250+ hiring and training partners:
