HOME > Development > Kubernetes for Data Engineering- Hands on End to End Guide

Kubernetes for Data Engineering- Hands on End to End Guide

  • Development
  • Feb 13, 2025
SynopsisKubernetes for Data Engineering: Hands on End to End Guide, a...
Kubernetes for Data Engineering- Hands on End to Guide  No.1

Kubernetes for Data Engineering: Hands on End to End Guide, available at $54.99, has an average rating of 4.5, with 29 lectures, based on 3 reviews, and has 44 subscribers.

You will learn about Understand the core concepts of Kubernetes, including pods, services, deployments, and more. Learn how to set up and manage a Kubernetes cluster Gain practical experience in deploying and managing the Kubernetes Dashboard, a powerful tool for managing Kubernetes clusters through a user-friendly interface Learn how to deploy Apache Airflow in a Kubernetes environment. Understand how to schedule and monitor data pipelines efficiently using Airflow. Dive into the world of Directed Acyclic Graphs (DAGs) and learn how to create, schedule, and monitor them in an Airflow environment running on Kubernetes. Understand how to secure your Kubernetes cluster and monitor its performance. Learn about Kubernetes namespaces, RBAC, secrets, and network policies. Learn how to scale your data applications and ensure high availability within your Kubernetes cluster. Develop skills to troubleshoot common issues in Kubernetes and optimize the performance of your data pipelines. This course is ideal for individuals who are Everybody interested in building scalable and efficient infrastructures It is particularly useful for Everybody interested in building scalable and efficient infrastructures.

Enroll now: Kubernetes for Data Engineering: Hands on End to End Guide

Summary

Title: Kubernetes for Data Engineering: Hands on End to End Guide

Price: $54.99

Average Rating: 4.5

Number of Lectures: 29

Number of Published Lectures: 29

Number of Curriculum Items: 29

Number of Published Curriculum Objects: 29

Original Price: £34.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand the core concepts of Kubernetes, including pods, services, deployments, and more. Learn how to set up and manage a Kubernetes cluster
  • Gain practical experience in deploying and managing the Kubernetes Dashboard, a powerful tool for managing Kubernetes clusters through a user-friendly interface
  • Learn how to deploy Apache Airflow in a Kubernetes environment. Understand how to schedule and monitor data pipelines efficiently using Airflow.
  • Dive into the world of Directed Acyclic Graphs (DAGs) and learn how to create, schedule, and monitor them in an Airflow environment running on Kubernetes.
  • Understand how to secure your Kubernetes cluster and monitor its performance. Learn about Kubernetes namespaces, RBAC, secrets, and network policies.
  • Learn how to scale your data applications and ensure high availability within your Kubernetes cluster.
  • Develop skills to troubleshoot common issues in Kubernetes and optimize the performance of your data pipelines.
  • Who Should Attend

  • Everybody interested in building scalable and efficient infrastructures
  • Target Audiences

  • Everybody interested in building scalable and efficient infrastructures
  • This is a Kubernetes For Data Engineering practical hands-on course based on a lot of requests by students.

    Are you ready to elevate your data engineering skills to the next level?

    This course has been meticulously designed to help you immerse yourself into the world of Kubernetes, the powerful tool revolutionizing the management of containerized applications. Join us in this comprehensive course where we explore Kubernetes and its practical applications in the realm of data engineering.

    This course is suitable for all levels of experience from beginners to expert as it has been designed to equip you with essential knowledge and hands-on experience.

    Here are what you’ll learn:

  • Understanding Kubernetes: Explore the fundamentals of Kubernetes, including its architecture, core concepts, and additional services, to grasp its significance in modern data engineering.

  • Kubernetes Deployment: Learn how to set up Kubernetes on Docker, master kubectl for cluster management, and deploy the Kubernetes Dashboard for efficient cluster administration.

  • Exploring Kubernetes Components: Dive into Kubernetes components such as Kubelet, KubeProxy, container runtimes, and additional services to gain a comprehensive understanding of their roles in the Kubernetes ecosystem.

  • Kubernetes Networking Fundamentals: Delve into the networking fundamentals of Kubernetes to understand how containerized applications communicate within a Kubernetes cluster.

  • Harnessing Kubernetes for Data Engineering:Discover how Kubernetes can empower you as a data engineer, streamlining processes, enhancing scalability, and facilitating efficient management of data workflows.

  • Setting Up Kubernetes on Docker: Start from the basics as we guide you through setting up Kubernetes on Docker. Perfect for newcomers or those looking to refresh their understanding.

  • Mastering kubectl: Learn the ins and outs of kubectl, the command-line tool for managing Kubernetes clusters. Gain proficiency with essential commands and expert tips for seamless navigation.

  • Deploying the Kubernetes Dashboard: Follow step-by-step instructions to deploy the Kubernetes Dashboard, an intuitive interface for efficiently managing Kubernetes clusters.

  • Running Apache Airflow with Helm Charts: Unlock the potential of Apache Airflow, a leading tool for orchestrating complex computational workflows, by running it on Kubernetes using Helm charts.

  • Deploying Apache Spark on Kubernetes Cluster: Explore the deployment of Apache Spark, a powerful framework for distributed data processing, on Kubernetes. Learn how to harness the scalability and flexibility of Spark within a Kubernetes environment.

  • In this detailed course, you’ll have easy access to each section of the course, ensuring a structured and efficient learning experience. From setting up Docker to optimizing Airflow DAGs and deploying Apache Spark on Kubernetes, we cover it all.

    Join us on this journey to master Kubernetes for data engineering and take your skills to new heights.

    Sign up now and accelerate your data mastery journey with us!

    Ready to embark on this exciting adventure? Enroll now and let’s immerse ourselves into Kubernetes for data engineers together!

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Introduction

    Lecture 2: What this course covers

    Lecture 3: Kubernetes Architecture Explained

    Lecture 4: KubeProxy and Container Runtime Deep Dive

    Lecture 5: Kubernetes Additional Services

    Lecture 6: Kubernetes Networking Fundamentals

    Lecture 7: Kubernetes Core Concepts

    Lecture 8: Kubernetes Behind The Scenes

    Lecture 9: Getting Started with Tools for Kubernetes

    Lecture 10: How Kubernetes can help you as an engineer

    Chapter 2: Infrastructure Setup

    Lecture 1: Installing Docker Desktop

    Lecture 2: Setting up, enabling and verifying Kubernetes

    Lecture 3: Installing Cluster Managers on all Operating Systems

    Lecture 4: Cluster Manager Commands

    Lecture 5: Installing and Setting up Helm Charts

    Chapter 3: Kubernetes Dashboard

    Lecture 1: Deploying Kubernetes Dashboard with Helm Charts

    Lecture 2: Generating Tokens for Kubernetes Dashboard

    Lecture 3: Working with Kubernetes Dashboard – End to End

    Chapter 4: Deploying Apache Airflow to Kubernetes Cluster

    Lecture 1: Deploying Apache Airflow on Kubernetes

    Lecture 2: Upgrading and Applying Changes to Apache Airflow using Helm Charts

    Lecture 3: Creating and Deploying Airflow DAGS to Kubernetes Cluster

    Lecture 4: Deploying and Working with Multiple DAGS on Kubernetes Cluster

    Lecture 5: Optimising your Airflow DAG pipeline on Kubernetes

    Chapter 5: Apache Spark Deployment on Kubernetes Cluster

    Lecture 1: Preparing Spark Jobs to run on Kubernetes

    Lecture 2: Packaging your Spark Jobs on Kubernetes

    Lecture 3: Deploying Spark Jobs to Kubernetes Cluster

    Lecture 4: Fixing Potential Bugs during Spark Deployment on Kubernetes Cluster

    Chapter 6: Next Steps (Resources and Documentations)

    Lecture 1: Course Resources (Source Code)

    Lecture 2: Commands, Text and Documentation

    Instructors

  • Kubernetes for Data Engineering- Hands on End to Guide  No.2
    Ganiyu Yusuf
    Big Data Engineer | Solutions Architect
  • Rating Distribution

  • 1 stars: 0 votes
  • 2 stars: 0 votes
  • 3 stars: 0 votes
  • 4 stars: 2 votes
  • 5 stars: 1 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

    Can I take my courses with me wherever I go?

    Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!