Kubernetes For Data Engineering: Hands On End To End Guide

Kubernetes For Data Engineering: Hands On End To End Guide
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English

| Size: 2.42 GB[/center]
| Duration: 2h 18m
Boost the efficiency of your Data Engineering Solutions by Deploying them on Kubernetes Cluster.

What you'll 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.

Requirements

Basic Programming Experience

Description

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!

Overview

Section 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

Section 2: Infrastructure Setup

Lecture 11 Installing Docker Desktop

Lecture 12 Setting up, enabling and verifying Kubernetes

Lecture 13 Installing Cluster Managers on all Operating Systems

Lecture 14 Cluster Manager Commands

Lecture 15 Installing and Setting up Helm Charts

Section 3: Kubernetes Dashboard

Lecture 16 Deploying Kubernetes Dashboard with Helm Charts

Lecture 17 Generating Tokens for Kubernetes Dashboard

Lecture 18 Working with Kubernetes Dashboard - End to End

Section 4: Deploying Apache Airflow to Kubernetes Cluster

Lecture 19 Deploying Apache Airflow on Kubernetes

Lecture 20 Upgrading and Applying Changes to Apache Airflow using Helm Charts

Lecture 21 Creating and Deploying Airflow DAGS to Kubernetes Cluster

Lecture 22 Deploying and Working with Multiple DAGS on Kubernetes Cluster

Lecture 23 Optimising your Airflow DAG pipeline on Kubernetes

Section 5: Apache Spark Deployment on Kubernetes Cluster

Lecture 24 Preparing Spark Jobs to run on Kubernetes

Lecture 25 Packaging your Spark Jobs on Kubernetes

Lecture 26 Deploying Spark Jobs to Kubernetes Cluster

Lecture 27 Fixing Potential Bugs during Spark Deployment on Kubernetes Cluster

Section 6: Next Steps (Resources and Documentations)

Lecture 28 Course Resources (Source Code)

Lecture 29 Commands, Text and Documentation

Everybody interested in building scalable and efficient infrastructures