Book Image

The Self-Taught Cloud Computing Engineer

By : Dr. Logan Song
Book Image

The Self-Taught Cloud Computing Engineer

By: Dr. Logan Song

Overview of this book

The Self-Taught Cloud Computing Engineer is a comprehensive guide to mastering cloud computing concepts by building a broad and deep cloud knowledge base, developing hands-on cloud skills, and achieving professional cloud certifications. Even if you’re a beginner with a basic understanding of computer hardware and software, this book serves as the means to transition into a cloud computing career. Starting with the Amazon cloud, you’ll explore the fundamental AWS cloud services, then progress to advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure Cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds while distinguishing their unique features. You’ll further enhance your skills through practical experience on these platforms with real-life cloud project implementations. Finally, you’ll find expert guidance on cloud certifications and career development. By the end of this cloud computing book, you’ll have become a cloud-savvy professional well-versed in AWS, Azure, and GCP, ready to pursue cloud certifications to validate your skills.
Table of Contents (24 chapters)
1
Part 1: Learning about the Amazon Cloud
9
Part 2:Comprehending GCP Cloud Services
14
Part 3:Mastering Azure Cloud Services
19
Part 4:Developing a Successful Cloud Career

Understanding the AWS big data pipeline

With the rise of big data and the increasing availability of data analytics tools and technologies, data analytics has become an essential component of modern business operations. Cloud-based technologies and services have been widely used to analyze and derive insights from big data, and provide the following benefits:

  • Scalability: Cloud-based data analytics systems can scale up or down based on the input volume of data and traffic, allowing businesses to handle large-scale datasets without having to invest in expensive hardware and infrastructure
  • Cost-effectiveness: Cloud-based data analytics systems are typically pay-as-you-go, allowing businesses to only pay for the resources they need and avoid extra investment in expensive hardware and infrastructure
  • Flexibility: Cloud-based data analytics provides a flexible and agile environment for processing and analyzing data, allowing businesses to select the best from different techniques...