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

Practice questions

Questions 1-8 are based on the data analytics pipeline in the AWS cloud shown in Figure 5.37. An engineer is designing a pipeline that will ingest long-term, big-volume streaming data from the web using Kinesis Data Streams, then make two copies: one copy pass to Kinesis Firehose and stored in an Amazon S3 bucket, the other data copy will be processed with Amazon EMR and then queried by Athena and visualized using Amazon QuickSight. Performance and costs are the main factors to be taken into account.

Figure 5.37 – Data analytics pipeline in the AWS cloud (redraw)

Figure 5.37 – Data analytics pipeline in the AWS cloud (redraw)

1. What instances would you recommend for the EMR cluster?

A. Reserved Instances for the cluster

B. Spot Instances for core and task nodes and a Reserved Instance for the master node

C. Spot Instances for the cluster

D. On-demand instances for the cluster

2. What filesystem would you recommend for the EMR cluster?

A. HDFS with a consistent view

B...