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 to 4 are based on the data pipeline shown in Figure 9.22. The pipeline has the default configurations and the following resources:

  • Pub topic = t1, and subscription = s1
  • Dataflow job = df1, with a GCS bucket called b1
  • BigQuery dataset = ds1, and table = ds1-table
Figure 9.22 – GCP data pipeline

Figure 9.22 – GCP data pipeline

1. Which of the following is not part of df1’s metrics?

A. Latency

B. CPU

C. Memory

D. Storage

2. What machine types will be used by df1’s workers?

A. n1-standard

B. f1-micro

C. e2-medium

D. g1-small

3. When defining BigQuery table names, what’s your recommendation?

A. Use delimited identifiers

B. Use different versions of SQL

C. It doesn’t matter since you can change the table name on the fly

D. Use something related to the pipeline

4. We need to update df1 without losing any existing data. What’s your recommendation?

A. Update...