Book Image

Professional Cloud Architect – Google Cloud Certification Guide

By : Konrad Cłapa, Brian Gerrard
Book Image

Professional Cloud Architect – Google Cloud Certification Guide

By: Konrad Cłapa, Brian Gerrard

Overview of this book

Google Cloud Platform (GCP) is one of the leading cloud service suites and offers solutions for storage, analytics, big data, machine learning, and application development. It features an array of services that can help organizations to get the best out of their infrastructure. This comprehensive guide covers a variety of topics specific to Google's Professional Cloud Architect official exam syllabus and guides you in using the right methods for effective use of GCP services. You'll start by exploring GCP, understanding the benefits of becoming a certified architect, and learning how to register for the exam. You'll then delve into the core services that GCP offers such as computing, storage, and security. As you advance, this GCP book will help you get up to speed with methods to scale and automate your cloud infrastructure and delve into containers and services. In the concluding chapters, you'll discover security best practices and even gain insights into designing applications with GCP services and monitoring your infrastructure as a GCP architect. By the end of this book, you will be well versed in all the topics required to pass Google's Professional Cloud Architect exam and use GCP services effectively.
Table of Contents (26 chapters)
Free Chapter
1
Section 1: Introduction to GCP
5
Section 2: Managing, Designing, and Planning a Cloud Solution Architecture
15
Section 3: Designing for Security and Compliance
17
Section 4: Managing Implementation
19
Section 5: Ensuring Solution and Operations Reliability
21
Section 6: Exam Focus

Additional considerations

There are other services offered by Google that we wish to highlight.

  • Dataprep: This is a web application that allows us to define preparation rules for our data by interfacing with a sample of the data. Like many of the other services we have discussed, Dataprep is serverless, meaning no upfront deployments are required. It can accept raw data and preprocess this before handing over to Cloud Dataflow to refine the data. Refer to https://cloud.google.com/dataprep/ for more information.
    We recommend that you refer to the Further reading section if you are interested in learning more.
  • Datalab: This is built on Jupyter (formerly IPython), which is an open source web application. Datalab is an interactive data analysis and machine learning environment. We can use this product to visualize and explore data using Python and SQL interactively. This would be...