Book Image

Professional Cloud Architect Google Cloud Certification Guide - Second Edition

By : Konrad Cłapa, Brian Gerrard
5 (1)
Book Image

Professional Cloud Architect Google Cloud Certification Guide - Second Edition

5 (1)
By: Konrad Cłapa, Brian Gerrard

Overview of this book

Google Cloud Platform (GCP) is one of the industry leaders thanks to its array of services that can be leveraged by organizations to bring the best out of their infrastructure. This book is a comprehensive guide for learning methods to effectively utilize GCP services and help you become acquainted with the topics required to pass Google's Professional Cloud Architect certification exam. Following the Professional Cloud Architect's official exam syllabus, you'll first be introduced to the GCP. The book then covers the core services that GCP offers, such as computing and storage, and takes you through effective methods of scaling and automating your cloud infrastructure. As you progress through the chapters, you'll get to grips with containers and services and discover best practices related to the design and process. This revised second edition features new topics such as Cloud Run, Anthos, Data Fusion, Composer, and Data Catalog. By the end of this book, you'll have gained the knowledge required to take and pass the Google Cloud Certification – Professional Cloud Architect exam and become an expert in GCP services.
Table of Contents (25 chapters)
1
Section 1: Introduction to GCP
5
Section 2: Manage, Design, and Plan a Cloud Solution Architecture
14
Chapter 12: Exploring Storage and Database Options in GCP – Part 2
17
Section 3: Secure, Manage and Monitor a Google Cloud Solution
21
Section 4: Exam Focus

GCP ML options

With GCP, you have multiple options when it comes to leveraging ML. Which one you choose largely depends on your use case and how knowledgeable you are on the topic. The following options are available:

  • TensorFlow (for a data scientist): This is an option for those who want to work with ML from scratch. It is a software library that's developed and open-sourced by Google. There are more libraries on the market, but this one is the most popular and is used by other cloud providers for their managed ML services.
  • Vertex AI (for a data scientist): This is an option for those who want to train their own models but who use Google for training and predictions. It is a managed TensorFlow/Kubeflow service that offloads all infrastructure and software bits from users.
  • Pretrained ML models (for a developer): This is an option for those who want to leverage ML without having any knowledge of it. It allows Google-developed models to be used to perform predictions...