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

ML services

One of the strongest points of Google is its long-term experience with ML. GCP offers several services around ML. You can choose between a pre-trained model or training the model yourself. The various services included under ML are as follows:

  • Cloud ML Engine: ML Engine is a managed service that allows you to train and host your ML models in GCP. It leverages the TensorFlow application for the training process. The underlying infrastructure is managed by Google, while users can choose from different hardware options. The trained model can be accessed through APIs to perform predictions.
  • Pretrained APIs: ML APIs are services that allow you to leverage several pre-trained models, enabling you to analyze a video. Currently, the following APIs are available:
    • Google Cloud Video Intelligence
    • Google Cloud Speech
    • Google Cloud Vision
    • Google Cloud Natural Language
    • Google Cloud...