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

Bigtable

There is a clue in the name, but Bigtable is GCP's big data NoSQL database service. Bigtable is low latency and can scale to billions of rows and thousands of columns. It's also the database that powers many of Google's core services, such as Search, Analytics, Maps, and Gmail. This makes Bigtable a great choice for analytics and real-time workloads as it's designed to handle massive workloads at low latency and high throughput.

Exam tip: Bigtable can support petabytes of data and is suitable for real-time access and analytics workloads. It's a great choice for Internet of Things (IoT) applications that require frequent data ingestion or high-speed transactions.

Given Bigtable's massive scalability, we will cover the storage model and architecture. When we discuss Bigtable, we will make references to HBase. HBase is effectively an open source...