May 1, 2024
Updated June 26, 2025
22 minute read
Navigating the World of Google Cloud Platform (GCP)
Google Cloud Platform, commonly known as GCP, is a suite of cloud computing services offered by Google. It runs on the same infrastructure that Google uses to power its end-user products, such as Google Search, Gmail, and YouTube. In essence, GCP provides a way for individuals and organizations to access computing resources—like servers, storage, networking, and even advanced tools for data analytics and machine learning—over the internet on a pay-as-you-go basis. This allows businesses to build, test, and deploy applications without having to invest in and manage their own physical hardware.
Working with GCP can be exciting for several reasons. Firstly, it positions you at the forefront of technological innovation, particularly in areas like artificial intelligence (AI), machine learning (ML), and big data analytics, where Google has a strong reputation. Secondly, the scalability and global reach of GCP mean you could be involved in projects that have a massive impact, serving users across the world. Finally, as cloud adoption continues to surge across industries, skills in GCP are becoming increasingly valuable, opening up diverse and often lucrative career opportunities.
Introduction to GCP
Definition and Scope of Google Cloud Platform (GCP)
Google Cloud Platform (GCP) is a comprehensive suite of public cloud computing services that enables users to access and utilize Google's vast and advanced infrastructure. These services cover a wide spectrum of needs, including computing power, data storage, data analytics, and machine learning. Imagine being able to use the same powerful tools and infrastructure that run Google Search or YouTube for your own projects or business applications; GCP makes this possible. The platform offers a variety of services that can be used individually or combined to create sophisticated, scalable, and resilient solutions.
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Find a path to becoming a GCP. Learn more at:
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Reading list
We've selected 28 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
GCP.
This study guide focuses specifically on the Data Engineer certification for GCP. It covers the objectives of the exam, providing a structured approach to learning about data engineering services and practices on GCP. It's a valuable resource for those looking to specialize in data engineering on GCP and can serve as a comprehensive reference.
Practical guide to building scalable data analytics systems on GCP. It covers key data engineering concepts and how to implement them using GCP services like BigQuery, Cloud Storage, Dataflow, and Dataproc. It's an excellent resource for data engineers and those interested in the data-intensive aspects of GCP.
Written by Google experts, this book shares best practices for designing secure and reliable systems. It integrates security and reliability into the system design lifecycle, offering valuable insights for building robust applications on platforms like GCP. is highly relevant for contemporary cloud development and operations.
A companion to 'Site Reliability Engineering,' this workbook offers practical examples and case studies for implementing SRE principles. It includes examples from Google Cloud Platform customers, making it directly applicable to the GCP context. is valuable for deepening understanding and applying SRE practices in a cloud environment.
A study guide for the Professional Cloud DevOps Engineer certification, this book covers DevOps principles and their implementation on GCP. It includes topics like CI/CD, monitoring, and logging using GCP services. is useful for those focusing on automating and managing workloads on GCP.
This guide is aimed at those seeking the Professional Cloud Network Engineer certification. It provides hands-on experience with implementing and securing networks on GCP, covering VPCs, hybrid connectivity, and network security best practices. It's a specialized book for deepening knowledge in GCP networking.
Authored by Google engineers, this book foundational text on Site Reliability Engineering (SRE) principles and practices. While not solely focused on GCP, it provides invaluable insights into building and operating large-scale distributed systems, which are highly relevant to anyone working with GCP at a professional level. It's considered a classic in the field and essential for understanding the operational aspects of cloud platforms.
For those interested in big data on GCP, this book provides an in-depth look at BigQuery, GCP's serverless data warehouse. It covers everything from querying and data ingestion to optimization and machine learning with BigQuery. It's a specialized book for deepening understanding in a key GCP data service.
Provides a comprehensive introduction to deploying scalable cloud applications on GCP. It covers a wide range of GCP services, from hosting web applications to using AI services, data storage, serverless functions, and Kubernetes. It is an excellent resource for gaining a broad understanding of GCP and its capabilities.
Focuses on designing and managing cloud solutions on GCP from an architectural perspective. It covers identifying suitable GCP services for various use cases and optimizing technical and business processes in the cloud. It's a good resource for architects and those looking to understand solution design on GCP.
Provides a comprehensive guide to machine learning engineering with GCP. It covers the entire machine learning lifecycle, from data preparation and model training to model deployment and monitoring, and shows how to use GCP services such as AI Platform, BigQuery ML, and Cloud ML Engine to perform these tasks.
Widely acclaimed resource on the fundamental principles of data systems. While not specific to GCP, it provides essential background knowledge for anyone designing and building data-intensive applications on any cloud platform, including GCP. It's considered a must-read classic for understanding the complexities of data management in distributed systems.
Provides a comprehensive guide to using GCP for data science. It covers various aspects of data science, including data preparation, data analysis, and machine learning, and shows how to use GCP services such as BigQuery, Cloud Dataflow, and Cloud ML to perform these tasks.
A study guide for the Professional Cloud Developer certification, this book focuses on developing applications on GCP. It covers using various GCP services for application development, deployment, and management. It's a good resource for developers looking to build on GCP.
Provides a collection of recipes for GCP developers. It covers various aspects of GCP, including compute, storage, networking, databases, and machine learning, and provides step-by-step instructions on how to perform common tasks using GCP services.
Provides a comprehensive overview of the fundamental concepts of GCP. It covers the basics of GCP, including its architecture, services, and pricing, and is suitable for beginners who want to learn about the platform.
Focusing on the administrative aspects of GCP, this book is suitable for those who need to manage and deploy applications on the platform. It covers GCP fundamentals, including compute, networking, storage, containers, operations, and security. is valuable for IT administrators and engineers looking to leverage GCP.
With courses mentioning Terraform, this book key resource for infrastructure automation on GCP. It covers using Terraform for provisioning and managing cloud infrastructure, a crucial skill for DevOps and cloud engineers working with GCP. is practical and widely used in the industry.
While a study guide, this book offers a solid foundation in GCP for those starting their cloud journey. It covers the core services and concepts necessary for the Associate Cloud Engineer certification, providing a structured approach to understanding the platform's basics. It's a good starting point for broad understanding and can serve as a textbook for introductory courses.
This cookbook provides practical solutions and examples for common tasks on GCP. It's a useful reference for quickly finding solutions to specific problems and can help solidify understanding through hands-on examples.
Provides a comprehensive guide to GCP for developers. While one of the other books also has this title, this book focuses on sustainability on GCP. It discusses how to build sustainable and eco-friendly applications on GCP using various services and tools offered by the platform.
Given the prevalence of Kubernetes in cloud deployments, this book is highly relevant for understanding container orchestration on GCP (specifically Google Kubernetes Engine - GKE). It provides a comprehensive guide to Kubernetes concepts and practices, essential for modern cloud-native application development and deployment.
Combines cloud-native principles with DevOps practices using Kubernetes. It provides a broader context for implementing DevOps on cloud platforms, including GCP, and is particularly useful for those working with GKE.
Focuses on using GCP for machine learning. It covers the entire machine learning lifecycle, from data preparation and model training to model deployment and monitoring. This book is ideal for readers with experience in machine learning looking to leverage GCP for their projects.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/yiu4ue/gc
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