Preface

Google Cloud Platform (GCP) provides autoscaling compute power and distributed in-memory cache, task queues, and datastores to write, build, and deploy Cloud-hosted applications.This course will help you develop and deploy scalable applications from scratch and make them globally available in almost any language. This course will guide you in designing, deploying, and managing applications running on Google Cloud. You’ll start with App Engine and move on to work with Container Engine, compute engine, and cloud functions. You’ll learn how to integrate your new applications with the various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. The next instalment of the course starts with practical recipes that explain how to utilize Google Cloud's common services. There are recipes for implementing authentication and security, Cloud APIs, command-line management, deployment management, and the Cloud SDK. Finally, we'll cover administration troubleshooting tasks with the Compute and Container Engines and we'll show how to monitor your organization's efficiency with best practices.By the end of this course, you’ll be well-versed with all the development tools of Google Cloud Platform, and you’ll develop, deploy, and manage highly scalable and reliable applications.

This Learning Path includes content from the following Packt products:

• Google Cloud Platform for Developers by Ted Hunter and Steven Porter
• Google Cloud Platform Cookbook by Legorie Rajan PS

Who this book is for

This book is designed for developers, IT professionals, and engineers, looking at implementing Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this course useful. 

What this book covers

Chapter 1, Why GCP?, this chapter introduces readers to the Google Cloud Platform. It provides an overview of cloud computing, a brief history of GCP, as well as a comparison to other public cloud providers.

Chapter 2, The Google Cloud Console, this chapter serves to familiarize readers with the primary user interfaces they will use when interacting with Google Cloud.

Chapter 3, APIs, CLIs, IAM, and Billing, in this chapter, readers will learn about the various command line tools provided by Google for managing cloud resources. Readers will also learn about the other tools that will enable them to manage their Google Cloud projects throughout the book.

Chapter 4, Google App Engine, this chapter will explain what Google App Engine (GAE) is, the driving philosophies behind it, and how to use it to run highly-scalable services.

Chapter 5, Google Kubernetes Engine, this chapter is about the Google Container Engine (GKE) platform for running and managing services on Google Cloud.

Chapter 6, Google Cloud Functions, this chapter is about creating and executing Cloud Functions using Google's serverless platform.

Chapter 7, Google Compute Engine, this chapter is about Google's IaaS offering: Google Compute Engine (GCE). This chapter will introduce readers to on-demand VMs and how they can be managed, scaled, and customized to the user's needs.

Chapter 8, NoSQL with Datastore and Bigtable, this chapter will introduce readers to the document based storage solutions offered by Google, including Datastore (plus the new Firestore), and Bigtable.

Chapter 9, Relational Data with Cloud SQL and Cloud Spanner, this chapter will cover Google's relational data storage solutions, including managed MySQL and PostgreSQL via Cloud SQL, as well as globally consistent relational data via Cloud Spanner.

Chapter 10, Google Cloud Storage, this chapter is about Google's unified object storage platform: Google Cloud Storage (GCS).

Chapter 11, Stackdriver, this chapter will cover Google's Stackdriver monitoring, logging, and diagnostics suite to drive application insights, availability, and fast incident resolution.

 

 

Chapter 12, Change Management, this chapter will introduce readers to the various platform tools Google offers around the developer/operations experience, including source control, building and deploying services.

Chapter 13, GCP Networking for Developers, this chapter will introduce readers to networking on Google Cloud, covering the products available and how to use them to build custom networking and security solutions. These topics will be presented in a manner appropriate for developers rather than networking professionals.

Chapter 14, Messaging with Pub/Sub and IoT Core, this chapter will introduce readers to the distributed messaging offerings on Google Cloud. Readers will learn how to leverage Google Cloud Pub/Sub for high-throughput messaging used both in service to service communications and Big Data ingestion pipelines, as well as Cloud IoT Core for widely distributed event-driven application architectures.

Chapter 15, Integrating with Big Data Solutions on GCP, this chapter will provide a high-level overview of big data solutions on the Google Cloud Platform. Users will learn how to build highly scalable, fully managed big data solutions with the power of Cloud Dataflow and BigQuery.

Chapter 16, Compute, contains recipes on the compute services of the GCP, namely Google Compute Engine, Google App Engine, Kubernetes Engine, and Google Cloud Functions.

Chapter 17, Storage and Databases, provides some recipes on Google Cloud Storage and some of the database options available (Cloud Spanner, Cloud BigQuery, Cloud Bigtable, and Cloud Datastore).

Chapter 18, Networking, provides a few advanced recipes on connecting two networks and handling traffic to websites

Chapter 19, Security, discusses how to use some out-of-the-box security tools provided by the GCP and how GCP provides APIs to set up your own security systems.

Chapter 20, Machine Learning and Big Data, contains a few recipes that show the breadth of the big data offerings of GCP and some applied machine learning APIs, which will be directly consumed for our needs.

 

Chapter 21, Management Tools, shows us some recipes on the Stackdriver suite and the logging system to help us manage our Cloud Platform.

Chapter 22, Best Practices, covers some third-party tools and processes that can be used at the enterprise scale to derive the maximum benefit from the GCP.

To get the most out of this book

This book is geared towards readers with a familiarity with basic application development and DevOps concepts. The exercises provided in this book include Java, Python, Node.js, Go, SQL, and shell scripting. These exercises are designed to be simple and easy to complete without prior knowledge of a specific language or framework.

All examples and exercises in this book can be completed directly within the Google Cloud Console and Google Cloud Shell, however many users will prefer to work within a local development environment. To do so, download and install the Google Cloud SDK available at https://cloud. google. com/sdk/.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packt.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the SUPPORT tab.
3. Click on Code Downloads & Errata.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

 

The code bundle for the book is also hosted on GitHub at  https://github.com/TrainingByPackt/BuildingGoogleCloudPlatformSolutions .In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalogue of books and videos available at https://github.com/PacktPublishing/. Check them out!

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "The input() method is used to get an input from the user."

A block of code is set as follows:

{
"eventId": "27819225098479",
"timestamp": "2018-01-27T18:11:24.836Z",
"eventType": "providers/cloud.pubsub/eventTypes/topic.publish",
"resource": "projects/<PROJECT_ID>/topics/<TOPIC_NAME>",
"data": {
"@type": "type.googleapis.com/google.pubsub.v1.PubsubMessage",
"attributes": {
"<KEY1>": "<VALUE1>",
"<KEY2>": "<VALUE2>"
},

Any command-line input or output is written as follows:

gcloud compute instances create my-custom-instance \
--region=us-central1 \
--memory=12GiB \
--cpu=2

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "If you need something different, click on the DOWNLOADS link in the header for all possible downloads:"

 

Note

Warnings or important notes appear like this.

Note

Tips and tricks appear like this.

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